Towards a Multi-Dimensional Framework for Assessing the Value of. Software Projects

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1 Towards a Multi-Dimensional Framework for Assessing the Value of Software Projects by John Richard Kopp Submitted in partial fulfillment of the requirements for the Master s degree in Software Development and Engineering at Seidenberg School of Computer Science and Information Systems Pace University June 2009

2 We hereby certify that this thesis, submitted by John Kopp, satisfies the thesis requirements for the Master s degree in Software Development and Engineering and has been approved. - Dr. Olly Gotel Date Chairperson of Thesis Committee - Dr. Frank Marchese Date Thesis Committee Member - Dr. Sotiris Skevoulis Date Thesis Committee Member Seidenberg School of Computer Science and Information Systems Pace University 2009

3 Abstract Towards a Multi-Dimensional Framework for Assessing the Value of Software Projects by John Richard Kopp Submitted in partial fulfillment of the requirements for the Master s degree in Software Development and Engineering June 2009 As the role of software within organizations and within society has increased, so have the costs of producing and maintaining it. Whether the value delivered by software has proportionally increased is a subject of debate. This phenomena has been coined the IT value paradox. Part of the difficulty in establishing value is that it is dependent on perspective. Value at the level of society, value at an organization level and value at an individual project level need to be evaluated differently. Value also depends on the viewpoint of the recipient. That received by society in general differs from that received by consumers and from that received by the organization. This thesis specifically examines the assessment of value of software projects from the perspective of the organization. Value is seen to be multidimensional. Financial value can be measured using techniques such as net present value calculations, internal rate of return and payback period under the assumption that the world is static. Flexibility by management is quantified by real option techniques and the dynamics of the marketplace by game theory. In addition to financial measures, understanding project alignment with the organization and with IT departments is essential to obtaining and understanding the value of projects. A framework incorporating these multiple dimensions is presented to allow systematic valuation of software projects.

4 Acknowledgements I express my sincere gratitude to Dr. Gotel for her guidance, comments and feedback over the last year which greatly assisted me in developing brief initial thoughts on this topic into a more comprehensive understanding and framework. I thank her for teaching me how to perform academic research and how to frame a large topic, such as the one addressed in this thesis, in a manner so that it can be understood and communicated. Learning how to find and define relevant questions and how to fully and properly answer those questions was as valuable as learning the specific content of my thesis. I also thank Dr. Marchese and Dr. Skevoulis for their efforts and feedback over the last year.

5 Table of Contents Abstract... iii List of Tables... x List of Figures... xii List of Equations... xiv Chapter 1 Introduction Overview IT Value Paradox Basic Question Addressed in This Work Research Process Roadmap... 6 Chapter 2 Current State of Practice in Project Valuation Overview Definition of Project Success Earned Value Techniques Introduction Calculation of Earned Value (Example) Predicting Cost at Completion Predicting Task or Project Duration Use of Earned Value Techniques in Project Control Discussion Chapter 3 Prerequisites for Project Valuation Overview Stakeholder Value Proposition Elicitation, Analysis and Reconciliation Overview Benefits Realization Approach v

6 3.2.3 Model Based (System) Architecting and Software Engineering (MBASE) Win-Win Model / Theory W Goal Based Techniques Critical Success Factors Cost Estimation Sales and Marketing Forecasts Discussion Chapter 4 Quantitative Approaches to the Measurement of Value Overview Net Present Value (NPV) / Discounted Cash Flow Present and Future Values Discount Rates Payback Period Internal Rate of Return (IRR) / Return on Investment (ROI) Comparison of NPV, IRR and Payback Period Capital Asset Pricing Model (CAPM) Sensitivity and Scenario Analysis Real Options Introduction Decision Trees Review of Financial Options Valuing Financial Options Upper and Lower Bounds Valuing Options Relationship between Calls and Puts Factors impacting the price of options Black Scholes Formula Introduction to Real Options/ Extended NPV vi

7 Option to Defer Option to Expand Compound Options Example of Application of Black-Scholes Formula Discussion Game Theory Approaches to Project Valuation Introduction Definition of Game Theory Nash Equilibrium / Prisoners Dilemma Example Commitments Games Scenarios Discussion Process Measures Introduction Generic Process Frameworks Process Measures Use of Process Measures Discussion Chapter 5 Qualitative Approaches to the Measurement of Value Overview Balanced Score Cards Introduction Traditional Balanced Scorecards Linking Strategy to Measures Balanced IT Scorecards Corporate Governance vii

8 5.3 Project Portfolio Management / IT Governance Alignment with Organization Strategies and with IT Goals and Architecture Discussion Chapter 6 A Proposed Multi-Dimensional Framework for Project Valuation Introduction Overview of the Framework Portfolio Based Approach Quantitative (Financial) Measures Qualitative Measures Iterative Nature of the Process Project Evaluation Framework Project Valuation Process Effect of Supplier and Customer Types Shrink Wrap Projects (Supplier s Perspective) Shrink Wrap Projects (Customer s Perspective) Bespoke Projects (Supplier s Perspective) Bespoke Projects (Customer s Perspective) Internal Projects Qualitative Evaluations Project Portfolios Weill MIT CISR Framework (Categorization by Investment Type) Ross Beath (MIT CISR) Categorization by Management Objectives Proposed Categorization Scheme Types of Firm Investment Boundary Discussion Chapter 7 Application of the Framework viii

9 7.1 Example Discussion Chapter 8 Conclusions and Future Work Conclusions Future work Glossary References ix

10 List of Tables Table 1 Measures Used in Earned Value Techniques Table 2 Cost and Schedule Variance (Based on [8]) Table 3 Summary of Cost and Schedule Performance Indexes (Based on [8]) Table 4 Cost Estimates at Completion (based on [8]) Table 5 Time Estimates at Completion (based on [8]) Table 6 Evaluation of Critical Success Factors for an Example Project Table 7 Example of NPV Sensitivity Analysis Table 8 Payback Period Example Table 9 Comparison of NPV and IRR on Mutually Exclusive Projects (from [36]) Table 10 Comparison of IRR and NPV for Three Projects Table 11 Comparison of NPV, IRR and Payback Period Table 12 November 11th Google Option Prices [47] Table 13 Factors Impacting Option Prices [51] Table 14 Analogies between Real and Financial Options for Option to Defer [54] Table 15 Present Values of Cash Flows for Movie Delivery Example Table 16 Cash Flows Years 2 through Table 17 Classic Prisoner's Dilemma Table 18 Analogies between Prisoners and Firms in Classic Prisoners Dilemma Game 103 Table 19 Prisoner s Dilemma Game between Firms Table 20 Analogies between Prisoners and Firms in Classic Grab the Dollar Game Table 21 Grab the Dollar Example Table 22 Generic Process Goals Table 23 Strengths and Limitations of Financial Valuation Techniques x

11 Table 24 Causal Relationships Supporting Strategic Objective of Increased Sales Table 25 Additional Measure Supporting Strategic Objective of Increased Sales Table 26 Supplier-Customer Type Summary Table 27 Assumptions, Measures and Uncertainties of Shrink Wrap Projects (Supplier's Perspective) Table 28 Assumptions, Measures and Uncertainties of Shrink Wrap Projects (Customer's Perspective) Table 29 Assumptions, Measures and Uncertainties of Bespoke Projects (Supplier's Perspective) Table 30 Assumptions, Measures and Uncertainties of Bespoke Projects (Customer's Perspective) Table 31 Assumptions, Measures and Uncertainties of Internal Projects Table 32 Usefulness of Process Measures by Project Type Table 33 Relevant Financial Measures by Project Type Table 34 Value in Different Firm Types Table 35 Project Type Emphasized by Firm Type Table 36 Example of Use of Framework xi

12 List of Figures Figure 1 Relationship between Project and Product Life Cycles (based on [5]) Figure 2 Illustration of PV, BAC, AC and EV Figure 3 Tracking Project Performance using Earned Value Techniques Figure 4 Earned Value Measures as Feedback (based on [9]) Figure 5 Modeling Elements for Benefit Realizations Approach (from [10]) Figure 6 Example of Benefit Realizations Approach Figure 7 MBASE Model Integration Framework [14] Figure 8 Plot of NPV vs. Discount Rate Figure 9 Decision Tree for Option to Expand Figure 10 Decision Tree Example Figure 11 Profit from Nov Call Option with 320 Strike Price Figure 12 Profit from Nov Call Option with 320 Strike Price Figure 13 Profit from Nov Put Option with 320 Strike Price Figure 14 Upper and Lower Bounds to Value of Call Option Figure 15 Stock Prices of Hypothetical Security Figure 16 Option Prices on Hypothetical Security Figure 17 Price of Equivalent Portfolio Figure 18 NPV Analysis for Option to Defer Example Figure 19 Option Analysis for Option to Defer Example Figure 20 Option Value Calculation - Option to Expand Example Figure 21 Cash Flows for Internet Based Movie Delivery Example Figure 22 Possible Changes in Demand (Movie Delivery Example) Figure 23 Working Backwards in Movie Example Figure 24 Impact of Nature of Project on Selection of Financial Measures xii

13 Figure 25 Organizational Balanced Scorecard Example Figure 26 Balanced Scorecard Cascade [75] Figure 27 Project Evaluation Framework Figure 28 Supplier Types Figure 29 Customer Types Figure 30 Shrink Wrap Projects Financial Value Calculation (Supplier's Perspective). 155 Figure 31 Shrink Wrap Projects Financial Value Calculation (Customer's Perspective) 157 Figure 32 Bespoke Projects Financial Value Calculation (Supplier's Perspective) Figure 33 Bespoke Projects Financial Value Calculation (Customer's Perspective) Figure 34 Internal Projects Financial Value Calculation Figure 35 Project Evaluation against Firm's Objectives Figure 36 Project Evaluation against IT Goals and Architecture Figure 37 Project Evaluation against Project Success Factors Figure 38 Returns from the Four Project Categories (based on [84]) Figure 39 Project Classifications (from [85]) Figure 40 Proposed Project Classification Scheme Figure 41 Investment Boundary: ROI vs. Chance of Loss Figure 42 Investment Boundary: NPV vs. Chance of Loss Figure 43 Project Evaluation with respect to Organization and IT Goals Figure 44 Project Evaluation with respect to Organization Goals and Project Success Factors Figure 45 Project Evaluation with respect to IT Goals and Project Success Factors xiii

14 List of Equations Equation 1 Future Value Of $100, One Period At 5% Equation 2 Future Value After One Period Equation 3 Present Value After One Period Equation 4 Present Value of $ Equation 5 Future Value After N Periods Equation 6 Present Value Of An Amount To Be Received in N Periods Equation 7 NPV of Word Processor Project Example Assuming 5% Discount Rate Equation 8 NPV of Word Processor Project Example Assuming 12% Discount Rate Equation 9 Rate of Return Equation 10 Single Period NPV Set to Zero Equation 11 Discount Rate Equation 12 Calculation of NPV for Example from Section Equation 13 Variance of Portfolio of Two Assets [39] Equation 14 Capital Asset Pricing Model (Risk Premium) Equation 15 Calculation of Beta Equation 16 NPV Calculation at Start of Project for Full System Equation 17 NPV Calculation at Year 1 Assuming System Upgrade Equation 18 NPV Calculation at Year 1 Assuming No Upgrade Equation 19 NPV Calculation at Start of Project for Partial System Equation 20 NPV Calculation at Start of Project for Partial System with No Option to Expand Equation 21 Relationship of Call Price to Hypothetical Portfolio at Start of Period Equation 22 Relationship between Call Price and Hypothetical Portfolio with Increase in Stock Price Equation 23 Relationship between Call Price and Hypothetical Portfolio with Decrease in Stock Price xiv

15 Equation 24 Number of Shares Equation 25 Size of Loan in Portfolio Equation 26 Value of Call Equation 27 Risk Neutral Probability Equation 28 Black-Scholes Formula Equation 29 NPV Analysis using Risk Free Discount Rate - Option to Defer Example. 85 Equation 30 NPV Analysis using Risk Adjusted Discount Rate - Option to Defer Example Equation 31 Static NPV of Operating System Example Equation 32 Option Value - Option to Defer Example Equation 33 Project Value at Year 1 - Option to Expand Example Equation 34 Project Value at Year 1 with High Demand - Option to Expand Example.. 88 Equation 35 Project Value at Year 1 with Low Demand - Option to Expand Example Equation 36 Project Value at Start of Project - Option to Expand Example Equation 37 Option Value Calculation - Option to Expand Example Equation 38 Risk Free Probability (Movie Delivery Example) Equation 39 NPV Calculation for Process Measurement Example xv

16 1 Chapter 1 Introduction 1.1 Overview Over the last few decades, the cost of software to firms has grown significantly both in absolute terms and as a percentage of the budgets of firms. Given this increase in spending, one would expect to see a similar corresponding increase in value delivered to the firm and to society. This linkage has been difficult to demonstrate, leading to what has been described as the IT value paradox. Despite becoming ubiquitous within firms and society in general, software s impact and that of software projects has been difficult to elusive to quantify. Part of the difficulty in establishing value is that it is dependent on perspective. Value at the level of society, value at an organization level and value at an individual project level need to be evaluated differently. Value also depends on the recipient. That received by society in general differs from that received by consumers and from that received by the firm. This thesis specifically examines the evaluation of value of software projects from the perspective of the firm. The need to deliver value to the users of our products increases as the role of software in the success of enterprises and in society in general continues to grow. The value of software projects can be evaluated in multiple dimensions including the degree of satisfaction of stakeholder value propositions, financial terms and in terms of support for larger organizational goals or strategies. Value considerations can be used to focus

17 resources and to evaluate the usefulness of software processes toward the goal of delivering user needs. 2 Current project tracking and control methods, earned value techniques, as prescribed by professional organizations describe project tracking and control as being done against the plan of execution of the project. Completion of a project plan does not necessarily correlate with the delivery of value. Explicit consideration of value is required. Project tracking and control against a value baseline will lead to the better achievement of stakeholder goals, the organizations strategies and to financial benefits. The components required to establish such a value baseline are examined within this work. There are several techniques used to quantify the financial benefits or returns expected from a software project. The Net Present Value (NPV) of a project is calculated by discounting future revenues and expenses by appropriate rates to calculate the total present value of the project. The internal rate of return and the payback period provide alternate views into the same numbers supporting the NPV calculation. Real options and the use of decision trees are used to quantify the value of flexibility within projects. Results from game theory can quantify the effects of market conditions, competition and market timing. The inputs into these financial techniques vary from sales and market forecasts for products sold in the marketplace to the quantification of business process changes for software products used internally by the firm. The applicability of these techniques and their use are examined. Many techniques for eliciting, reconciling and measuring satisfaction of stakeholder value propositions have been developed and are prerequisites for determining and

18 obtaining value. Identifying all key stakeholders and understanding the role of the intended software within larger systems which include other software applications and 3 human actors are significant to identifying and reconciling value propositions. The applicability and the use of techniques such as the Benefits Realization Approach, Model Based (System) Architecting and Software Engineering (MBASE) and goal oriented requirements engineering are examined within this thesis. Projects exist within a larger framework of portfolios and also to varying degrees support or conflict with overall corporate strategies and with IT strategies. The degree to which an individual project complements other projects within a portfolio or supports corporate or strategy is another important measure of its value. The satisfaction of stakeholder value propositions refers to the degree that a project fulfils its own set of requirements. A project has additional value when viewed from a wider perspective. The alignment of projects within portfolios and with overall corporate and IT goals and strategies can be an important criterion in project selection and delivery of value. Balanced scorecard techniques are examined as a means of achieving this alignment. Other factors play a role in successful delivery of value from a project and must be identified to develop more comprehensive project evaluation techniques. For instance, the level of innovation in a project and its level of complexity have impact on its chance for success and influence the project s chance of delivering value. Factors such as the skills of the project team and the organizational environment are also crucial. The projects evaluation against these factors can be related to its chances for successful completion.

19 4 Ultimately, multiple value based techniques, such as those measuring the financial returns from a project and those measuring alignment with organizational goals need to be combined in order to establish comprehensive measures for a project. This thesis will examine ways to combine these techniques in a useful way for practitioners. A systematic framework for the evaluation of projects is presented. 1.2 IT Value Paradox Robert Solow, a Nobel price winning economist is frequently quoted as saying You can see the computer age everywhere but in the productivity statistics. [1] In IT Doesn t Matter [2], Carr provides a comparison that shows that the growth in spending on IT has paralleled growth in spending of railroads and electricity. He argues that each follows the same development pattern. Early adopters gain significant strategic advantages. As usage becomes more widespread, each no longer offers advantage, only parity. He argues that just as electricity and railroads became commodities, so too has IT. If IT is a commodity, then firms should seek to minimize spending, seek off the shelf solutions rather than firm specific distinct IT solutions and seek to ensure only that they have sufficient IT resources to have parity with competitors. If IT can offer strategic advantages to the firm, then increased spending on IT and development of firm specific applications and IT solutions is valuable. It would offer competitive advantages. Carr s postulation and other similar ones cause considerable debate. By extension, if IT s contribution to value is limited, then what about the contributions of individual academics and practitioners? [3]

20 5 The responses to arguments about IT s lack of value, which predate Carr, can be divided into two groups. One attempts to understand sources of IT value and to improve value delivered through the use of requirements techniques. Any lacking in delivered value is seen as a failure to understand business needs and in the business changes necessary to effectively utilize IT solutions. These are examined in section 3.2, Stakeholder Value Proposition Elicitation, Analysis and Reconciliation. The second group attempts to understand IT value generated, both quantitatively and qualitatively. The value of IT can be studied at three levels. At a national or society level. What has IT brought to the population? At a firm level. What role does IT bring in allowing the firm to achieve greater wealth generation? Does IT bring competitive advantage to the firm? How can this be maximized? At a project level. Simply, what is the value of individual projects? How should projects be selected, prioritized and monitored? This thesis primarily studies the question at the project level. It examines techniques to determine the value of individual projects and of their selection. As part of understanding value, the scope and requirements of the project must also be well understood. 1.3 Basic Question Addressed in This Work The basic question addressed in this thesis is the following. How can the value of a software project be understood and assessed? Consider the following two projects: Project A was estimated to cost 200,000 and last for 6 months. It was completed for 180,000 in 5 months. Project B was estimated to cost 300,000 and last for 9 months. It was completed for 800,000 in 18 months.

21 6 Which project had more value? The correct answer is that you can t tell from the information provided, yet it is not uncommon for practitioners and organizations to make assessments using the very type of incomplete information presented above. Only project cost and possibly the successfulness of the job done by the project manager are described. The business value of the project is not. It s quite possible that project B delivered more value to the organization. This thesis is directed toward developing a systematic framework to answer questions of this nature, that is, to understand project value, both quantitatively and qualitatively. 1.4 Research Process A survey and review of available literature from multiple fields including computer science and software engineering, general management, finance and project management was performed. Relevant approaches and concepts from these sources were combined and synthesized into a framework with the intended goals of producing a summary and guide useful to practitioners desiring to understand the sources and assessment of project value and of providing a step by step process that could be used for assessment of project value. Empirical validation of the proposed framework was outside the scope of this thesis given time and resource constraints, but would be a direction for future work. 1.5 Roadmap This work is divided into the following sections:

22 7 Current State of Practice in Project Valuation: A discussion of what is commonly meant by project success and what should be meant is given. The benefits and lackings of earned value techniques, commonly used to track and measure project progress, are described. Prerequisites for Project Valuation: Certain core competencies are required before systematic valuation of projects is possible. An overview of several requirements techniques, including the Benefits Realization Approach and goal based requirements engineering are presented. Good requirements techniques allow the costs and benefits of projects to be better understood and measured. Critical success factors, factors associated with a better chance of a project successfully completing are also presented. Quantitative Approaches to the Measurement of Value: Financial measures of value, calculated from estimated costs and revenues, are presented. Static techniques, such as net present value, internal rate of return and payback period, assume the course of the project will not change. Real options is presented as a technique to allow the benefits of managerial flexibility and choices to be quantified. Game theory is presented as a way to model and quantify competition. Process measures are presented as a means of quantifying the benefits of internal projects, that is, those that address internal business needs and do not produce a product for sale. Qualitative Approaches to the Measurement of Value: Project value is multidimensional. Quantitative (financial) techniques do not fully capture project value. Alignment with the strategic goals of the organization and with IT goals and architecture is considered.

23 A Proposed Multi-Dimensional Framework for Project Valuation: A proposed 8 process for evaluating project value is presented. Both quantitative and qualitative techniques are combined to allow better assessment of value. Application of Framework: An example of the use of the framework is presented. Due to time and resource constraints, the example is fictional, but is designed to emphasize various aspects of the proposed process. Conclusions and Future Work: Concluding remarks and possible future research directions are presented.

24 9 Chapter 2 Current State of Practice in Project Valuation 2.1 Overview A clear distinction must be made to distinguish between the project being conducted and the product being designed and constructed. Many project management techniques and measures of success examine only the former while the later is the only source of value. Current practice utilizes techniques such as the earned value technique, which while useful as a means of controlling and measuring progress, provide no information on the value generated by a software project. There is no value in the earned value technique; it is actually a cost tracking technique. 2.2 Definition of Project Success An understanding of the meaning of project success is essential in developing frameworks that can be used to value projects and to track success in the achievement of that value. The definition of success is a key element in understanding what elements need to be measured and tracked to evaluate project value. Success can be measured along several dimensions and evaluation of the project in each of these dimensions can be crucial for successful project delivery and to evaluate project value. The distinction between the project and product and between the project life cycle and the product life cycle is important. A project is a temporary endeavor undertaken to create a unique product, service or result [4]. The product is the result of the project and has a

25 lifespan well past the end of the project. The relationship between the project and product cycles is illustrated in the figure below from [5]. 10 Product Life Cycle Business Plan Upgrades Operations Divestment Product IDEA Project Life Cycle Initial Intermediate Final Figure 1 Relationship between Project and Product Life Cycles (based on [5]) Of note, it is during the potentially long operations period, when the product is in active use, when much of the business value promised by the project is delivered. During the divestment or end of life phase some of the cost of the product is incurred or potentially through salvage value, some of the cost of the product is recovered. Also significant is that the operations phase of the products life is typically much longer than the formal software project. It is important to consider the difference between the project life cycle and the product life cycle. Traditional measures of project success, such as the earned value technique, discussed in section 2.3, have focused on time, cost and scope measures during the life of the project. This narrow focus on the project life cycle leads to only operational measures and misses the strategic value of the project. [6] It casts project success in terms of internal project measures rather than in terms of what the project delivers to the organization. It measures project delivery against the original plan, but fails to consider the value delivered to stakeholders. The project life cycle is typically considered to end

26 11 with the start of the operational life of the product, that is, when the product is delivered or implemented. By taking a limited view, looking only at the project life cycle rather than the whole product life, much of the value of the project is not accounted for. Judgev [6] suggests that a more holistic understanding of project success can be achieved by measuring success during operations and decommissioning when effectiveness measures are taken into account and involve input from different stakeholders. By considering the whole product life, rather than just the project, we can measure both the project s value to the organization and obtain feedback from stakeholders. Measuring the value during the product s operational life is also critical feedback that allows assessment of valuation techniques done earlier in the project. Another consideration in measuring project success is the difference between project efficiency and effectiveness. Efficiency looks at time, scope and cost. Effectiveness focuses on satisfying stakeholder requirements and goals. It is a wider view of project success. Efficiency is operational in focus measuring the success of the project against its plan. Effectiveness is more strategic measuring the value the project produced. An alternate description of this is the difference between project management success and project success. Cooke-Davies [7] makes the following distinction. Project management success, being measured against the traditional gauges of performance (i.e., time, cost and quality), and Project success, being measured against the overall objectives of the project. Many traditional measures of project success are actually measures of project management success rather than project success. There are many examples of successive projects that failed from an evaluation with respect to time and cost, and more

27 12 significantly, projects that succeeded on cost and time measures but failed overall. In the latter case, traditional project measures such as the earned value technique may declare the project a success and the project manager successful despite a lack of satisfaction of stakeholder goals. Jugdev describes this phenomena succinctly as an example of "the operation was a success, but the patient died [6]. Project management success helps to complete the project and deliver a product. Project success is the measure of the business or strategic value delivered. Jugdev [6] traces the evolution of measures of project success. Initially ( ), success was defined mainly in terms of cost, time and scope measures. As noted earlier, these measures fail to consider stakeholder satisfaction or overall product success and as such fail to be good measures of project success and do not in themselves lead to effective means of measurement of value delivered. Value must consider the financial worth of the product and include an assessment of the project in terms of the stakeholder needs or satisfaction or in terms of the wider organization. 2.3 Earned Value Techniques Introduction The earned value technique allows tracking and control based on time and scope estimates and measurements. It allows for calculation of schedule and cost variances and provides a means to calculate estimated cost at completion and estimated time to completion as a project progresses. As shown later in this section, earned value, EV, techniques can serve a role in early detection of time and schedule variances and in

28 13 understanding the effectiveness of corrective actions. The earned value technique is in common use in practice and is frequently a main measure of project success even though it only it has no measures of value, only costs. EV techniques are based on four measures or parameters [8]: Table 1 Measures Used in Earned Value Techniques Parameter Definition Example Planned value (PV) or Budgeted Cost of Work Scheduled (BCWS) Budget at Completion (BAC): This is the budget allocated for performing a task, work package or project itself. It is a time phased, meaning it is dispersed or spent as the task or project proceeds. This is the total budget allocated to a task, work package or project. Assuming linear progress, a task estimated to take two months and cost 10000, would have a planned value of 5000 at the end of month one. A task estimated to cost has a budget at completion of Actual Cost (AC) or Actual Cost of Work Performed (ACWP) Earned Value (EV) or Budgeted Cost of Work Performed (BCWP) This is the actual cumulative cost at an interim point in time spent on a task, work package or the project itself. This is the cumulative (earned) value of work completed on a task, work package or the project itself at an interim point in time. Suppose that at the end of month one, 6000 has been spent working on a task. Its actual cost is 6000 regardless of how much of the task is completed or what was estimated to be done. Assume a task is estimated to cost If it is 45% complete, its earned value is PV, BAC, AC and EV as of the end of the first month for the example presented in the above table are illustrated below in Figure 2.

29 BAC 5000 Cummulative Value AC at Month 1 PV at Month 1 EV at Month 1 Time (Months) 1 2 Figure 2 Illustration of PV, BAC, AC and EV Calculation of Earned Value (Example) Earned value is best understood with an example. Suppose a project consists of two sequential tasks. Assume that the estimates have been reviewed and accepted and the budget is approved. The budgets at completion of the tasks are and 30000, respectively. Task A: Estimated cost 20000, estimated duration 2 months Task B: Estimated cost 30000, estimated duration 3 months Total Project: Estimated cost 50000, estimated duration 5 months Suppose after one month, dollars have been spent on task A and it is 45% completed. The planned value, PV, of task A and the project at one month is This assumes the progress expected and spending are linear. The task was expected to take two months, so at the end of the first month, it was planned to have it half done. The actual cost, AC, of task A and the project at one month is

30 15 The earned value, EV, of task A and the project at one month is: EV = percent complete * budgeted cost = 0.45 * = From these measures, it is possible to calculate the cost performance and schedule performance of the project at one month and to make predictions about the cost and duration for project completion. Table 2 Cost and Schedule Variance (Based on [8]) Term Calculation Meaning Cost Variance, CV CV = EV AC Absolute variance in cost. EV worth of value was generated and it cost AC Cost Performance Index, CPI CPI = EV/AC Ratio of value generated (EV) to actual cost (AC) Schedule Variance, SV SV = EV PV Variance in value generation against plan. EV worth of value was generated, but we had planned (scheduled) to accomplish PV worth of value Schedule Index, SPI Performance SPI = EV/PV Ratio of value generated (EV) to planned (scheduled) value (PV) Critical Ratio (CR) CR = CPI * SPI A measure of project health [8]. Further described in Table 3 Summary of Cost and Schedule Performance Indexes. Continuing with the example: Cost variance (CV) = EV AC = = The interpretation of this is that dollars has been spent to create 9000 worth of value. Money is being spent than expected for the value produced.

31 Cost Performance Index (CPI) = EV/AC= 9000/12000 = If money was spent exactly as planned CPI would equal 1.0. A CPI of less than one indicates that less value per dollar is being produced than that planned. Schedule Variance (SV) = EV PV = = The interpretation of this is that dollars worth of value were planned to be created during the first month, but only 9000 worth of value were actually created. Progress is slower than planned. Schedule Performance Index (SPI) = EV/PV = 9000/10000 = 0.9. If the project was exactly on schedule, SPI would equal 1. A SPI of less than one indicates that the project is behind schedule. Critical Ratio (CR) = CPI *SPI = 0.75 * 0.9 = The critical ratio is a measure of project health [8]. A critical ratio greater than one is desirable. Less that one indicates that the project is either behind on cost or schedule or on both. It can be seen that CPI and SPI individually are insufficient measures. Suppose it is costing more than estimated to create value (AC > EV or CPI < 0) and the project is ahead of schedule (EV >PV or SPI > 0). The project may cost more but may be completed sooner. Or suppose that it is costing less that estimated to create value (EV > AC or CPI > 0) and the project is behind schedule (EV < PV or SPI < 0). The project may cost less but may be completed later. Whether either of these two scenarios should be a cause of concern is very dependent on project particulars, but CR is a measure of the severity of the potential problem. 16 Table 3 Summary of Cost and Schedule Performance Indexes (Based on [8]) CPI SPI CR Cost Schedule Interpretation > 1, EV > > 1, EV > >1 Ahead Ahead Positive AC PV > 1, EV > < 1, EV < Depends Ahead Behind Mixed AC PV < 1, EV < > 1, EV > Depends Behind Ahead Mixed AC PV < 1, EV < AC < 1, EV < PV < 1 Behind Behind Negative

32 17 The example project is behind on both schedule and cost, corrective action may be indicated and the cause of this deviation must at least be understood. Was the initial estimate incorrect? Were the resources less skilled or less motivated than expected? Was there a steeper than expected learning curve? Certainly, the corrective actions taken depend on the cause, but equally significantly, the predicted cost at completion and predicted project duration that can be made at this point as well based on the cause of the deviation Predicting Cost at Completion Earned value techniques can be used to estimate the cost of a task or project at completion. Two parameters of interest are Estimate at Completion (EAC): Estimated cost of the project at completion Estimate to Completion (ETC): Estimated cost for the remainder of the task or project The estimate to completion and estimate at completion at dependent on whether there is any variance in cost and the possible cause of the variance as summarized below. Table 4 Cost Estimates at Completion (based on [8]) Case ETC EAC Comments No cost variance BAC AC = BAC- EV BAC Original cost estimates correct, project on budget. The earned value (EV) is exactly equal to the actual cost (AC). For example, $1000 was spent to create $1000 worth of value. Original estimate incorrect Must create estimate for remaining work AC + ETC New estimate needed for remaining work. Potential causes for error in estimate are ill defined scope, incorrect understanding of task or project

33 18 complexity or of skills of resources Over cost, but original estimate valid BAC EV AC + BAC EV = BAC +AC EV = BAC + CV One explanation is that the learning curve was greater than expected. Once trained, resources can be expected to perform as by the original cost estimate. EAC is the cost so far (AC) plus the original estimate for the remaining work (BAC EV). Past performance is a good indicator of future work (BAC EV)/CPI AC + (BAC EV)/CPI = BAC/CPI The original estimate for the remaining work (BAC EV) is scaled by the performance to date (1/CPI) and added to the cost so far (AC). Cost variance but no correction BAC AC = BAC- EV BAC In this case, there is cost variance, but it is assumed that the variance will somehow be made up. This is usually not very realistic and not a good approach. The value of the above table is that it provides a way to estimate the cost to complete a project or task and the total cost at completion given its current state. It also provides guidance on when a new estimation for the project is required Predicting Task or Project Duration Analogous to ETC and EAC, it is possible to predict the time estimate at completion (TEAC) and time estimate to completion (TETC) using the following parameters: Schedule at Completion (SAC): This is original estimated duration for a task or project. Actual Time (AT): The actual duration of a task or project to date. Table 5 Time Estimates at Completion (based on [8])

34 Case TETC TEAC Comments No schedule SAC AT SAC Original time estimates correct, variance project on schedule Original time Must create AT + TETC New time estimate needed for estimate incorrect new time remaining work. Potential causes Behind schedule, but original estimate valid Past performance is a good indicator of future work Cost variance but no correction estimate for remaining work Original time estimate for remaining work. (SAC AT)/SPI SAC - TV SAC/SPI for error in estimate are ill defined scope, incorrect understanding of task or project complexity or of skills of resources One explanation is that the learning curve was greater than expected. Once training, resources can be expected to perform as by the original cost estimate. The original estimated duration for the remaining work (SAC AT) is scaled by the performance to date (1/SPI) and added to the time spent so far (AT). SAC AT SAC In this case, there is time variance, but it is assumed that the variance will somehow be made up. This is not very realistic. The value of the above table is that it provides a way to estimate the time required to complete a project and the total time the project will take Use of Earned Value Techniques in Project Control Cost and time variances can be monitored over time as a project progresses as a means to track progress and as a means to evaluate the effectiveness of project controls. Below is an example of how CPI, SPI and CR are plotted and monitored as a project progresses.

35 20 Project Performance R a t i o CPI SPI CR Time Figure 3 Tracking Project Performance using Earned Value Techniques The project is performing according to plan or better with respect to cost when CPI >= 1. The project is performing according to plan or better with respect to schedule when SPI >= 1. When either measure is less than one, the project may be in need of corrective measures. Earned value is used as a form of feedback to control the project against its original plan. The process is illustrated below. Develop/Update Plans Perform to Plan Measure actual cost and completion status Is CPI > 1 && SPI > 1 Yes No Determine Corrective Action

36 21 Figure 4 Earned Value Measures as Feedback (based on [9]) Discussion Earned value techniques perform a useful role in tracking and controlling cost and schedule in software projects. They can be effective in controlling a project against an initial plan. The technique itself is not lacking, but the real problem is described in section 2.2. Earned value techniques measure project management success rather than project success. They measure conformity to a plan. There is no explicit consideration of whether the plan delivers value in financial terms or in terms of stakeholder value propositions. Interestingly, all of the value measures in earned value techniques are actually cost measures. For instance, planned value, PV, is actually the estimated cost to complete the project. Successful project control requires attention to progress against plans, possibly via earned value techniques, monitoring of the critical success factors described in section 3.3 and explicit consideration of the measures of value described in Chapter 4, Chapter 5 and Chapter 6 of this thesis.

37 22 Chapter 3 Prerequisites for Project Valuation 3.1 Overview All project valuation techniques have an implicit assumption that the scope and requirements of the project are sufficiently understood to allow estimation of costs and of benefits. Without this level of understanding of the requirements of the project, accurate and meaningful estimates are not possible and thus, accurate assessment of value is not possible. Most software projects consists of both the design and construction of the product and an associated set of changes within the business or within processes to successfully adopt the product and adapt to use it well. Good requirements techniques are needed to identify the changes needed to successfully use a new or modified product and to obtain value from that product. A high level review of several requirements techniques is presented. Achievement of value from a software project requires the successful completion of the project. Critical success factors are factors associated with higher chances of successful project completion. They can be evaluated to establish necessary prerequisite conditions before a project should be started and also can be used as a discriminator for project selection. Critical success factors for projects are described and a simple method for evaluation of projects against these factors is presented.

38 Stakeholder Value Proposition Elicitation, Analysis and Reconciliation Overview Good requirements techniques can be seen as a prerequisite for the valuation of projects. In all techniques to measure the value of projects, there is a critical implicit assumption that the scope of the project and the requirements for the project are known sufficiently well to support value estimations appropriate for the current stage in the project s life cycle. For instance, when projects are initially requested or proposed, sufficient knowledge of their scope is required to make high level cost and benefit estimates. As requirements are elicited, analyzed and validated, cost and benefit estimates should be refined to reflect the better understanding of the project. Good requirements techniques can be seen as necessary to obtain the understanding and details of the project required to support valuation techniques. IT expenditures represent a significant percentage of the expenditures of many organizations. A natural question is, what value is returned by these expenditures. Can this value be determined and produced by IT groups alone? Thorp [10] correctly states that IT efforts or projects are typically only a small portion of a larger business effort and it is necessary to consider the larger effort to both achieve and measure value to the business. In project management terms, value needs to be established from an overall program of business and IT projects. The IT project alone can neither deliver value nor be the measurement of value. Thorp [10] refers to this as silver bullet thinking. The IT project, by itself, does not deliver value and is not a silver bullet solution to the underlying business need.

39 Benefits Realization Approach Introduction The Benefits Realization Approach [10] is a framework that allows consideration of the overall business program, of which an IT effort or project is a part. It includes a simple modeling technique that supports reasoning about the associated efforts needed to achieve business value. There is an attempt to look at the entire set of conditions needed for success; not just the IT efforts alone. The entire product life is examined rather than just limited aspects of the software project. A concept to cash approach, rather than a design to development approach, is needed to achieve value Approach Key to an understanding of this approach is the notion that any IT solution, regardless of its own merits, will not achieve its full value or benefit without wider and coordinated changes in the business. Thorp [11] notes that even for IT efforts that would appear initially to be primarily IT, when the product is fully integrated into the business much of the changes and investments are actually on the business side. Organizations do not always analyze, understand or track these related business costs. Thorp labels his approach the Benefits Realization Approach. Three key premises underlie the approach [11]. Benefits do not just happen There is an adoption period for any new product and a learning curve as people learn how to best utilize its functionality. Related to this is the notion that successful realization of value (benefit) requires training and a migration plan from the current state to a new one utilizing the software developed.

40 25 Benefits rarely happen according to plan Benefits realization is a continuous process These last two points noted by Thorp, really emphasize points noted in other parts of this thesis. The achievement of value (or benefit) requires several steps. An understanding of the measures of value is needed. From the realms of finance and engineering economics, means of understanding the financial value of projects (or of wider programs) are needed. Means of assessing the project in relation to organizational and IT strategies and goals are also needed. A wide understanding of means to elicit and understand the benefits and values sought by stakeholders is needed. Modeling techniques such as the results chain and goal based methods can elicit the requirements that will yield the value sought by stakeholders. Getting this full set of requirements and goals and understanding both the business and IT components needed are keys to obtaining value. The results of an initial analysis, an estimation of the value of the effort, a business case, sets of goals, requirements and initiatives must be taken as what they are: rough initial estimates of what needs to be done and what can be achieved. Progress must be measured, financial calculations must be redone and achievements against models of stakeholder and organization value must be monitored as reality unfolds. Some of the initial estimates will be proven correct and some incorrect. Without measurement, the project or program is proceeding blindly. It s unlikely to achieve the desired results given that it is quite unlikely that initial estimates and plans are perfect. Evaluation of financial models, requirements and goals, and business cases needs to be done early and often Results Chain Modeling Results chain modeling is fully described in [12]. The interested reader is directed there. A very brief example is presented below as an illustration. The key point of this technique is to capture and understand all related business changes needed to accompany software changes to achieve value. Four main modeling elements are used [10]:

41 26 OUTCOME Outcome: The results sought, including either intermediate outcomes in the chain, those outcomes that necessary but not sufficient to achieve the end benefit, or ultimate outcomes, the end benefit to be harvested. Initiative: actions that contribute to one or more outcomes. INITIATIVE CONTRIBUTION Contributions: the roles played by elements of the Result s Chain, either initiatives or intermediate outcomes, in contributing to other initiatives or outcomes. ASSUMPTION Assumptions: hypothesis regarding conditions necessary to the realization of outcomes or initiatives but over which the organization has little or no control. Changes to assumptions require updates in the Result Chain Figure 5 Modeling Elements for Benefit Realizations Approach (from [10]) Results Chain Example The following example is an enhanced version of an example from Thorp [13]. The enhancements include a consideration of training, of motivating factors and of associated business process changes. A firm is experiencing a drop in sales. Feedback from customers includes complaints that order fulfillment is taking too long. The current order entry system is paper based, manually intensive and time consuming. An automated order entry system is proposed.

42 27 Initiative: Train staff to use new system. Assumption: The time to fulfillment of an order is an important buying criterion Allows staff to efficiently use new system Initiative: Implement an automated order entry system. Decreased time to process order Outcome: Reduced order entry time (Intermediate outcome) Reduced time to order fulfillment Outcome: Increased sales Reduces time for and resistance to adoption Reduced time to order fulfillment Initiative: Create financial incentives for sales staff to adopt new system (commisions). Initiative: Improve distribution system to reduce delivery time by storing products at multiple locations near customers. Figure 6 Example of Benefit Realizations Approach There are several key observations from this model. First, only one of the four initiatives shown involves software development. An initiative can be considered the equivalent of a project in standard project management terms. Achievement of the desired outcome of increased sales requires a series of related projects that involve both training and changes in business process. In project management terms, this collection of projects would be considered a program. A key assumption is that the time to order fulfillment is an important criterion for buyers when they are choosing whether to make a purchase. If this is false, for instance, if potential customers are interested only in price, then the benefits (value) desired from the program will not be achieved. Tracking, measurement

43 28 against both financial estimates and satisfaction of goals/requirements, and control, making modifications in the overall plan based on these measurements, also play a key role in achievement of value Model Based (System) Architecting and Software Engineering (MBASE) Introduction MBASE [14] [15], Model Based (System) Architecting and Software Engineering, is another technique that attempts to identify all conditions that are needed to achieve value. A narrow focus on IT is again seen as too limited to achieve success. There is an attempt to look along four dimensions to maximize value. An iterative process is used to ensure that models representing each dimension are mutually consistent. The dimensions are as follows [14]: Product: The system being developed. Models in this dimension represent requirements, code and architecture. Process: The processes used to develop the system. Examples of process models include waterfall development models, spiral models, iterative approaches. Properties: These are models of the properties of the product or process. These include project management models, such as cost estimates and schedules, and models of the product that model performances or reliability. Success: What each class of stakeholders needs to be satisfied. Success models include the financial models presented in Chapter 4 and stakeholder satisfaction models such as Win-Win or IKIWISI (I ll know it when I see it). This can be visually represented as follows, from [14]:

44 29 Success Models Win-Win; IKIWISI; Business-Case; Mission Models Process Models Life-Cycle Waterfall Evolutionary Incremental Win-Win Spiral Anchor Points Risk Management Activities CMM KPA s Entry/Exit Criteria Product Development and Evolution Process Milestone Content; Planning and Contol Validation and Verification Criteria Product Models Domain Artifacts Requirements Architecture Code Documentation Packaging Embedded Shrink Wrapped Turn Key Product Line Evaluation and Analysis Property Models Cost/Schedule; Performance; Assurance;Usability Figure 7 MBASE Model Integration Framework [14] As can be seen in the above figure, models are formed in each dimension. These models have interactions and there is a need for mutual consistency to achieve value. An iterative spiral approach is used to achieve consistency between these models Win-Win Model / Theory W Introduction At the core of techniques to elicit and deliver stakeholder value are models to understand stakeholder value and to reconcile the values of varied stakeholders. Theory W is a theory that states that project success can be obtained by satisfying the value propositions of all critical stakeholders. Any IT effort will have multiple stakeholders including end

45 30 users, customers, line of business management, IT management, project manager, analysts, developers, maintainers of the future system among others. Each stakeholder group will have their own goals which may conflict with other groups. Resolving these conflicts can be a key to delivering value Theory W Theory W is simply, make everyone a winner [16]. Or more formally from [17] Making winners of the system s key stakeholders is a necessary and sufficient condition for project success Is Win-Win possible? Many situations appear at a first pass to be zero-sum; that is, they appear to be a win-lose situation where one parties will gain at the expense of another. A critical question is whether these situations can be converted to win-win through negotiation and expectation management. Theory W holds that unless everyone wins, success for a project is less likely. The key to creating Win-Win situations is negotiation. In the book, Getting to Yes [18], five principles are established toward creating win-win situations. The reader is referred to that text for more details. Don t bargain over positions A position is where someone stands on an argument. Arguing or bargaining over positions can only result in one party losing. Separate people from the problem

46 Negotiators are people. Their emotions and relationships can impact their positions and negotiations over those positions. It is important to separate those factors from the substantive problem at hand. Focus on interests, not positions It is critical to focus on the interests and needs of each stakeholder and not just their current position. Invent options for mutual gain Expanding or inventing options can turn a win-lose situation into a win-win. Insist on using objective criteria The techniques described in Getting to Yes and from Theory W can enhance the identification and creation of Win-Win conditions. Under certain conditions win-win is possible. The examination of the conditions required is beyond the scope of this work, but reconciling stake holder value propositions is a significant step in achieving value from a project Goal Based Techniques Introduction A key part of obtaining value from a software endeavor is eliciting requirements. Fully understanding and developing requirements is crucial to determining stakeholder value propositions, that, simply, what they value. Goal modeling is a technique that can be used to establish requirements. The establishment and definition of goals is recognized as an important component in many aspects of requirements engineering. The creation of a hierarchy of related goals at varied levels of abstraction can lead to better identification, elicitation and elaboration of requirements. Analysis of goals by refinement, asking how, and by abstraction, asking why, can lead to a more complete set of requirements. Common GORE approaches include GBRAM [19] [20], i* [21] [22], the NFR framework [23] and KAOS [24] [25]. Detailed study of these approaches is outside

47 the scope of this thesis, but the interested reader is directed to the references noted. General GORE concepts are described below Goal-Oriented Requirements Engineering Concepts Goals are fundamental to the requirements process. Yu noted [22]: Perhaps the elucidation and manipulation of goals is a natural and inherent part of doing RE, even though earlier RE methods have not made this explicit, and have not provided the associated support. This interpretation is plausible since requirements by its very nature represents a target to be reached, a wish to be fulfilled, a vision to be materialized. Goal-oriented requirements engineering (GORE) is concerned with the use of goals for eliciting, elaborating, structuring, specifying, analyzing, negotiating, documenting, and modifying requirements [24]. Traditional requirements practices focus on what the system is intended to do, that is, on its functionality. Users and other sources of requirements typically express their needs as list of features. In contrast, GORE techniques focus on why, leading to a more thorough understanding of the proposed system within its environmental context and to a more complete, consistent set of requirements, and on how, which allows generation and comparison of alternative implementations. A better understanding of the project can lead to better achievement of value. The relationship between goals and requirements is analogous to the relationship between design and code. Requirements implement the goals. Alternate sets of requirements can be evaluated to determine how well they satisfy an identified hierarchy of goals.

48 Gore techniques can play a role across many aspects of requirements engineering, but they are particularly relevant early in the process. Goals are fundamentally at a high level and fully understanding stakeholder intent and motivations first can lead to successful requirements development. Two fundamental approaches to GORE are: Begin with an initial set of user goals at a high level and derive sub goals. Successive and iterative refinement of sub goals leads to requirements. Begin with a system description, scenarios or functional specification. From these, determine an initial set of goals. Successive and iterative refinement of these goals leads to a more complete set of requirements. 33 The concept of a goal is fundamental. A goal is an objective or intended purpose for a system. Goals exist at varied levels of abstraction. At the highest level they may express the overall strategy of the organization, for instance, "offer accounting services to clients". At the lowest level they may be satisfied by the actions of a single agent and map directly into a requirement or assumption. Goals can be concerned with either functional or non-functional aspects of a system. Functional goals represent the individual operations or services that the system supports. Non-functional goals are system qualities. Goal oriented techniques provide a means for the qualitative and quantitative systematic evaluation of both functional and non-functional goals. Requirements can be linked back to non-functional goals and the satisfaction of these goals by the proposed set of requirements can be evaluated. Many non-functional goals are soft goals. A soft goal is one that can be satisfied to varied extent. For instance, usability is a soft goal. The final system usability will be supported to different extents by different sets of requirements, designs and implementations.

49 34 Goals are interrelated or linked. Goal hierarchies can be established linking each goal with its sub goals. Satisfaction of each goal can require that all sub goals are satisfied, called AND-refinement, or satisfaction of any sub goal can result in satisfaction of the parent goal, called OR-refinement. Soft goals linked to sub goals lead to the notion of a goal being satisficed by its sub goals. Sub goals either add or detract from the completion of a parent goal. Development of a goal hierarchy is done by iteratively asking why and how. Refinement of goals can be achieved by asking how to break each goal into sub goals. Abstraction of higher level goals can be achieved by asking why, that is, why is a lower level goal needed. Goal based approaches examine the composite system, that is, the software system within its larger environment. Explicit consideration of actors is also done. Within such frameworks why, who, and when questions can be addressed in addition to the usual what questions. It then becomes possible to reason formally about goal satisfaction [25]. Goal based approaches are seen as a means to determine the requirements necessary as a prerequisite to deliver value. 3.3 Critical Success Factors Critical success factors, CSFs, are sets of conditions associated with a higher probability of project success. For instance, the technical background of the project team is a CSF. A project with skilled, experienced, well trained team is more likely to be successful than one with a less experience team. There are many studies of critical success factors in the literature, this thesis presents a synthesis of three [26] [27] [28].

50 35 Belassi [26] suggests that critical success factors can be classified into four groups Factors related to the project Factors related to the project manager and to the project team Factors related to the organization Factors related to the external environment. The specific factors sited in [26] [27] [28], plus others hypothesized by this author, can be mapped into these categories. The set of factors chosen in this work is by no means optimal or empirically demonstrated, but can serve to show a proposed technique to evaluate specific projects with respect to critical success factors. The focus of this section is on how critical success factors can be evaluated to establish necessary prerequisite conditions before a project should be started and also to demonstrate how CSFs could be used as a discriminator for project selection. The proposed evaluation technique is independent of the exact set of CSFs. CFSs may vary based on project type, industry and possible other factors. Determining an optimal set of CSFs would require empirical studies beyond the scope of this work. A simple spreadsheet can be used to evaluate projects against CSFs as shown below. Table 6 Evaluation of Critical Success Factors for an Example Project Category CSF Low (L) Project Project Project Manager Project Manager Project Manager Technical Complexity New technolog y Medium (M) Hard, well know technology High (H) Easy, Well known technology Complex, Complexity of Requirements uncertain, subject to change Complex, but stable Simple, easy to understand M Technical Skills Weak Good Excellent M Communicati on Skills Weak Good Excellent M Management Skills Weak Good Excellent M Ranking of Example Project M

51 Project Team Techical Skills Weak Good Excellent L Project Team Organizatio n Organizatio n Organizatio n Organizatio n External Environme nt External Environme nt Experience With Similar Projects Top management support Maturity of Software Process Users actively involved in requirements Users actively involved in testing No experienc e Weak Ad hoc - no processes Weak Weak Some team members have relevant experience Some support Repeatable processes Limited user participatio n Limited user participatio n Most team members have relevant experience Clearly identified champion Optimized processes Extensive user participatio n Extensive user participatio n Understandin g of Market Poor Somewhat Excellent H Understandin g of Competition Poor Somewhat Excellent M SCORE 1.92 L M M M M 36 Here the score has been calculated as (3 * number of H rankings + 2 * number of M rankings + number of low rankings) / number of CSFs. It is not proposed that this particular ranking is optimal or suggested, but that organizations can identify factors that are correlated with their successful projects and that new projects can be ranked against these factors for the following purposes. As a stage gate to determine whether to consider the project at all. Some minimum score would be required to proceed. As a means to judge the relative possibility of success of different projects. This would serve as one of several project selection criterions.

52 Cost Estimation Quantitative valuation techniques are dependent on good project cost estimation. For purposes of this thesis, it is assumed that accurate cost estimates are available. The topic of cost estimation is outside the scope of this thesis, but it is a well researched topic and information is readily available within software engineering literature. 3.5 Sales and Marketing Forecasts Quantitative valuation techniques can be dependent on estimates of future revenue via sales and marketing forecasts. For purposes of this thesis, it is assumed that these forecasts are available and accurate. Since this topic is outside the scope of traditional software engineering and of this thesis, it will not be discussed. 3.6 Discussion Having good requirements is a key step in obtaining value. Without a clear definition of what needs to be done, both in software and in associated business and process changes, there is little hope of delivering value to stakeholders. Several techniques, the Benefits Realization Approach, MBASE and goal-based requirements engineering were surveyed at a high level as examples of techniques to obtain good requirements. Project critical success factors were seen as useful in both predicting chances of project success and as a discriminator for project selection.

53 38 Chapter 4 Quantitative Approaches to the Measurement of Value 4.1 Overview Quantitative approaches to the measurement of value from projects are presented. These measures attempt to assess the financial value of the project as measured by the difference between costs and revenues. The costs of a project are dependent on good cost estimation techniques. While not directly discussed within this thesis, cost estimation is crucial in estimating value and in project ranking and selection. The expected revenue from a project can be estimated by marketing and sales forecasts for projects producing products for sale in the marketplace or can be estimated as savings from business process improvements for internal projects. Financial measurement techniques can be divided by whether they take a static or dynamic view of the project. Net present value, internal rate of return and payback period approaches are seen to take a static view of the project. A financial value is calculated under the assumption that the project will proceed exactly as planned regardless of how reality unfolds. Real options approaches take a more dynamic view by attempting to value managerial flexibility. Game theory approaches also take a more dynamic view and allow modeling and quantification of the effects of competition and cooperation in the marketplace. Internal projects are defined for purposes of this work as those that do not produce a product for sale, but are instead producing a software product for internal use in the

54 39 organization to improve business processes. Techniques to quantify and assign monetary value to internal business process improvements are presented. 4.2 Net Present Value (NPV) / Discounted Cash Flow Present and Future Values An underlying principle in the financial measure of investments, including investments in software projects, is that the value of a given quantity of money today is worth more than the same amount at a date in the future. This first basic principal, the time value of money, can be stated succinctly as: A dollar today is worth more than a dollar tomorrow [29] It is intuitive that given a choice between receiving a dollar today and a dollar at a later time, even tomorrow, that today is preferable. There are two factors that explain this preference: 1. Money received today is immediately available for other investments. 2. Future events have uncertainties. Suppose that a choice exists between receiving $100 today and a greater amount one year from now. How much additional money would be required to make the later payment preferable? A simple way to determine this is to look at possible investments at a similar risk. Assume that in this example, the future payment is guaranteed; investments with zero risk should be considered. Suppose that a U.S. government bond offers a 5% interest rate. Presumably, even considering recent market turmoil and tremendous government deficits, U.S. government bonds have no risk of default. Suppose that $100 is invested today at a 5% interest rate.

55 * (1 + interest rate) = 100 * (1 + r) = 100 * ( ) = 105, where r is the rate of return. Equation 1 Future Value Of $100, One Period At 5% The above equation states that given a 5% interest rate, the future value of $100 today is $105. PV * (1 + r) = FV, where FV is the future value and PV is the present value. Equation 2 Future Value After One Period From another perspective, suppose that a payment is offered at a later date. What is the value of that payment today? Equation 2 can be manipulated to solve for the present value in terms of the future value. PV = = FV * ( ) Equation 3 Present Value After One Period The term, ( ), is known as the discount factor, with r being described as the discount rate. As a concrete example, suppose a payment of is offered in one year. What is the present value of this payment? Assume that alternative, equivalent risk investments are available at a 5% rate of return. PV = Equation 4 Present Value of $110

56 41 Assuming a 5% rate of return, or equivalently, a 5% discount rate, the present value of $110 one year from now, is $ This means that $ received today is of equal value to $110 received in one year. Equation 2 and Equation 3 can be used to calculate future value and present value over one time period, in the examples, over a period of one year. The future value over multiple periods can be determined as follows. Period 1: Period 2:.. Period N: Equation 5 Future Value After N Periods Solving for PV yields Equation 6 Present Value Of An Amount To Be Received in N Periods As can be seen from above, money has a time value. The value of a quantity of money spent or received today is different from the value of the same quantity of money at a future date. To evaluate any investment, all payments and outlays are converted into dollars valued at the same point in time, usually the present. This is referred to as calculating the net present value. Present value indicates that all money is converted into its worth today. Net indicates that all payments and outlays are summed. Efforts

57 with positive NPVs are worthy of consideration. This is best understood via a simple example. Suppose that a project to develop a new commercial software product, perhaps 42 a word processor, is being considered. Suppose that the costs include payment of $100,000 to a team of requirements engineers today and payment of $300,000 to a team of developers six months from now. Further suppose that the final product will be completed in one year and that it can be sold to another company or on the market for $ at that time. Should this project be conducted? The answer to this can be determined by calculating NPV 1. Assume US government bonds are available at an interest rate of 6% per year or 0.06/12 = 0.005% per month. Individual cash flows (both revenue and outlays) can be designated by C i. C 0 = (today, cost of requirement engineers) C 1 = (six months from now, cost of development team) C 2 = (one year from now, sale of product) r = 0.06/year = 0.005/month NPV = ( )/( ) /( ) 12 = = 4445 Equation 7 NPV of Word Processor Project Example Assuming 5% Discount Rate The general rule is a project is worth consideration when NPV is positive 2. The NPV of this project is positive. This indicates that given our assumptions, the organization will 1 The question is actually answered partially by the NPV calculation. As seen elsewhere in this thesis, value assessment is multidimensional. NPV calculations serve as a measure of worth in the financial dimension. 2 Value is multidimensional and NPV, or financial value, is only one dimension. Some classes of projects, mandatory, for instance, those forced by legal or regulatory requirements, may need to be done regardless

58 43 gain wealth as the result of this project. The next question is whether the project should proceed based on this calculation. There are several implicit assumptions in this NPV calculation. How certain are the expenses ($100000, $ (in six months)) and the future revenue ($ (in one year))? Assume the discount rate (0.06) used was the interest rate available from zero risk government bonds. Is this the correct discount rate to use in this calculation? Using a risk free discount rate is appropriate for calculating the NPV of risk free investments. Unless the project is risk free, which is highly unlikely for any project, the calculation is not valid due to use of an incorrect discount rate. This project generates a future value of $ in one year given investments of $ today and $ in six months. Again, assume that a 6% return is available from safe government bonds. All projects have risk. Any rational investor would require a return higher than $ to undertake this effort. The same return could be return risk free from government bonds. This principal can be expressed as: A safe dollar is worth more than a risky one [30] Discount Rates As can be seen in the proceeding section, NPV calculations are dependent on the choice of discount rate, which begs the question of how to choose the correct discount rate. Ideally, the discount rate should reflect the rate of return of similar investments. Suppose that further analysis shows that the risk involved in undertaking the word processor of NPV. Another example is an upgrade to an operation system or DBMS. These may need to be done to maintain support. A negative NPV calculation would not be an indication to remain on an unsupported operating system.

59 project in section is equivalent to the risk of investing in a particular stock and that the expected return of that stock is 12%. In this case, the opportunity cost of investing in the software project is that of not investing in the stock market. The opportunity cost of capital is said to be 12%. Recalculating the NPV of the word processor project yields: C0 = (today) C1 = (six months from now) C2 = (one year from now) r = 0.12/year = 0.01/month NPV = ( )/( ) /( ) 12 = = Equation 8 NPV of Word Processor Project Example Assuming 12% Discount Rate 44 It is seen that given the new assumption about the risk of the project being equivalent to an investment in a particular stock, the NVP is the project is negative. This indicates that money is lost by conducting the project, relative to other equivalent risk investments such as simply buying the particular stock as noted. Two immediate criticisms of NPV methods are the need to determine an appropriate discount rate and the need to have accurate estimates of costs and of revenues. By maintaining a historical database of estimates from previous projects and comparing project actuals against these estimates, the later concern, that of producing accurate estimates can be addressed. Even after an organization gains expertise on estimation, the problem of determining the correct discount rate remains. This can be handled by performing sensitivity analysis of NPV on a range of discount rates. To see how this can be done, consider this second example.

60 A new accounting system is proposed to replace a legacy system. Project costs are estimated at $ The system will have a life span of 5 years and will save $ per year in operating cost compared to the legacy system. For simplicity, assume that the development costs are spent completely at project initiation and that the savings are realized as a bulk amount at the start of each year of operation. Should this project commence based on its NPV? The critical question is what discount rate to use. To determine the correct discount rate it would be necessary to identify investments with similar risk and to quantify their return. Practically, it is difficult to impossible to do this. As an alternate approach, consider a sensitivity study to evaluate the range of discount rates for which the project generates wealth. A spreadsheet can be used to conduct this study. Table 7 Example of NPV Sensitivity Analysis Discount Rate Development Cost Year 1 Savings Year 2 Savings Year 3 Savings Year 4 Savings Year 5 Savings NPV

61 The results of this sensitivity analysis can be summarized in graph. NPV NPV Discount Rate Figure 8 Plot of NPV vs. Discount Rate

62 47 It can be seen that for discount rates below approximately 12.5, the project has a positive NPV and is worth consideration. That is, if the return on investments with equivalent risk is less than or equal to 12.5%, the project is a good investment. If the return on equivalent risk investments is greater than 12.5%, the project is a bad investment. Now suppose that a source of capital is available at 5% interest. For example, suppose a bank is willing to lend funds for this project at a 5% interest rate. Given that the project has a positive NPV at the discount rate of 5%, should it be done? Not necessarily. The discount rate that should be used is that of investments of equivalent risk. The rate of the loan is not the discount rate. The key decision is based on the rate of return available from alternative investments of equivalent risk. Let s assume that investments of equivalent risk are available that offer 20% return. At a discount rate of 20%, the NPV of the project is negative and the project should not be done. Another way of stating this is that we could take the 5% loan and invest the money in other ways that have a greater return for the same risk. Before evaluating other financial measures of projects, it is useful to summarize the characteristics of the NPV rule, which is to accept projects with a positive NPV. NPV is based on the fact that a dollar today is worth more than a dollar tomorrow. Any financial valuation technique that does not account for the time value of money is flawed. [31] NPV depends solely on forecasted cash flows and the opportunity cost of capital. Any financial valuation technique that depends on managerial tastes, the companies choice of accounting method, the profitability of the company s existing business or the profitability of other independent projects will lead to inferior decisions. [31]

63 NPV is additive. Combining a project with negative NPV with a project with positive NPV will result in a lower NPV for the combined project than that of the project with a positive NPV. [31] Other common measures of a project s financial worth include the return on the internal rate of return (IRR) and the payback period Payback Period The payback period is the number of periods until the estimated cash flows equal the initial investment. NPV calculations express present and future cash flows as equivalent current dollars. Payback period expresses this in terms of time. Intuitively, this can be stated as the investment will pay for itself in X number of years. [32] While useful as a secondary measure of project value, it has several defects that are apparent with a simple example. Table 8 Payback Period Example Project Initial Outlay Cash Year 1 Flow Cash Year 2 Flow Cash Year 3 Flow Payback Period (Years) NPV assuming 10% opportunity cost A B C As a measure of value, payback period is seen to be deficient. Project A clearly brings significantly more value to the organization than projects B or C, but has a longer payback period. Project selection techniques based solely on payback period will

64 49 overlook valuable projects with longer payback periods. For instance, a requirement that all projects payback their investments within two years would reject project A. Additionally, simple techniques based on payback period fail to acknowledge the time value of money. Projects B and C both have 2 year payback periods, but only project B should be considered on the basis of NPV. Myers [33] suggests that the use of payback period in valuing projects may stem from a distrust of forecasted future distant cash flows. If distant forecasts are not trustworthy then a quick payback is more valuable Internal Rate of Return (IRR) / Return on Investment (ROI) NPV expresses an investment in terms of equivalent dollars. Payback period evaluates an investment with respect to time. The internal rate of return, IRR, (or equivalently, the return on investment, ROI) evaluates an investment in terms of an interest rate. [34] The internal rate of return, alternately referred to as ROI, for a simple investment consisting of a single investment and a single payoff in one period can be expressed simply as: Equation 9 Rate of Return The internal rate of return is also the discount rate that makes NPV equal to zero. [35] This can be seen as follows. Here, C 0 is the initial investment and C 1 is the revenue (payoff) at the end of the period.

65 50 Equation 10 Single Period NPV Set to Zero Solving for the discount rate or rate of return Equation 11 Discount Rate Comparing Equation 9 and Equation 11, it is seen that the IRR (or equivalently ROI) is the discount rate at which NPV is zero. For a project containing multiple investments, multiple cash flows and multiple periods solving for the internal rate of return is less straight forward. Consider the second example presented in The NPV is given by: Equation 12 Calculation of NPV for Example from Section By setting this equal to zero, the IRR, being the rate at which NPV equals 0, can be found. Solution of this equation is non-trivial. The IRR is best obtained by trial and error. As can be seen in Table 7, the IRR is approximately 12.5%. Projects that have an IRR greater than the opportunity cost of capital (the return on investments of similar risk) have a positive NPV. Projects that have an IRR less than the opportunity cost of capital have a negative NPV. This can be seen in Figure 8. When the discount rate (opportunity cost of capital) is less than the IRR, NPV is seen to be positive.

66 51 This result can also be obtained by reviewing Equation 12. It is a strictly monotonically decreasing function of r. The discount rate, r, equals the internal rate of return, IRR, when NPV equals 0. Clearly, NPV will be positive when r is less than IRR and negative when r is greater than IRR. There are situations where IRR and NPV techniques give contradictory results. This is particularly true for the case of mutually exclusive projects. An example of mutually exclusive projects is when there are two possible approaches to a project with different costs and different payoffs. An example of this is presented in Myers [36]. Suppose two projects are proposed to build a particular software product. Perhaps they represent two different architectural solutions. Table 9 Comparison of NPV and IRR on Mutually Exclusive Projects (from [36]) Cash Flows Project Investment (C 0 ) Payoff (C 1 ) IRR (%) NPV at 10% A B Which approach is preferred from a financial standpoint? Project A has a higher IRR. Project B has a higher NPV. Assuming no shortage of available capital, that is, assuming that the investment for project B can be secured, performing project B rather than A will make the organization = 3636 dollars richer. Clearly approach B is

67 preferred. This suggests that using IRR as a means of evaluating the value of projects may result in less profit for the firm than the use of NPV techniques. 52 The following example from [36] again illustrates a difference in the projects selected by maximizing IRR and by maximizing NPV. Table 10 Comparison of IRR and NPV for Three Projects Cash Flows Project C 0 C 1 C 2 C 3 C 4 C 5 IRR (%) NPV at 10% F G H Myers reports that when shown this example, many managers prefer project F to project G despite the higher NPV associated with project G. He suggests the reason for this is an implicit assumption about a shortage of capital. If project F is chosen, there is a possibility of using its cash flow, C 1, to fund project H. Is this a reasonable approach? No, unless capital is limited. As shown above, the best way to maximize value for the firm is to maximize NPV. A better solution would be to view this as an optimization problem to be solved by linear programming techniques.

68 Another significant criticism of IRR techniques is that when used alone, they tend to 53 direct investments toward projects with lower strategic value. [37]. Lower level managers attempting to maximize IRR may suggest projects or modify project requirements to reduce initial investments and get quick paybacks (which will increase IRR = payoff/investment 1). These short lived projects may not be the type of investments that allow the firm to grow Comparison of NPV, IRR and Payback Period NPV, IRR and payback period offer three different perspectives into the financial value of projects. The following table summaries some significant points and conclusions discussed in the preceding sections. Table 11 Comparison of NPV, IRR and Payback Period Technique Emphasis Investment Rule Criticism Net Present Value Internal Rate of Return Expresses all cash flows in terms of equivalent dollars Expresses all cash flows in terms of an interest rate Invest in projects with a NPV greater than 0.0. Select projects with greatest NPV. Invest in projects with IRR greater than some threshold. Select projects with highest IRR. Lacks a time dimension. Revenues far in the future are more difficult to predict and are more uncertain. No consideration of capital being tied up by project preventing other investments. Essentially a ratio. Is a project with a high IRR and a low NPV preferable to one with a lower IRR and a higher NPV? May

69 54 Payback Period Expresses all cash flows in terms of time Invest in projects that have a payback period shorter than some threshold. Select projects with the shortest payback period. emphasize short lived, nonstrategic projects. Does not consider dollars or cash flows, only time. Is a project that pays for itself quickly necessarily preferred over one with much greater but more distant payback? Since each technique has strengths and weaknesses, projects should be evaluated with respect to all three to obtain a better understanding of potential value Capital Asset Pricing Model (CAPM) A critical question in the NPV technique is how to choose the correct discount rate. The capital asset pricing model provides a means to calculate the relevant discount rate. The Capital Asset Pricing Model is well covered in [38]. The following follows that text and presents significant findings. Generally, investors and firms wish to avoid risk. One way to avoid risk is through diversification. As the overall market changes value, individual securities change price with or against the market with varied ways. For a portfolio consisting of multiple stocks, as the market changes, movements in the individual stocks tend to cancel out each other. Suppose that a portfolio consists of two assets, r 1 and r 2, weighted in proportions x 1 and x 2, then Var(x 1 r 1 + x 2 r 2 ) = x 1 2 var(r 1 ) + x 2 2 var(r 2 ) + 2x 1 x 2 covar(r 1 r 2 )

70 55 Equation 13 Variance of Portfolio of Two Assets [39] The variance of the portfolio is less than the average variance of the individual assets provided that the correlation between the two assets is less than one. Extending this, the variance of a portfolio consisting of many assets can be lower than the average variance of its individual assets depending upon the correlation between the assets. For an investor looking at a particular security, the relevant risk of a particular security is not the risk of the security itself, but rather the how the security increases the risk of their portfolio. The rate of return required by the investor is related to this risk, that is, the investor will require to be compensated only for that portion of the assets risk that is not removed by diversification within the portfolio. Following on this line of reasoning, one might expect that the relevant risk for an individual project is the contribution of that project to the firm s risk, that is, to the risk of firm s portfolio of projects. There are two problems with this. If this were the case, NPVs would not be additive. A new project would change the risk of the portfolio of projects and change the NPV of all projects due to the change in the portfolio risk and the related discount rate. Each project s discount rate would be dependent on its contribution to the portfolio risk. If the risk of the portfolio changes, the discount rate for each project and its NPV would change. The NPV of the portfolio would no longer be the existing NPV of the portfolio plus that of the new project [40]. To evaluate a new project, it would be necessary to recalculate the NPV of all existing projects, which would be an unpleasant prospect. Investors are not willing to pay for a firm to diversify within their portfolio of projects. They can achieve their desired levels of diversification more efficiently by purchasing the securities of multiple companies. The value of a project to investors (the owners of the firm) is independent of its risk relative to other projects the firm is undertaking, that is, to how its risk is correlated to other projects. The risk premium demanded by investors for a particular project is related to the projects correlation with overall market risk. Investors require

71 56 compensation for the part of a projects risk that cannot be eliminated by diversification by purchasing the securities of other firms. For a particular stock, since firm specific risk can be eliminated by diversification, the risk premium demanded by investors is related only to how a firm s stock price varies with the overall market. [41]. This finding forms the basis for the Capital Asset Pricing Model. From [41]: Expected risk premium on a stock = beta x expected risk premium of the market Equation 14 Capital Asset Pricing Model (Risk Premium) Where is the stocks sensitivity to changes in the market, r is the rate of return required by investors for the security, r m is the rate of return for the overall market and r f is the risk free rate of return (for instance, from treasury bills). Equation 15 Calculation of Beta All of this leads to a somewhat practical means of determining the proper discount rates for NPV analysis of projects. Choose a security of a company that performs many projects similar to the project under consideration. Determine the stocks This can be determined by looking at on-line financial information sites such as Yahoo or Google finance. Calculate the rate of return required from the CAPM. The complexity of doing this correctly points to the need for participation of both technology and finance departments in assessment of project value.

72 Sensitivity and Scenario Analysis Discounted cash flow (DCF) or NPV analysis is critically dependent upon estimates for costs and for future cash flows. Obviously, these estimates are error prone. One way to understand and quantify the possible errors in costs and cash flow estimates and ultimately in NPV analysis is via sensitivity analysis. The estimates are functions of sets of independent variables. For instance, cost might be a function of lines of code. Base estimates for each independent variable can be made. From these, base-case cost or cash flow estimates can be produced. Then, one variable at a time can be changed from its base value to pessimistic and optimistic values. Cost and cash flows are recalculated as is NPV. From this analysis, it is possible to determine key variables that impact NPV and to further study them to reduce possible errors. One criticism of sensitivity analysis is that only one variable is modified at a time. Another type of analysis, scenario analysis, attempts to correct this by modifying several variables at a time. For instance, in a software project, choosing a particular programming language may impact lines of code, programmer productivity and defect rates. Modifying each independently, as down with sensitivity analysis, may not reflect reality. Monte Carlo simulations can also be used to study dependencies on several variables at once.

73 Real Options Introduction The valuation techniques discussed in Section 4.1 have a common theme. There is an implicit assumption that project is always carried out as initially planned and that management does not actively modify the project once it is in progress. Cost estimates and cash flows forecasts were prepared and were discounted using a discount rate appropriate for the project risk and NPV, IRR and payback period were calculated. As a project proceeds valuable information is learned. There are opportunities to exploit good fortune and success and opportunities to change direction or even stop the project in the case of bad fortune and failures. Additional knowledge as the project proceeds leads to additional choices and additional opportunities to create wealth or to avoid loss. Opportunities to modify projects as the future unfolds are known as real options [42]. Additional information gathered as the project unfolds and the ability to modify the course of the project have real value. Intuitively, all things being equal, a project that is easy to modify based on better knowledge has more value than a project that is harder to modify once in progress. There are several types of real options or opportunities to modify projects as they progress. The first is the option to expand. An example of this is a pilot project or initial version of a product with a minimal feature set. Suppose that a new web based store is proposed that will allow users to order coffee that will be delivered to them. This new business might be piloted in a limited market and then expanded nationally based on the observed success.

74 59 Expand Nationally Create initial pilot in limited market Observe Results in Test Market Cancel Effort Figure 9 Decision Tree for Option to Expand The high values of certain of certain internet companies such as Amazon and EBay are related to the option to expand. The high stock prices of these firms are related to the perception that they have options to expand infrastructure and technology into new markets. Based solely on a discounted cash flow analysis (NPV) of their current business, their stock prices would be significantly lower. A second type of real option is the option to abandon. Although not the case in the software industry where old software and computers have little or no value, in other industries after the choice is made to discontinue production there is often significant salvage value to equipment and facilities. Depending on choices made during a project, the salvage value may vary. For instance, one means of production may utilize machinery with significant salvage value while another may utilize machinery with less salvage value.

75 The following example is modified from [43]. Assume that a brokerage firm has a choice between developing a specialized object oriented database or using a standard vendor provided relational database, such as Oracle, to support a trading system for a completely new market. The object oriented database is highly specialized, has lower operational costs and no salvage value. The relational database is more standard, has higher operational costs and some salvage value. Suppose that 10 million in licensing costs could be saved by using the relational database on another project if the new trading system fails. Suppose that the project development costs are equal for both technology options. Further suppose that the expected payoffs (incoming revenue discounted to the current time) from each technology are based on the demand for this product and are as follows: Payout (Millions) O.O. Database Oracle High Demand Sluggish Demand The payout represents the NPV of all future cash flows at the time the system is put into use. Clearly, if we were certain that demand would be high, the custom O.O. database is preferred. But suppose that demand is sluggish. With the custom database, the best choice is to keep using the trading system to receive a payout of 8.5 million. The specialized object oriented database cannot be reused. With the standard Oracle database, we could continue to use the system and receive 8.0 million in payout, but a better choice would be to shut it and reuse the database for another purpose saving 10 million. The option to abandon increases the value of the project when a standard reusable technology is chosen.

76 A third type of real option is referred to as a timing option. Suppose that a project is 61 calculated to have a positive NPV, but there are uncertainties. For instance, these uncertainties could be about the overall economy or about projections on future demand. In this case, there may be value in delaying. The overall economy could improve or additional details about future demand might become available. Erdogmus [44] described a phased migration option as a type of timing option. A basic system can be deployed and enhanced in a phased manor. Each enhancement is done only as demanded by market conditions. Real options can quantify this approach. The fourth type of real option is referred to as a production option. Part of the value of modularity in software is due to this. Suppose a new software system is being developed and there is a choice between making the system modular and expandable at higher cost or less modular and more restrictive at lower cost. A simple NPV style analysis might indicate that the less modular approach is preferred. Real options techniques provide a way to quantify the value in a flexible, modular design. Having the ability to combine, and selectively replace or improve software modules increases the value of a system [45] Decision Trees Decision trees can be used to calculate the value of a project when options exist and can also be used to quantify the value of an option. The following example is taken from [46] with modifications. A company is considering entering a new web-based business. It can initially build a rich full featured system or a limited system with minimum functionality. The cost of the full system is 550K, but it will attract more customers. The cost of the minimal system is

77 62 250K and is less appealing to customers. The minimal system can be expanded after one year of use for 150K. Due to shortcuts made during its initial construction, even with an upgrade the minimal system will not be as appealing to customers as the full system. There is uncertainty in the level of demand and thus in future cash flows. Assume that there is a 60% chance of high demand in year one and a 40% chance of low demand. This was determined by marketing and sales groups within the company and will be assumed accurate. Assume that given high demand in year one, there is an 80% chance of high demand and a 20% chance of low demand in year two. Assume that given low demand in year one, there is a 40% chance of high demand and a 60% chance of low demand in year two. Assume a discount rate of 10% is appropriate. Assume that the future cash flows shown have been produced from accurate marketing and sales forecasts. This is depicted below in Figure 10.

78 63 YEAR 1 YEAR 2 High Demand (0.8) 960 High Demand (0.6) 150 Low Demand (0.2) 220 Full System -550 Low Demand (0.4) 30 High Demand (0.4) 930 Low Demand (0.6) 140 High Demand (0.8) 800 Partial System -250 High Demand (0.6) 100 Expansion -150 No additional investment Low Demand (0.2) 100 High Demand (0.8) 410 Low Demand (0.4) 50 Low Demand (0.2) 180 High Demand (0.4) 220 Low Demand (0.6) 100 Figure 10 Decision Tree Example As can be seen from the figure, if the full system is constructed, there is a 60% chance of high demand in year 1 with a cash flow of 150K and a 40% change of low demand with a cash flow of 30K. Given high demand in year 1, there is a 80% chance of high demand in year 2 with a cash flow of 960K and a 20% chance of low demand with a cash flow of 220K. Using discounted cash flows and expected values, it is possible to calculate a NPV for each system choice.

79 64 Full System: Equation 16 NPV Calculation at Start of Project for Full System Partial System: First, look at the decision on whether to expand. Assuming high demand, at the end of year 1, an option exists. The firm can enhance the system or remain with the partial system. Equation 17 NPV Calculation at Year 1 Assuming System Upgrade Equation 18 NPV Calculation at Year 1 Assuming No Upgrade Clearly, if demand is high, the option to expand is preferred.

80 65 Calculating the NPV for the partial system choice from the start of the project yields: Equation 19 NPV Calculation at Start of Project for Partial System Since the NPV for the partial system with an option to expand is higher than the NPV for the full system (117K > 96K), it is preferred. Now, the remaining question is what the value of the option to expand is. Suppose there was no option to expand the system. In that case: Equation 20 NPV Calculation at Start of Project for Partial System with No Option to Expand The value of the option to expand is = 65K. From this example, some immediate shortfalls are apparent. Complexity grows quickly with the number of choices. Decision trees with more than a few choices quickly become unworkable. There is also a need to estimate both cash flows and probabilities. The

81 probabilities of high or low demand are at best rough estimates, at worst, guesses. Real options techniques offer solutions for all of these short falls of decision trees Review of Financial Options Options are complicated. A review of financial options and their valuation is presented as a means of better understanding options. Real options are simply similar techniques applied to real assets and to projects. For the following sections, Google common stock, GOOG, is used as an example. The closing stock price on Nov 11 th was Option prices are: Table 12 November 11th Google Option Prices [47] Expiration Date Strike Call Put 21-Nov Nov Nov Nov Nov Nov Dec Dec Dec Dec Dec Dec

82 67 16-Jan Jan Jan Jan Jan Jan The following terms are used in the sections which follow. Call option: Gives the owner the right, but not the obligation to purchase an underlying asset at a predetermined price. Put option: Gives the owner the right, but not the obligation to sell an underlying asset at a predetermined price. Strike price: The predetermined purchase price of an underlying asset for a call option or the predetermined sale price of an underlying asset for a put option. Exercise date: For American style options, the last date that the option can be exercised or used. For European style options, the (only) date that the option can be exercised or used Call Options A call option gives its holder the right but not the obligation to purchase an underlying asset at a specified execution or strike price on or before a specified exercise date. A European style option can only be exercised on the exercise date. An American style option can be exercised on or before the execution date. The key point is that an option is a right to act, but not an obligation to act.

83 68 For purposes of this discussion, assume the current date is Nov 11 th, The current price of GOOG is From Table 12, it would be possible to buy a Nov call option for GOOG with a strike price of 320 for For $10.4 a call option can be purchased that would allow purchase a share of Google stock for 320 anytime before Nov 21 st (still 10 days in the future since we are assuming it is Nov 11 th ). Since GOOG is currently worth , the option would not be exercised immediately. If the option was exercised, a share of stock could be purchased for 320. Since Google stock is available on the market for , this would not be sensible. Similarly, any call option at a strike price higher than the current price per share is worthless. Exercising it will cause the loss of money. A Nov call option for a strike price of 280 is available for Its strike price, 280, is lower than the current share price, If it were exercised it today (assuming today is Nov 11 th ), neglecting trading costs, the profit will be current share price cost of a share via the option cost of the option itself = = At first, this may seem surprising. The previous paragraph showed that call options with a strike price higher than the current share price are worthless. This paragraph seems to imply that a purchaser of a call option with a price less than the current share would also lose money. The key to understanding options is that their value is derived from variability. If the share price of GOOG was static at , no option could ever be exercised for profit. The current option prices are such that with the current price all are out of the money, that is, they cannot immediately be purchased and executed for profit. The liquid nature of the markets guarantees this. As soon as an option can be bought and executed for profit,

84 Profit bidding occurs and drives up the price until no immediate profit is possible. The value of an option is in variability. The holder of the option can profit when prices change. 69 The November call option for strike (exercise price) 320 costs Figure 1 shows the value of the option as the share price varies. For prices under 320 per share, the option has no value. Its owner has a loss of (the cost of the option). As the share price increases, the option gains value. An important observation is that the potential value is asymmetric. The option buyer can lose at most 10.4, but has unlimited potential. Profit from Call Option to Buyer Share Price Figure 11 Profit from Nov Call Option with 320 Strike Price An analysis of the Nov call option for a 280 strike price yields a similar plot.

85 Profit Profit from Call Option to Buyer Share Price Figure 12 Profit from Nov Call Option with 320 Strike Price A call option becomes more valuable as prices or potential increases. This is similar to a real option to expand. It is significant to note that the value of a call option decreases with strike price and that it increases as the expiration date is extended. Events far in the future have more uncertainty. In the case of Google stock, there would be more time to increase or decrease in value. Since the potential for profit is greater as the time frame increases, the cost of the option also increases Put Options A put option gives its holder the right but not the obligation to sell an underlying asset at a specified execution or strike price on or before a specified exercise date. A European style option can only be exercised on the exercise date. An American style option can be

86 Profit exercised on or before the execution date. The key point is that an option is a right to act, but not an obligation to act. 71 Again, assume it is Nov, 11 th A Nov put option for GOOG for strike price 280 is available for $5. The holder of this option has a right to sell GOOG at 280. Since the current price is , acting on the option would cause a loss. Just as with call options, the value of the option results from variability. If the price of GOOG falls before the option expires, a potential for profit exists. Suppose the price falls to 270. The holder of the option could purchase a GOOG share for 270 (on the open market) and then sell it for 280 (to the unfortunate person who wrote (sold) the option). The profit would be = 5 dollars per share. Profit from Put Option to Buyer Share Price Figure 13 Profit from Nov Put Option with 320 Strike Price A Nov put option for GOOG for strike price 320 is available for The holder of this option has a right to sell GOOG for 320. Since the current price per share is ,

87 someone purchasing and exercising this option would have the following loss: = Put options become more valuable as prices fall. This is similar to a real option to abandon. The option to abandon is worth more when the project is worth less (ir as it fails). It is significant to note that the value of a put option increases with strike price and that it increases as the expiration date is extended. Both call and put options increase in value as the time to expiration increases Valuing Financial Options Upper and Lower Bounds The following plot is based on [48] B Value of Call A C Stock Price Upper Bound Lower Bound Value of Call Figure 14 Upper and Lower Bounds to Value of Call Option The first step in understanding the value of a call option is determining the upper and lower bounds to its value. Continuing with the GOOG example for a 320 exercise price for Nov, suppose that the current share price of GOOG is 0.0. At that price the value of a

88 73 call option, which gives the right to purchase GOOG shares at 320 surely has no value. It gives the right to buy GOOG at 320 per share, but the assumed current share price is 0. As the price of GOOG increases, as long as the price remains below 320, the option has no value. It is less costly to directly purchase GOOG stock. As GOOG share prices rise above 320, the option starts to have value. It becomes possible to exercise the option and buy shares of GOOG at 320 and to resell them for more than 320. If the current share price is 321, the option could be immediate exercised and 1.0 profit made. Suppose the price of the option were less than 1 dollar, say 0.75, anyone could immediate purchase the option, exercise it to immediately earn a profit of = Such arbitrage opportunities would immediately be recognized, assuming a fluid market and the price of the option would be bid up to A similar argument for all share prices above 320 sets the lower bound for the value of the option at share price option exercise price. The upper bound for the value of a call option is the share price of the underlying stock. Suppose the option had value above the share price. For instance, suppose there were buyers willing to pay 100 for an option on a share of stock worth 80. Holders of the option could immediately sell it (to a masochistic buyer) and buy an equivalent number of shares of stock and pocket the difference. In this case, if the share prices rose, holding the stocks instead of the option would yield the same profits. If prices fell below the exercise price, the option is worthless but the stock still has value. It is seen that if the option price (value) is above the share price, owners of the option would benefit by immediately selling it. This forces the value of the option to be at maximum to be equal to the share price. Consider the following points on Figure 14.

89 74 Point A: If the stock (or underlying asset) is worth zero, the option is worth zero. Presumably, if there is any potential for the stock to have value at a future time, someone would be willing to pay some small finite amount for it. If it is zero, it has no potential. No one would buy the stock or the option. Point B: As the stock price increases more and more above the exercise price of the option, it becomes more likely that the option will have value at the exercise date. If it is very likely that the stock price will be above the exercise price, then holding the option is the same as holding the stock except that you don t have to pay the exercise price until you exercise the option. Suppose that GOOG is trading for 1000 and the 320 option is selling for = 680. The buyer can purchase the option for 680 and invest the 320 in a risk free investment. Since it is fairly certain the price of GOOG will be above 320, this is the equivalent of buying a share for 1000, except that 320 does not need to be paid immediately and can be invested. This leads to the option price being the current share price minus the present value of the exercise price. Point C: The exercise price of the option equals the current share price of 320. If the price decreases, the most that can be lost is the purchase price of the option, if the price increases the profit is limitless (the price of the stock has no upper limit). Given this asymmetry, the option has some positive value even when the exercise price equals the current share price. The value of the option at point C is related to the variability of the stock or underlying asset. If it has very low variability, it s quite likely that the share price when the option matures will be around 320. No one will pay much for this option, since it is likely that the payoff is not great. Suppose that the stock (or underlying) asset has high variability. Then it may be worth much less or much more than 320 when the

90 75 option matures. In this case, since losses are limited to the price of the option and gains are equal to the share price minus the exercise price and are potentially large, the option has more value. This is a key observation, the more variability in the underlying asset, the more valuable the option. A second key point to note is regardless of the underlying asset, the longer the period until the option expires, there is more opportunity there is for change. This indicates that the longer the period to expiration, the more valuable the option Valuing Options Call options can be valued by considering the value of an equivalent portfolio formed by purchasing stock and borrowing money at the risk free rate. If this portfolio and the option have the same value at all possible states, then the value of the portfolio must equal the value of the option. If it didn t then an arbitrage opportunity would exist. For instance, if the option were priced higher, owners of the option could sell it and purchase the portfolio and profit. Such arbitrage opportunities would be recognized by participants in the markets. As more and more option owners attempt to sell, as supply increases, the price is forced downward. More people are trying to sell. There would be fewer and fewer buyers. Buyers would realize that they could buy the portfolio instead as well. The price of the option would drop until it reached that of the portfolio. The following is based on [49]. To value a call option on a stock, suppose that the underlying stock is currently priced at S + = 180 $100 and that in one time q S = q S - = 60

91 period it will either increase in value to $180 with probability q or decrease in value to $60 with probability 1-q. 76 Figure 15 Stock Prices of Hypothetical Security Now, look at the value of a call option on the same security assuming the same possible movements in stock price over the period. Assume for now that the exercise or strike price of the option is 112. The value of the option at the end of the period, C + or C -, is easily calculated based on the stock price and the exercise price as shown in the figure below. But what is the value of the option at the start of the period, that is, what is C? C + = max(s+ - E, 0) = max( , 0) = 68 q C 1 - q C - = max(s- - E, 0) = max(60-112, 0) = 0 Figure 16 Option Prices on Hypothetical Security Suppose, an equivalent portfolio is constructed by buying N shares of the stock and also borrowing money (B) at a risk free interest rate (r) to finance the purchase. At the end of the period, the principal of the loan plus interest would need to be repaid, (1+r)B. The

92 porffolio also have N shares of the stock worth either NS + or NS - depending on the movement in the share price. 77 C + = NS + - (1+r)B q C = NS - B 1 - q C - = NS - - (1+r)B Figure 17 Price of Equivalent Portfolio Since the option and the portfolio have the same returns at the two possible states at the end of the period, the above diagram yields two equations in two unknowns (N, B). The values of S +, S -, C +, C - at the end of the period are known as shown in the above diagrams. Equation 21 Relationship of Call Price to Hypothetical Portfolio at Start of Period Equation 22 Relationship between Call Price and Hypothetical Portfolio with Increase in Stock Price Equation 23 Relationship between Call Price and Hypothetical Portfolio with Decrease in Stock Price

93 78 Using Equation 22 and Equation 23 and solving for N and B yields: Equation 24 Number of Shares Equation 25 Size of Loan in Portfolio The return of the option, $68 if the stock price increases to $180 and $0 if the stock price decreases to $60 can be replicated by buying shares and borrowing $31.5. The value N is also known as the replication ratio or options delta. Plugging these values back into C = NS B (Equation 21) yields The value of the option (at the start of the period) is $ As given in [38], Equation 24 and Equation 25 can be substituted into Equation 21 to yield. Equation 26 Value of Call Where, p is the risk neutral probability and is given by:

94 79 Equation 27 Risk Neutral Probability Application of this to software projects will be shown in a following section Relationship between Calls and Puts The value of puts on an asset is related to the value of calls on the same asset. From [50]: Value of call + present value of exercise price = value of put + share price Or Value of put = value of call + present value of exercise price share price Factors impacting the price of options Table 13 Factors Impacting Option Prices [51] Factor Price (value) of call Price (value) of put Stock or asset price increase Increase Decrease Exercise or strike price Decrease Increase increase Interest rate increase Increase Decrease Time to expiration increase Increase Increase Volatility of stock price or asset Increase Increase

95 80 On key observation from the above is that both puts and calls increase in value with variability, either due to an increase in the volatility of the underlying asset or due to an increase in the time until the option expires. With respect to real options, this indicates that risky projects, with greater rewards and greater chance of failure, have more value than less risky projects. At first, this is very counter intuitive. With NPV analysis, increased risk decreases value. With options, increased risk increases value. This is due to the asymmetry of options. The most that can be lost is the cost of the option, but the gains are limitless. High variance means high potential gains while the losses are still limited. The option or choice to invest in a risky project has more value than the option to invest in a less risky one Black Scholes Formula The technique shown on Section 4.3.5, Valuing Options, derived the value of an option by creating a leveraged portfolio (consisting of some amount of the asset plus a borrowed amount) that would have the same returns as the option. A leveraged portfolio is created by simply borrowing money to finance some portion of the asset or stock purchase. In section 4.3.5, the return over a single time interval was considered. By subdividing the time interval into progressively smaller periods, it is possible to derive the Black-Scholes formula. Derivation of this formula is beyond the scope of this thesis, but the interested reader is referred to [52]. The Black-Scholes formula provides a means to evaluate the value of a call option, and via section the value of puts. Let:

96 81 As developed in [52], the Black-Scholes formula for the price of a call option is given by: Where Equation 28 Black-Scholes Formula A cumulative distribution function, F(X), is the probability that a random variable, X, is less than or equal to some value, x. A standard normal distribution is a Gaussian distribution with 0 mean and unit variance. So N(d) is the probability that a random variable with a standard normal distribution is less than or equal to d.

97 An application of the Black-Scholes formula to real assets (projects) is presented below in section Introduction to Real Options/ Extended NPV Financial options are pieces of paper, or more accurately today, electronic records, that grant the right to purchase or sell other pieces of paper such as stocks or other similar instruments. The purchaser of an option is paying at the current time for the right or ability to take another action in the future. They are seeking to profit from the flexibility to act on uncertain future events. If the future unfolds favorably, they can profit by investing more. If the future unfolds unfavorably, they have lost only the cost of participation, that is, the cost of the option. The valuation techniques used in financial options are ways to assess the value of this flexibility. The value of an option, or equivalently the value to have the flexibility to act, was seen to depend upon the current worth of the asset, the amount of time until a decision is needed, the amount of variability in the value of the asset and the risk-free interest rate (the opportunity cost, since instead of trying to benefit from flexibility an investment with certain returns could be chosen). These factors determine the value of the option. The value of the option is what an investor will pay today for that flexibility. Real options are an application of financial options theory to real assets or projects. By making analogies between elements in investments in projects and elements in investments in securities (stocks), the valuation techniques of financial options can be used to assign value to flexibility in projects. This is best understood by illustration. Suppose that is necessary to build a prototype to determine the feasibility of building a full system. An investment is being done now (the cost of the prototype) for the option of

98 83 building a full system later. This is analogous to buying a financial option to buy a stock at a later date. In both cases, there is flexibility. After building the prototype, there is a choice of either building the full system or simply discontinuing the project. After purchasing the financial option, there is a choice of either purchasing the stock or not. In both cases, there is uncertainty. The feasibility of the system and conditions for its use, its potential value in the future, is uncertain. The future stock price is uncertain. Both cases are investment decisions. Both have the same opportunity cost. Rather than engaging in a project that has risk, or trying to invest in a stock that has risk, it s possible to invest in a risk-free investment such as a government bond Option to Defer Discounted cash flow/npv analysis assumes that the decision to invest must be made now. The project is either accepted or rejected at the present time. However, there are many situations where it is beneficial to wait until more information is available or until there are favorable changes in market conditions or the cost of resources. Agile based approaches to software development derive much of their value from the option to defer. Decisions are delayed by building incrementally. Later releases benefit from information learned in early releases and by delaying decisions it s possible to react to favorable or unfavorable changes in the environment. Value is maximized by deferring. The value of agile approaches is increased by situations that are highly variable. Options are worth more if range of possible outcomes is wide. It s interesting to note that SDLC, waterfall type software development processes derive value from reducing variability by having standardized processes. Reduced variability reduces risk. Reduced risk lowers the discount rate that should be used in static NPV analysis of projects. Since the discount

99 rate is in the denominator of the terms in NPV calculations, a lower discount rate from reduces variability increases value. 84 The following is based on [53]. Suppose Microsoft is considering whether to develop a new version of its Windows operating system. It has a proprietary license to produce Windows. Assume that it takes one year to develop the new OS. Further assume that the expected future cash flows depend on the future demand for new PCs. If demand is high, future cash flows will be 180 million. If demand is low, future cash flows will be 60 million. Assume that there is a 50% chance of high demand and a 50% chance of low demand. Development costs are 80 million. Should a project to build a new OS be conducted? The first step in the analysis is a static NPV calculation. V + is the value of the project at the end of the period (in one year) assuming high demand. V - is the value of the project at the end of the period assuming low demand. V is the value of the project today and must be calculated. V + = 180 q = 0.5 V 1 q = 0.5 V - = 60 Figure 18 NPV Analysis for Option to Defer Example Investment: I = 80 (based on cost estimates)

100 Discount Rate: k = 0.20 (discount rates can be determined via the capital asset pricing model) 85 Risk-free rate: r = 0.08 (assume this to be the case) Actual probability: q = 0.5 (from marketing/sales forecasts of future demand) Risk-free probability: The present value of the future cash flows can be equivalently be calculated using riskfree probabilities and rates. Equation 29 NPV Analysis using Risk Free Discount Rate - Option to Defer Example Or using the actual probabilities and risk adjusted discount rate. Equation 30 NPV Analysis using Risk Adjusted Discount Rate - Option to Defer Example The NPV of the project is given by: NPV = V I = = 20 million. Equation 31 Static NPV of Operating System Example Based on a positive NPV alone, the project would be accepted. But should the project be conducted? There is substantial risk (50%) that demand will be low for PCs and the investment will lose money. Only 60 million in cash flows would be generated one year

101 86 hence and 80 million is required as an investment. If management had no other options, no flexibility, given that the NPV is positive, the project should be conducted. But management does have options. Only Microsoft can produce a new version of Windows. management could choose to wait one year to see the level of PC demand and then decide whether to invest. C + = max(v + - I, 0) = max(180 80, 0) = 100 q C 1 - q C - = max(v - - I, 0) = max(60-80, 0) = 0 Figure 19 Option Analysis for Option to Defer Example C + is the value of the option at the end of the period (one year) if demand is high. In this case, future revenue would be 180 and the development cost is still 80. The possible choices available would be to conduct the project and earn = 100 million or do nothing. Clearly the project would be done one year given high demand, so C + is 100 million. C - is the value of the option at the end of the period if demand is low. In this case, future revenue is 60 and the development cost is still 80. The possible choices in this case are to invest 80 to get back 60 or to simply not conduct the project. C - is 0 since it is preferable to not conduct the project rather than lose 20 million. Based on this analysis, if demand is high after waiting one year, then invest. Otherwise, don t. This option is worth the following.

102 87 Equation 32 Option Value - Option to Defer Example The option to wait is worth more than the NPV from the immediate execution of the project. The value C can be considered as an extended NPV that includes the static NPV plus the value of flexibility. Management should wait to see how demand for PCs evolves over the next year. Intuitively, this result is correct. Given the substantial risk of loss and the ability to wait, it should be better to resolve market uncertainties before investing. One significant point to note is that this analysis neglects the impact of possible competitors. While Microsoft is waiting for market uncertainties to resolve, competitors could capture the OS market. As will be explored in section 4.4 of this thesis, game theory can be used to analyze such competitive interactions. The following analogies exist between real and financial options [54]. Table 14 Analogies between Real and Financial Options for Option to Defer [54] Variable Real Options in Projects Call Option V Present value of expected cash Stock Price flows I Present value of investment Exercise Price outlays T Length of deferral time Time to maturity r Risk free rate Risk free rate 2 Volatility of project returns Variance of stock returns

103 Option to Expand Once a project is underway, management may have options to modify the level of output. If demand is high, it may be possible to invest more to expand production. If demand is low, planned expenditures can be reduced. An option to expand the scale of production by e% is analogous to a call option, C, on (a fraction of e%) the value of a project [55]. The exercise price of an option to expand is the additional investment outlay. Suppose that demand is high in the OS example of and that management can expand production by 50% by investing an additional 40 million (perhaps by advertizing more). In this case: The project value at one year is given by: Equation 33 Project Value at Year 1 - Option to Expand Example That is, it s possible to continue with the original plan or increase sales by 50% by investing I 1. Equation 34 Project Value at Year 1 with High Demand - Option to Expand Example Equation 35 Project Value at Year 1 with Low Demand - Option to Expand Example

104 89 Discounting this back to the start of the project: Equation 36 Project Value at Start of Project - Option to Expand Example The expanded NPV is: Since the static NPV is 20 (Equation 31), the value of the option to expand is The option value can be calculated directly as: C + = max(v + - I, 0) = max(0.5*180 40, 0) = 50 q C 1 - q C - = max(v - - I, 0) = max(0.5*60-40, 0) = 0 Figure 20 Option Value Calculation - Option to Expand Example Equation 37 Option Value Calculation - Option to Expand Example

105 Compound Options As an example of compound options, suppose a project is being considered to develop and then market a new technology to deliver high definition quality movies via the internet. Assume that the project will consist of the following: An initial two year research and development effort A large investment to develop infrastructure at the start of year two. Positive cash flows beginning in year three continuing until year ten. After year ten, it will be assumed that another technology will be developed and will cause this technology to be obsolete. Essentially, the operation will cease in year ten. Assume that the rate of return demanded by investors for a security with similar risk to this project is 15%. Assume that capital for the development and infrastructure costs is available at a 4% interest rate. Assume cash flows are as shown in Figure 21 and in Table Cash Flows T h o u s a n d s Year Figure 21 Cash Flows for Internet Based Movie Delivery Example

106 91 The net present value of the project can be calculated as follows. Table 15 Present Values of Cash Flows for Movie Delivery Example YEAR CASH FLOW PRESENT VALUE The sum of the present values is -34,000. Based on NPV analysis, this project would not be done despite its potential. Intuitively, this seems wrong. Delivering high quality movies directly to consumers via the internet would seem to have great potential. The problem in this case, and with NPV analysis in general is the analysis is that it is static. Regardless of how well or poorly the R&D phase progresses and regardless of how demand materializes in year three forward, there is an assumption that management will fully commit or not to the project on day zero and will run the project unaltered for the

107 entire 10 year period regardless of what additional information is available. Clearly, this does not represent how companies behave. 92 In reality, management has two decisions. In year zero it can decide to engage in a two year R&D effort and in year two it can decide whether to invest in full scale production. The R&D effort can be viewed as an option. It provides the opportunity, but not the obligation, for the company to invest for full scale production in year two. The opportunity to invest in year two is really a (call) option with a strike price of 1350 thousand (the additional investment required to start production, that is, to begin actually selling movies) with an expiration date of two years on an asset worth the NPV of the cash flows from years 3 through 10. The present value of the cash flows from years three to ten can be calculated as follows (discounted to year 2, again assuming a 15% discount rate). Table 16 Cash Flows Years 2 through 10 YEAR CASH FLOW PRESENT VALUE

108 As seen by the NPV analysis, based on this static view of the future, the project was not worth conducting. But suppose during years 1 and 2, while the company is conducting R&D, market conditions change. There could be an expansion of the number of households with broadband access or there could be a recession that limits spending on entertainment. Assume that demand will either increase by 50% per year or decrease by %. Marketing data or market surveys might be used to determine these market swings Figure 22 Possible Changes in Demand (Movie Delivery Example) The risk free probability is given by:

109 94 Equation 38 Risk Free Probability (Movie Delivery Example) In Equation 38, the actual probabilities, 1/2 change of increased sales and 1/3 chance of decreased sales were used. As in section 4.3.5, Valuing Options, the value of a call option is For commercial use, an investment of 1350 is required at year two. The value of the project is the maximum of (the expected revenue minus the investment) and zero. If the expected revenue is less than the required investment, the project will be abandoned. The most revenue expected is 2840; the least is 567 and if there is no change in demand, 1268 is expected (see Figure 22). Working backwards from year two: Max( ,0) = 1490 C H C Max( ,0) = 0 C L Max( ,0) = 0 Figure 23 Working Backwards in Movie Example

110 95 Where: So, the value of the option for commercial implementation of this project is 273 thousand. The cost of obtaining this option is the cost of the R&D effort discounted back to year zero. For a cost of 48,500, management may purchase an option worth 273,000. The project is worth doing when management flexibility and the variability of the market are considered Example of Application of Black-Scholes Formula

111 The example given in section contains many assumptions about the future. The potential upward and downward movements in the market for high definition movies delivered by the internet are assumed to be 1.5 and 0.67 respectively. There may be some marketing data to support this, but this is more likely a guess at best. We ve made assumptions about future cash flows as far as 10 years out. This is possible to do, but it quite error prone. An alternate approach is described in [56]. The following procedure is suggested. 1. Identify a replicating or tracking portfolio, and calculate its price and volatility 2. Size the investment relative to the replicating portfolio 3. Apply standard financial option pricing tools, particularly Black-Scholes 96 Continuing the same example as in , the first step is to identify a replicating or tracking portfolio. This means, a security with the same risks and potentials as the real asset under consideration must be identified. Assume that following considerable analysis, it is determined that Netflix, NFLX, is such a security. On Jan 15, 2009, NFLX traded for $31.26/share with a market capitalization of 1.83 Billion. The volatility of the stock from ivolatility.com is 63%. Assume the risk free interest rate is 4% as in section Assume the project (new movie distribution service) can capture 10% of the market. In practice, this might be based on an assessment of marketing forecasts and an assessment of planned technology against that used by the competitor, Netflix. 10% of the current market is work 1.83 billion *.1 = 183 million. Also assume that the market size will be the same in two years, meaning the current share price (183 million) equals the strike price (what it will be in two years). This example is meant to illustrate the use of the Black-Scholes formula, so the inputs and results do not directly correspond to the example in the previous section,

112 97 Share Price 183 Strike Price 183 Time to Expiration (Days) 730 (2 Years) Volatiliy 63% Annual Risk Free Interest Rate 4% Calculating the option value (essentially what this project is worth) using Black-Scholes by hand is cumbersome and difficult. Standard calculators are available on the internet [57] [58]. Using available Black-Scholes calculators, the value of this option is 68 million. Consistent results were obtained using several on-line calculators. If the total investment required is less than this, it may be a good project to conduct Discussion Real option approaches are seen to capture the value of management flexibility. Two key assumptions are made during option valuation. There are no arbitrage opportunities. That is the market is fluid, fair and transparent. That there exists a twin security traded on the market that has the same risk characteristics as the project under consideration.

113 Both of these assumptions are questionable. Can we really identify a twin security? In section , does an investment in Netflix really have the same risk as the proposed project? Does it have the same potential? Are the results of the project correlated with the returns on Netflix? It s more reasonable that the opposite is true. The better Netflix does, the worse the prospects for the project. Perhaps a negative correlation exists. [56] notes that there is little evidence that the correlation between an individual investment and a twin security is valid. It notes that the co-variances (betas) of individual securities and the overall market are well studied, but that covariances between pairs of securities or investments (projects in the context of this thesis) are not. Further noted is that The real-option approach may provide qualitative insight even if some of the underlying assumptions are invalid. 98 If we accept that at least qualitatively, a real option approach provides insights into the value of projects, there are still dimensions not captured by this approach. In particular, there is no consideration of the interactions with competitors and with market timing. Is there value to being first to market? Suppose competitors either increase or decrease production or enter or leave markets? Game theory approaches attempt to analyze this. 4.4 Game Theory Approaches to Project Valuation Introduction One significant lacking in the NVP/Discounted Cash Flow and Real Option valuations of projects is that there is no explicit evaluation of the impact of possible competition or cooperation. The actions and reactions of other firms can have significant impact on the profitability and thus the value of any proposed effort. NPV valuations are static. They evaluate what will happen if the project is blindly continued regardless of how reality unfolds. Real options are a valuation technique that includes management flexibility. The ability to decide to continue or not, to expand or contract and to delay can

114 99 significantly increase project value. Lacking in this valuation technique are tools to understand and evaluate potential competitors or partners. For instance, real option techniques may tell us that there is value in delaying until more information is available or until ambiguity is resolved. This is true in a world where the firm has a monopoly. This is also true in a world of perfect competition, where a late entrant into a market with better technology or prices could easily capture its share of the market. With reality somewhere between these two extremes, game theory offers a systematic way of thinking about and evaluating the impact of other firms on the value of a project. It allows an understanding of which strategies will lead to competitive responses and which to cooperative responses from other firms. One caveat is that the project under consideration needs to significant enough to have strategic value to the firm. Competitors react to entry into new markets, significant new technologies, major changes in products and start ups. As such, game theory analysis is irrelevant for smaller efforts where a competitor would be unconcerned and probably unaware Definition of Game Theory Stripped to its essentials, game theory is a tool for understanding how decisions impact each other [59]. It involves being able to visualize, analyze and anticipate the actions and reactions of competitors, or in game theory terminology, of players. Game theory studies techniques for players (management) to make optimal decisions to maximize their returns in an environment with other players (other firms) Nash Equilibrium / Prisoners Dilemma Example For certain games, as each player reasons about all possible benefits and consequences and about the actions of other players, it s possible that as all players seek to maximize

115 100 their returns, the chosen actions of all players will converge into a single consistent set. All of the reasoning and actions of players converge into an equilibrium where each player will receive their maximum benefit. Given the situation and the rationally driven actions of each player, no other course of action by any single player would increase their return. This equilibrium is sometimes referred to as a Nash Equilibrium. Nash equilibrium is best understood by examining a simple game known as the Prisoner s Dilemma. Two suspects, prisoner A and prisoner B, are arrested for a crime and are interrogated separately by the police. Each suspect is offered two choices: Confess and implicate the other suspect and receive a more lenient sentence. Remain silent. Don t confess; don t provide evidence against the other suspect. Further assume: If both remain silent, they both will receive light 1 year sentences due to the lack of evidence of more serious crimes. If one turns evidence and the other remains silent. The rat receives no sentence and the one who remains silent receives a 10 year sentence. If both talk, they both receive 5 year sentences. Table 17 Classic Prisoner's Dilemma Prisoner A MUTE TALK Prisoner B MUTE (1,1) (0,10) TALK (10,0) (5,5)

116 The actions of prisoner A are shown on the horizontal. The actions of prisoner B are shown on the vertical. The potential outcomes are as follows: 101 (1, 1): A receives a 1 year sentence; B receives a one year sentence (0, 10): A receives a no sentence; B receives a ten year sentence. (10, 0): A receives a 10 year sentence; B receives no sentence (5, 5): Each receives a 5 year sentence Prisoner A can either be mute or talk and he does not know what B will do. His reasoning would be as follows: If B is mute, if I am mute I receive a 1 year sentence and if I talk, I receive no sentence. Clearly in this case it is better to talk. If B confesses, if I am mute I will receive a ten year sentence and if I talk, I will receive a five year sentence. Again, it is better to talk. So regardless of the actions of B, A s best option is to talk. A similar analysis of B s options leads to the same conclusion for B. It s better to talk regardless of what A does. In game theory, when a player has an optimal decision regardless of the actions of other players, that decision is said to be dominant. In this game, both prisoner A and prisoner B have dominant actions regardless of what the other does. Since both will chose their dominant actions, equilibrium exists. Both will talk Commitments In real option analysis, a premium was placed on flexibility. Managerial choice added value at various stages of the project. In game theory analysis, the lack of flexibility or said another way, commitment can add value. If a competing firm can view a firm s

117 102 commitment to invest and participate in a particular market, they may choose not to compete. It may be better not to compete rather than compete and face joint disaster. A first entrant to a market, if deeply invested and committed, may deter other firms. If a firm has no choice but to continue in a particular market, competitors may choose not to engage them. As an example, Microsoft is deeply entrenched in the operating systems business. They are very unlikely to leave that market regardless of which competitors exist. Too much of their revenue is generated in this market to allow any flexibility by Microsoft s management. This commitment deters competitors. Competitors would face a long extended costly battle for market share. This type of commitment is also referred to as a credible commitment. There is no doubt of Microsoft s commitment in this market Games Game theory reduces complex strategic decisions to four dimensions [60]. Identification of the players The players in making strategic decisions are management. One key assumption in simple game theory is that the actions of the players are rational. That is, they analyze the game and make decisions to maximize value. Other factors that may impact the decisions of people such as ego, hatred, revenge and favoritism are not considered. Since these factors are present in most decisions, a valid criticism of game theory is that it fails to account for psychological factors. Smit [61] notes that although these factors can play a role, the assumption of rationality is a good starting point in understanding for business and economic decisions. Timing or order in which the players make their decisions Games can involve simultaneous or sequential play. With sequential play, which player moves first can have impact on the outcome of the game. The available actions and information set Players may or may not have complete information about the environment or about other players. The payoff structure attached to each possible outcome.

118 103 It s necessary to identify the source of value for the players. This may be shareholder value evaluated with techniques such as NPV or real options or it may be to gain market share or maximize short term profits. Once a game is characterized along these dimensions, game theory provides techniques for each player to come to analyze and understand potential moves by competitors and to work toward a solution. As noted in section 4.4.3, a key to solving games is to look for dominant strategies, that is, strategies that maximize value regardless of the actions of other players Scenarios The following scenarios follow the discussion in [62] Prisoner s Dilemma The classic prisoner s dilemma game was described in section Competition between two firms, each seeking to introduce a new innovation, can be described as a prisoner s dilemma game. Each firm can choose to invest at the current time or wait to allow time for the market to be better understood or for technical issues to be resolved. Without competition, real option analysis shows the value of delay under some circumstances. With competition, a prisoner s dilemma type game can be used to understand the strategic choices available and their impact on value. Table 18 Analogies between Prisoners and Firms in Classic Prisoners Dilemma Game Prisoner s Dilemma Analogous Strategic Game Players Prisoners Firms Option Confess / Turn Evidence Invest immediately Option Remain silent Wait to resolve uncertainty Possible outcome for Receives no sentence Obtains full value of project individual player without added value from delay. Possible outcome for Receives short sentence Shares value of project with

119 individual player Possible outcome for individual player Possible outcome for individual player Best possible outcome for individual player Nash Equilibrium Receives sentence intermediate Receives long sentence Prisoner confesses while other prisoner does not. Prisoner who confesses receives least possible sentence. Prisoner who doesn t confess receives maximum sentence. Both players confess. Both receive intermediate sentence. 104 added value from delay Shares value of project without added value from delay Receives no value. Firm invests immediately. Other firm does not invest. Firm that invests receives maximum value (without added value from delay). Firm that doesn t invest receives no value. Both firms invest immediately and share lower value. As an example, let s assume that there are two competing software firms preparing to invest to create virtual reality video games. Each firm has two choices: Invest immediately. Delay to resolve uncertainty and benefit from flexibility as the environment evolves. Further assume: The current NPV value of the market for virtual reality games is 1 billion. This will be shared by all firms that participate in the market. In this example, if only one firm invests it will receive the whole value; if two firms invest they will share this value. The value of the market including the added flexibility due to delay based on real option analysis is 1.2 billion. Perhaps by delaying, better technology could increase future sales or a better understanding of the market from additional studies could produce more popular games. Based on the choices made, this could be received by one firm or shared by both. If both firms delay, they will share the maximum value of the market including the value added by managerial flexibility to respond to market or technology changes.

120 If one firm invests immediately while the other doesn t invest it will receive the entire NPV without the added value of flexibility. If both firms invest immediately they will share the NPV without the added value of flexibility. Table 19 Prisoner s Dilemma Game between Firms 105 Firm A Delay and invest Invest Immediately Firm B Delay and invest (600,600) (1000,0) Invest Immediately (0,1000) (500,500) The actions of firm A are shown on the horizontal. The actions of firm B are shown on the vertical. The potential outcomes are as follows: (600, 600): Both firms share 1.2 billion (1000, 0): A receives 1 billion; B receives nothing. (0, 1000): A receives nothing; B receives 1 billion (500, 500): Both firms share 1 billion To solve this game, the first step is to determine whether a dominant strategy exists. For firm A: If firm B delays, A should invest immediately to receive 1000 rather than 600. If firm B invests immediately, A should invest immediately to receive 500 rather than 0.

121 106 Since firm A s best strategy is to invest immediately regardless of B s actions, a dominant strategy for A exists. Similar analysis leads to the same conclusion for B, that is, B should invest immediately. This leads to a Nash Equilibrium as indicated in the table by the highlighted cell. There are several interesting observations that arise out of this example. NPV/discounted cash flow, real option and game theory analysis assign different value to the project. The project value based on NPV analysis without consideration of potential competitors is 1 billion. The project value based on real option analysis without consideration of potential competitors is 1.2 billion. The project value based on game theory analysis is 500 million. This indicates that a careful analysis of potential competitors is a crucial step in determining value and in determining the best strategic direction. As indicated in the sections on real options, there is value in flexibility and it must be considered. Competition is seen to remove flexibility. There s no value in waiting for more information if a competitor can remove all your options by gaining the entire market while you delay. Game theory analysis depends on NPV and real option analysis. Those techniques are used to assign value to the various choices available. Game theory can be used to choose between choices. Game theory applies to projects with strategic value. For small routine projects, competitors are unaware and probably unconcerned. An understanding of the market and of competitors is needed to perform valuation of projects with strategic value Grab the Dollar A classic grab the dollar game involves two players sitting with a dollar between them. If only one player grabs for the dollar, they get it and win. If both grab for the dollar, it tears in half. They both get a worthless torn dollar. Both lose. This is analogous to the situation when two firms are competing in a market that can only support one firm or perhaps one standard.

122 107 Table 20 Analogies between Prisoners and Firms in Classic Grab the Dollar Game Description Grab the dollar Two players sit at a table with a dollar between them. They can either wait or grab the dollar. If one grabs, he wins the dollar. If both grab, they tear the dollar and both lose. Analogous Strategic Game Two firms are considering an investment in a market. The firm that invests first (leads) will gain most of the market. The second firm can follow and gain a small slice of the market. If both firms try to lead, they will both lose money. Players People Firms Option Grab for dollar Lead. Invest heavily, establish a standard and gain most of market Option Don t grab Follow. Enter the market later and get a small share. Possible outcome for individual player Possible outcome for individual player Possible outcome for individual player Best possible outcome for individual player Get a dollar Get half a dollar (presumed worthless) Get nothing Dependent on sequence of play. By moving first, you win. Gain most of market Lose money in costly battle over establishing a standard Gain a little piece of the market Depends on sequence of actions. Described below. Suppose the following situation. Two firms are considering investing in a new innovation that requires the establishment of a standard or format and the market will support only a single standard. Further assume that if both firms invest fully and attempt to lead in the market and establish a standard, they will both lose money in a costly battle. If one firm invests and leads, it will gain most of the market. The second firm could then invest and using the same standard could obtain a small slice of the market. As an example of this type of game, two rival consortiums of media and electronics companies have been competing over the last several years to establish a new standard for high

123 definition movies: Blu ray and HD DVD. Similar battles have occurred in the past over standards in media formats, operating systems and computer hardware. 108 Each firm has two choices: Lead: Invest heavily to try to establish a dominant standard. If the attempt is successful, it will gain most of the market share and value. If the attempt fails, the firm will lose substantial money. Follow: Let another firm establish the standard. Enter the market later, perhaps pay royalties to the first firm, and accept a lower market share and value. Further assume: If only one firm attempts to lead, it will be successful. If both firms attempt to lead, they will both fail and suffer loses. The total market has a NPV value of 1 billion. A successful leader will get 90% of the market; a follower 10%. Failure will result in a loss of 200 million for a firm. If neither firm attempts to lead, no product at all is developed. This is analogous to neither player grabbing for the dollar in a grab the dollar game. No play occurs. Table 21 Grab the Dollar Example Firm A Follow Lead Firm B Follow (900,100) Lead (100,900) (-200, -200) The actions of firm A are shown on the horizontal. The actions of firm B are shown on the vertical. The potential outcomes are as follows:

124 109 Neither firm participates (900, 100): A receives 900 million, B receives 100 million (100, 900): A receives 100 million, B receives 900 million (-200, -200): Both A and B loss 200 million The solution of this game depends on whether play is sequential or simultaneous. Assume that firm A has no knowledge that B is doing research and development toward this market or of B s actions. Clearly, A would choose to invest under the assumption that it had no competitors and that it would gain the entire value of the market. If it were aware of B s intent to participate in the market, its actions depend on the sequence of play. If A is able to act first (winning a race to innovate) it gains most of the value (most of the market). This is shown in the top right cell of the table. If B has already invested heavily, A s best choice is to follow. A would receive 100 million. If A attempts to catch up (lead as well), the results are disastrous for both A and B. They both lose. The key observation of this example is that the sequence of play can be critical. The rush to be first to market can be a key to success in some situations Burning the Bridge The burning the bridge game is best illustrated by the following scenario. Suppose an island exists between two hostile countries, A and B. Each is connected to the island by a single bridge and each wish to occupy the island. Neither wants a prolonged costly war. Suppose A moves its army onto the island and then burns the bridge, leaving its army stranded on the island. Without the possibility to retreat, A s army can only fight. B has two choices; it can either enter a costly unwanted war or cede the island to A. Given A s demonstration of commitment and assuming B s wish to avoid for battle, B will cede the island.

125 110 In a similar way, a firm s demonstration of commitment can deter competition. A perceived commitment, whether real or not, can be equally effective. If competitors are convinced of a firms commitment, that is sufficient to deter them. Commitments were discussed in section Discussion Game theory approaches are seen to offer ways to reason about the environment that a project will be conducted in and about the impact of possible competition or cooperation. It is relevant for large strategic types of projects such as entering new markets, new businesses or introducing entirely new products. 4.5 Process Measures Introduction The financial measures described above, are dependent on an estimate of cash flows, that is, on the revenues earned by the product developed by the software project. The projects presented as examples above all had a product sold in the market place or companies competing in the market place. This leads to an important question. How can the financial value of internal projects, those that do not produce a product for sale but instead satisfy internal business needs with a firm, be evaluated? Many internal projects are done to improve business processes, support new business processes, to reduce labor and other resources needed or to improve quality of processes or products. All these changes are measurable. It may be challenging to design and perform process measures, but all changes are measurable [63]. If they are not measureable, then they have no impact at all and the project should not be done.

126 Generic Process Frameworks Process measures are to some extent dependent on the specifics of a particular project. For instance, the measures appropriate for projects related to security will differ from projects related to transactional business processes or to projects related to the delivery of health care services. Several authors [64] [65] have attempted to create generic frameworks of business processes. From these frameworks, sets of process (operational) measures can be elicited. These frameworks are seen as ways to identify and elicit relevant process goals. The following list of generic process goals is compiled from multiple sources including [64], [65]. Table 22 Generic Process Goals Category Process Planning and Support Supplier Relations and Inbound Logistics Production Operations and Process Goal Improve the process and content of decision making [64], [65] Improve Intra-organization communications [64], [65] Provide better coordination among functional areas in your corporation [64] Reduce transaction costs by making it easier for suppliers to handle orders [64] Reduce variance in supplier lead times [64] Enhance the ability to monitor the quality of products and services from suppliers [64] Help to gain leverage over suppliers [64] Help to coordinate closely with suppliers [64] Reduce the cost of materials [65] Increase the level of production / Improved throughput [64] Retire systems [65] Reduce waste / scrap [65] Reduce headcount [65] Reduce employee turnover [65] Improve employee productivity [65] Improve system uptime Reduce days of inventory [65] Reduce rework Improve product / process quality

127 Product and Service Enhancement Sales and Marketing Support Customer Relations and Outbound Logistics Reduce time to market [64], [65] 112 Reduce variance on product/service quality [64] Facilitate the tailoring of products/services to markets [64] Reduce the cost of designing/developing new products / services [64] Provide support for identifying market trends via analytical tools [64] Assist the firm in locating or serving new markets [64] Enhance the accuracy of sales forecasts [64] Increase firm s ability to anticipate customer needs [64] Track market responses to pricing strategies, discount strategies, promotions [64] Optimize existing markets [65] Increase cross-selling [65] Reduce days of receivables [65] Enable your corporation to provide administrative support to customers [64] Facilitate a high level of responsiveness and flexibility to customer needs [64] Reduce the variance and uncertainty in product/service delivery times [64] Increase available information about customers [64] Help your corporation coordinate with customers [64] General Risk Avoidance [65] Reduce capital Hardware/Software expenses [65] Become vendor of choice [65] Increase Good Will [65] Increased flexibility allowing redistribution of resources Process Measures Each of the process goals in the proceeding section can be related to quantitative benefits. Examples are presented below. Process Goal Examples quantification of Improve the process and content of decision making Example: Reducing losses due to bad loans. Calculation: reduced percentage of bad loans * number of loans made * loss per loan

128 Process Goal Examples quantification of Improve Intra-organization communications Example: Assume that one department sent information via to another department who in turn used it to update a status of a particular transaction and that this process is being replaced by one that allows the first department to make updates directly. Calculation: Number of status send per day * (minutes spent per transaction in old process minutes spent per transaction in new process) * (1 work day / number of minutes per day) * adjusted average labor cost per workday * scaling factor Assumption: Some fraction of saved employee time is directed toward other productive work, as represented by scaling factor 113 Process Goal Examples quantification of Improve system uptime Example: New diagnostic software is being deployed to identify problems with machinery within a factory. This is expected to reduce downtime, Calculation: Number of machines * reduction in length of outage (hours)* number of units produced per hour * revenue per unit Assumptions: Equipment is currently 100% utilized, so increased production due to decreased downtime is desirable. Process Goal Examples quantification of Provide better coordination among functional areas in your corporation Example: Set up of dedicated test servers / regions requires coordination of multiple groups such as DBA, system administrators, hardware support groups, messaging groups. A simple wiki based approach is proposed to reduce the need for multiple request forms, s and phone calls. Calculation: Number of tests conducted per year * time saved by consolidated information on a wiki page * adjusted hourly rate of staff * scaling factor. Assumption: Some fraction of saved employee time is directed toward other productive work, as represented by scaling factor Process Goal Reduce transaction costs by making it easier for suppliers to handle orders

129 Examples quantification of 114 Example: Electronic integration of internal ordering system with suppliers order fulfillment systems to reduce manual processing. Calculation: Number of orders placed * time saved by not manually processing * adjusted labor rate * scaling factor + Number of incorrect orders * (time per reorder + time in return processing) * adjusted labor rate.*scaling factor Assumptions: Some fraction of saved employee time is directed toward other productive work, as represented by scaling factor. Note: There may be additional benefits if reduction in incorrect orders results in more output due to having fewer delays due to needing to wait for materials to arrive. Process Goal Examples quantification of Reduce variance in supplier lead times Example: Electronic integration of internal ordering system with suppliers order fulfillment systems to reduce manual processing. Calculation: Increased number of units produced * revenue per unit Assumption: Erratic delivery of supplied was leading to lost production. Construction of products were delayed waiting for supplies. Process Goal Examples quantification of Enhance the ability to monitor the quality of products and services from suppliers Example: Deployment of automated testing software to test circuit boards prior to use in assembly of products. Calculation: Percentage of defective circuit boards * cost of rework per unit produced. Process Goal Examples quantification of Help to gain leverage over suppliers Example: A system supporting comparison of products and prices across suppliers could allow discounts to be negotiated. Calculations: Cost savings per input * number of inputs used per period. Process Goal Examples Help to coordinate closely with suppliers of Example: Electronic integration with supplies lowering

130 115 quantification transaction cost on orders and reduced time to supply resulting in lower inventory requirements Calculation: Savings per order * number of orders made Calculation: Dollar amount of reduction in inventory * cost of capital per period. Process Goal Examples quantification of Increase the level of production / Improve Employee Productivity Example: Automation of business process Calculation: Time saved per transaction (hours) * number of transactions * adjusted hourly rate of employees * scaling factor Assumptions: Some fraction of saved employee time is directed toward other productive work, as represented by scaling factor. Example: Automation of factory equipment Calculation: Increased number of units produced * revenue per unit Process Goal Examples quantification of Reduce the cost of materials Example: Ordering system integrated with suppliers Calculation: Percentage discount * total cost of orders per period. Assumption: Suppliers will offer a discount because of lower costs on their end. Process Goal Examples quantification of Retire system(s) Example: Implementation of new system allows retirement of old system(s) Calculation: Hardware Costs (Old System) Hardware Costs (New System) + (Full Time Equivalents (Old System) Full time Equivalents (New System) * Adjusted labor rate per year * years of service of new system. Assumptions: New system is less costly. Process Goal Examples quantification of Reduce waste / scrap Example: Factory automation reduces scrap / waste production

131 116 Calculation: Reduced disposal costs Process Goal Examples quantification of Reduced Headcount Example: Automation of business process Calculation: Number of headcount reduced * adjusted cost per period Calculation 2: Number of hours saved per day per employee / number of hours per work day * adjusted daily rate of pay * days in period * scaling factor Assumptions: Some fraction of saved employee time is directed toward other productive work, as represented by scaling factor. Process Goal Examples quantification of Reduce employee turnover Example: Improved access to information about employee benefits via new intranet site increases employee satisfaction and decreases employee turnover. Calculation: Total number of employees * reduction in turnover rate * training costs for new employee Assumption: Current employee headcount is required to support business and new employees face a significant learning curve. Process Goal Examples quantification of Improve system uptime Example: Better production monitoring software to minimize production outages. Calculation: reduction in down time (hrs) * units produced per hour. Assumption: Lost production time cannot be compensated for by unpaid overtime for employees or increased rate of production. Process Goal Examples quantification of Reduce days of inventory Example: Inventory control system supporting monitoring of actual inventory levels and allowing lower levels of inventory to be stored. Calculation: Reduced level of inventory (dollars) * cost of capital. Notes: Relevant for both reduction in supplies needed for

132 117 input and in inventory of finished product. Process Goal Examples quantification of Reduce rework Example: Automation of manual processes leads to lower error rates. Calculation: Number of defective units * cost of repair per unit Calculation 2: Number of defective units * (cost of manufacturing + cost of disposal) for unsalvageable units Calculation 3: Number of times process is run per day * reduction in error rate * process time (hrs) / number of hours per workday * adjusted daily labor rate * scaling factor. Assumptions: Some fraction of saved employee time is directed toward other productive work, as represented by scaling factor. Process Goal Examples quantification of Improve product / process quality Example: Automation of manual processes improving quality. Calculation: Increased customer reorder rate * revenue per unit Note: See reduce rework for additional examples Assumption: Higher quality products increase customer satisfaction leading to higher reorder rate. Process Goal Examples quantification of Reduce time to market Example: Deployment of better or integrated software development tools reduces time to market. Calculation: Assumptions: New tools do not become shelfware. Early entry into market leads to at least a temporary increase in market share. Process Goal Examples quantification of Reduce variance on products/service quality Note: See Improve product / process quality Assumption: Customers care about variance in quality as well as mean. Note 2: In some cases quality variance may be more significant than the mean quality. A small percentage of highly defective units (good mean quality with high variance) can change customer perceptions more than a large percentage

133 118 of slightly defective units (average mean quality with low variance) in some cases. Process Goal Examples quantification of Facilitate the tailoring of products/services to markets Example: System improvements allow production of customized output or customization of processes to better satisfy customers. Sample Calculation: Increased number of units sold * cost per unit. Process Goal Examples quantification of Reduce the cost of designing/developing new products or services Example: Integrated development tools Sample Calculation: Decrease in hours for design/development * adjusted hourly rate * scaling factor. Assumptions: Some fraction of saved employee time is directed toward other productive work, as represented by scaling factor. Process Goal Examples quantification of Provide support for identifying market trends via analytical tools Example: Statistical analysis system allows detection of market trends and allows greater investments in growing market segments. Sample calculation: Projected increase in sales * revenue per unit. Process Goal Examples quantification of Assist the firm in locating or serving new market Example: See Provide support for identifying trends via analytical tools Process Goal Examples quantification of Enhance the accuracy of sales forecasts Example: See Provide support for identifying market trends via analytical tools

134 Process Goal Examples quantification of 119 Increase firm s ability to anticipate customer needs Example: See Provide support for identifying market trends via analytical tools Process Goal Examples quantification of Track market responses to pricing strategies, discount strategies, promotions Example: See Provide support for identifying market trends via analytical tools Process Goal Examples quantification of Optimize existing markets Example 1: See Increase cross-selling Example 2: See Provide support for indentifying market tends via analytical tools Process Goal Examples quantification of Increase cross-selling Example: CRM (Customer Relationship Management) system allowing better cross selling, that is, the selling of other products to current customers of one of the firms products. Sample Calculation: Increased sales of product X to current customers of product Y * revenue per sale of X. Note: This increase can be determined in a pilot study comparing the results of sales staff with access to the CRM system to those without. Process Goal Examples quantification of Reduce days of receivables Example: New accounts receivable or billing system that allows increased collection rates, tracks missing or late payments to allow better collections and reduces errors in billing. Calculations: Number of days receipt of payment is earlier * amount received * interest rate for risk free investment Note: risk free interest rate is used to produce a conservative estimate of revenue.

135 Use of Process Measures Hubbard [63] presents valuable practical advice on how to perform process measures. The following approach is based on the techniques presented in that work. 1. Review the list of generic process goals presented in section Based on the requirements of the project being evaluated, identify relevant process goals. 2. Review the related process measures presented in section Initially to evaluate a project, estimates are needed. Single point estimates are particularly inaccurate. Estimates of upper and lower bounds are more accurate and more reasonable to use 3. Hubbard [63] suggests that estimators can be trained to produce good estimates of bounds. 4. A confidence interval is an estimate of a range in which is expected to contain a parameter [66]. A 50% confidence interval is a range that is expected to contain the parameter 50% of the time. 5. Estimates of the 10% and 90% confidence intervals should be obtained. As an example, suppose a business process is being automated to reduce headcount. The 10% confidence interval might be 10 headcount. This means that there is only 10% confidence that the true value of headcount savings will be 10 or less. The 90% confidence interval might be 2 headcount. This means that there is a 90% confidence that the true value of headcount savings will be 2 or less. A bounded estimate is produced. 6. Using the estimates from the confidence interval, one of the following approaches can be taken. a. Calculate the process measure using the 10% and 90% estimates. An average of the two can be used or the lower estimate can be used as a worst case estimate. b. A Monte Carlo simulation can be done. i. A distribution must be assumed. For many processes, Gaussian or uniform distributions are appropriate 4. ii. Using the 10% and 90% confidence intervals and the assumed distribution, Monte Carlo simulations can be performed. 3 Validation of this statement by a review of literature or by empirical study is beyond the scope of this work, but based on personal experience it is likely true. 4 The correct choice of a distribution is significant to producing correct results, but it is beyond the scope of this work.

136 iii. Monte Carlo simulations are very useful to understand the total benefits from several independent sources (independent random variables). 7. The benefit estimates from step 6 can be used as input into the financial measures covered in this chapter Example of Approach Suppose a firm is automating its billing process. The current process for invoicing customers is manual and time consuming. Clerks manually prepare each individual invoice. Clerks perform multiple duties each day; only part of their day is spent preparing invoices. A software project is being evaluated to automate this process. A quantification of expected benefits is needed to justify the cost of the project. 1. After a review of 4.5.2, the benefits of this project are most likely derived from improved employee productivity. 2. From section 4.5.3, the following measurement is suggested: Time saved per transaction (hours) * number of transactions * adjusted hourly pay rate of employees * scaling factor a. The average number of invoices prepared per day is a quantity that can be accurate determined from corporate records. Assume it is 300 per day for this example. b. The current time spent preparing each invoice manually can be measured by observation of the current process. Assume it is ½ hour. c. The average adjusted hour pay rate for clerks is known. Adjusted means that is considers the costs of all benefits, not just salary. Assume it is $20 per hour. d. Since only part of each clerks day is spent doing productive work, all time savings from automation will not be directed toward other productive work. Clerks may not use all time savings productively. Assume only 50% of the time savings will be redirected toward productive work. e. An estimate must be done of the time to prepare an invoice using the new system. Assume the 10% confidence interval is 5 minutes (1/12 hour)

137 and the 90% confidence interval is 10 minutes (1/6 hour). There is 10% confidence that the invoices can be prepared in 5 minutes or less using the new system. 90% confidence that invoices can be prepared in 10 minutes or less using the new system. f. Translating the estimates: There is a 10% confidence that the time savings will be = 20 minutes per invoice. There is a 90% confidence that the time savings will be at least 30 5 = 25 minutes per invoice. 3. Calculation of financial benefit lower and upper bounds, average Lower bound: 20/60 hours/transactions * 300 transactions/day * 1 day/8 hours * $20/hour * 0.5 = $125 saved/hour = $1000/day Upper bound: 25/60 hours/transactions * 300 transactions/day * 1 day/8 hours * $20/hour * 0.5 = $ saved/hour = $1250/day Average: ( )/2 = 1125 saved/day = /year based on a 220 day year. 4. A NPV calculation can be performed to evaluate whether the automation project should be done. Assume the following: a. The risk free interest rate is 5% per year or % per day. The appropriate discount rate for projects of this nature and risk is 15% per year or % per day. b. Cost estimates for the project are $ Assume this will be paid evenly over six months. This cost will be distributed over 6 months of calendar days to simplify the NPV calculation even though cost may actually occur on business days only /183 days = 2732/day. c. The savings of 1125/business day (assume there are 220 business days per year) will begin in 6 months and will continue for five years after which the system will need to be retired and replaced. Since the yearly savings are , to make the NPV calculation more tractable without special software, assume the benefits are /365 = 685 per calendar day. Benefits start in day 184 and continue to day 2009, five years later. 122 Equation 39 NPV Calculation for Process Measurement Example

138 123 NPV = = d. Given the large positive NPV, the project is worth conducting. Some of the simplifications done, such as working in calendar days rather than business days and rounding some intermediate numbers will not impact this result that the project should be done. The NPV is large enough that even errors due to these simplifications, the true NPV will also be positive. 5. A Monte Carlo simulation can be done to show the range of possible benefits. 4.6 Discussion Discounted cash flow/npv analysis suffers from a major flaw. Each project is evaluated without regard to managerial flexibility. It is assumed that the entire project will be conducted exactly as planned and exactly when planned. There is no consideration of modifying the course of the project as more information is revealed or as events unfold. Simple examples of this include the ability to expand or contract the project, delay the project or even cancel based on how events unfold. NPV techniques tend to undervalue projects. The flexibility to limit losses or take advantage of opportunities increases the value of projects. NPV/discounted cash flow techniques look at project value in terms of an absolute number. IRR reduces value to an interest rate. Payback period reduces value to a time period. All three can be combined to get an understanding of project value. They are three views into the same set of numbers. Decision trees incorporate managerial choices, but are deficient in several aspects. First, as the number of decision points grows, they quickly become unmanageable with more

139 124 and more branches to keep track of. A second deficiency is that it necessary to estimate probabilities of possible outcomes. The trees require information such as a 0.25 chance of one cash flow and a 0.75 chance of another. At best, these probabilities are estimates. At worst, they are guesses. A third, more subtle, flaw in decision tree analysis is that typically the same discount rate is used for all branches. Whether nature is friendly and the best possible outcomes occur, for instance, the maximum cash flows are achieved or nature is against us, the same discount rate is used. This is equivalent to assuming that project risk is unchanged even though as more information is uncovered, project risk changes. Real options are a technique where the mathematics of financial options is applied to the valuation of projects and capital asset investments. This analysis helps management decide whether there is value in delay, expansion, contraction or abandonment of the project. Real option techniques capture the value of flexibility, the value of changing the course of the project based on additional information as it progresses. One fault in real option approaches is that they only examine the project by itself. The effects of the outside world and particularly of competitors are not included. Game theory provides means to reason about competitors and about competition in the market. It is relevant for large strategic types of projects such as entering new markets, new businesses or introducing entirely new products. Process measures were seen as a means to quantify financial value in internal projects which ultimately allows application of the financial techniques described in this chapter to be used on both projects producing a product for sale and for internal projects.

140 Strengths and limitations of these approaches are listed in Table 23. The strengths and limitations listed are based on [67] [68] [69] [70]. 125 Table 23 Strengths and Limitations of Financial Valuation Techniques Financial Valuation Technique Net Present Value Internal Rate of Return Payback Period Strengths Easy Calculation Quantifies benefit of project as a single absolute number (profit). Considers time value of money. Considers risk (via discount rate). Easy Calculation Considers time value of money. Easy to understood (simple percentage) Consideration of time. Easy to understand. Implicit consideration of risk (Favoring quick payback lowers risk). Real Options Considers managerial flexibility. Realistic valuations of risky or uncertain projects. Limitations Length of time not considered. Rate of return not considered. No accounting for managerial flexibility. No consideration of market or competitors. Under values risky projects (by not considering flexibility) Length of time not considered. Risk not explicitly considered. No accounting for managerial flexibility. Under values risky projects (by not considering flexibility). No consideration of market or competitors. No consideration of absolute amount. Ignores revenues after payback period. Considers only time, not absolute amount or percentages. No accounting for managerial flexibility. No consideration of market or competitors. Complex calculations. Difficult to understand. No consideration of market or competitors.

141 Game Theory Approaches Captures value of delaying until uncertainty is resolved. Considers competition and market factors. Captures value of early entry into competitive markets. 126 Very difficult to fully understand markets and to predict the actions of competitors. Only applies for strategic projects where competitors exist and matter. The applicability of these techniques is to a large extent driven by the nature of the project. This is illustrated below in Figure 24.

142 127 Proposed Project Is this a large strategic project where an understanding of competitors and the market is crucial? Yes Use Game Theory Approaches No Is there uncertainty about future cash flows or flexibility to chance course based on events? Yes Use Real Option Analysis No Use Basic Financial Measures (NPV, IRR, payback period) Figure 24 Impact of Nature of Project on Selection of Financial Measures

143 128 Chapter 5 Qualitative Approaches to the Measurement of Value 5.1 Overview The techniques discussed in section 3.3 and Chapter 4 suffer from a common defect. They examine each project independently. Each project was evaluated as if there were unlimited access to capital and resources, as if there were no conflicts with other projects or with respect to corporate strategy and is if there was no overlap or synergy with other projects. The value of each project was evaluated independently. There is uncertainty in quantitative measures. Costs and revenues are uncertain. How markets will develop is uncertain. Projects have multiple objectives, dependencies on other efforts and it is often unclear how to measure benefits [71]. Stakeholders value propositions and utility functions vary. Qualitative measures can compensate for a lack of confidence in financial measures such as ROI. [72] The financial analysis techniques evaluated whether each project increased the wealth of the firm, that is, whether it had positive net present value. If it is assumed there is unlimited access to capital for projects, should all projects with positive NPV be conducted? No. Even with unlimited capital (money), other resources are limited. There are limits on the number of available skilled employees. Attempting to increase the number of resources available beyond some limit is difficult and probably unwise. The labor pool limits the number of potential resources. And even if the labor pool was unlimited, there are limits to the number of new resources that can be successfully integrated in a given time frame.

144 Suppose there is sufficient capital and other resources, should all projects with positive NPV be conducted? No. 129 There are possible conflicts with the goals and requirements of other projects. The techniques explored in section 3.2 looked at ways to determine and satisfy stakeholder value propositions of stakeholders of a single project. The imperfect knowledge of the stakeholders of an individual project about other efforts the firm is conducting leads to the possibility of conflicts between projects and of lost opportunity for synergy due to overlap between projects. Even if it is assumed that an extraordinarily job was done in requirements, that all potential stakeholders have been included, that all conflicts and overlap with other projects have been uncovered and accounted for, that all capital and resources are unlimited, should all projects with positive NPV be conducted? No. At the core, the project may be at conflict with overall corporate strategies. Microsoft could conceivably conduct profitable projects to produce crackers, sardines and toy guns. These are probably unaligned with corporate goals and strategy. Given that a firm can t and shouldn t conduct every profitably project, which should be conducted, how should the success of those projects be measured and how should those projects be monitored and controlled to achieve success. Balanced score card techniques are considered in section 5.2 as a way to analyze project alignment with corporate strategy. Project portfolio techniques are considered in section 5.3 as a means of evaluating project conflicts and synergies with other projects. 5.2 Balanced Score Cards Introduction Financial measures, while critical in measuring value at the project, program and overall corporate level, cannot alone guide an organization toward its strategic goals. Financial measures have limitations. First, they tend to be backward looking or lagging. That is,

145 130 they are a measure of what has occurred, not what can be achieved or how additional value can be created. A second criticism is that there is no explicit linkage between financial measures and the corporation s strategic goals and that there is no linkage between the financial measures and strategic goals with operational changes and with programs and projects. The balances scorecard provides a framework to map the organizations strategic goals into concrete measures and to link those measures to individual projects. The balanced scorecard is a technique that allows modeling, measurement and understanding of financial measures to be combined with measures of value in other dimensions. It provides a concise summary of value along several dimensions. By considering value along several dimensions, certain types of sub-optimizations are avoided. A simple example is that of achieving an objective of reducing time to market. Within the software industry this could conceivably be achieved by lowering quality standards. Thus, reduced time to market could be achieved at the expense of other goals such as customer satisfaction or having a loyal customer base for future products. This can be summarized by Even the best objective can be achieved badly [73] Traditional Balanced Scorecards The balanced scorecard technique as developed by Kaplan and Norton [73] measures performance along four dimensions or perspectives. Measures, sometimes referred to as key performance indicators, KPIs, are developed to understand performance in each perspective:

146 131 Financial Perspective Customer Perspective Internal Business Perspective Innovation and Learning Perspective The customer perspective is an external view of the organization. What do customers think about the organization; what do they value? A key point here is that source of value and its measurement is defined by the customer. It is what they value and should be determined by them, not internally. The sources of value can be identified via surveys and via feedback from external parties. Measurement of value in this perspective should also be done externally, either by the customer directly, or via a third party evaluations by government agencies or external third parties, such as industry groups or companies such as JD Powers or Gartner who specialize in producing comparative measurements of performance. Having the customer define value is analogous to requirements engineering techniques that look to identify all stakeholders and have them define their requirements. The internal business perspective looks at current processes and their measures. Broadly, this perspective can be divided between processes whose aim is achieving customer satisfaction and core competencies. Core competencies for an organization might include design and manufacturing. For software organizations manufacturing competency could be seen as the ability to produce high quality, low defect software. The innovation and learning perspective looks at measures of how well the organization expands its capabilities and those of its employees. Long term, the only way that an organization can grow is to launch new products and expand into new markets. This

147 perspective measures the organization s processes that support this expansion by improving staff. 132 It is interesting to note that the perspectives have different temporal focuses. The financial perspective measures how well the organization has done. The customer and internal business perspectives examine the present time; how well customer needs are currently being met and how well the organization is currently functioning. The innovation and learning perspective looks forward at how the company is organizing to achieve longer term strategic goals and to expand. The financial perspective, as stated earlier, is really a backward look at how the company has performed with respect to the bottom line. But, it serves a critical purpose. It provides a reality check on the other three perspectives. The customer, internal business and innovation and learning perspectives in some sense are hypotheses. The ultimate goal of the business is financial success; the achievement of increased value for stakeholders. The success of any initiative in the other dimensions is ultimately measured in the financial perspective. Kaplan [73] notes the hard truth is that if improved performance fails to be reflected in the bottom line, executives should reexamine the basic assumptions of their strategy and mission. Not all long term strategies are profitable strategies. A key benefit of balanced scorecard approaches is that they provide a framework for explicit linking between operations and finance. The act of modeling, of creating balanced scorecards can add value as consideration is given as to how initiatives and projects in the other dimensions translate into performance in the financial perspective.

148 Linking Strategy to Measures The relationship between measures and strategy can be seen as bidirectional. The balanced scorecard can be seen as a set of measures that indicate progress toward a strategy. Looking in the other direction, an interesting observation is that people are motivated and influenced by the measurements made. The measures themselves influence performance. Carefully selected measures can guide the organization toward completion of its strategic objectives. The taking of measurements establishes goals for individual employees and can guide performance. The balanced scorecard displays a set of measurements. An implicit assumption is that there is a causal relationship between the measurements and successful implementation of the strategies they support. For instance, suppose a software company selling shrink wrapped software to retail customers has a strategic objective to increase profit. Assume that higher sales will increase profit. Sales can be measured in terms of number of units sold. Assume that reducing the defect rates will increase customer satisfaction and ultimately increase sales. The operational measure of defect rate is a measure supporting the strategic objective of increased sales. Defect rates can be measured in defects per thousand lines of code. Customer satisfaction can be measured (subjectively) using surveys and a numeric scale. The next question becomes how a lower defect rate can be obtained. Assume that developer education can achieve this. That is, developer education causes a lower defect rate. Developer education could be measured in hours of training per developer. The causal relationships, measurements and perspectives can be summarized as follows. Strategic Objective: Increased sales (Financial Perspective)

149 134 Table 24 Causal Relationships Supporting Strategic Objective of Increased Sales Relationship Measurement Perspective Better educated developers Hours of training per Innovation and Learning produce code with fewer employee Perspective defects Fewer defects increase Customer surveys Customer perspective customer satisfaction More satisfied customers will purchase more software Number of units sold Financial Perspective Here we see three measures supporting one objective. Further analysis might indicate that a better defined software process will lead to fewer defects in code. Process can be measured via internal software quality assurance audits. Table 25 Additional Measure Supporting Strategic Objective of Increased Sales Relationship Measurement Perspective Better process produces Percentage of processes Internal software with fewer defects followed as measured in SQA audits perspective business The process of finding measures may lead to more strategic objectives. For instance, increased customer satisfaction might be another strategic objective. Following along the lines of the above analysis, a simple balanced scorecard can be drawn. Financial Perspective Business Process Perspective Strategic Objective: Increase Profit Measures: Total revenue Total costs Number of units sold Strategic Objective: Better Quality Code Measures: Defect rate (defects per KLOC) SQA Audit results (percent compliance)

150 135 Customer Perspective Innovation and Learning Perspective Strategic Objective: satisfaction Higher customer Strategic Objective: Better trained staff Measures: Training hours per employee Measures: Customer surveys Figure 25 Organizational Balanced Scorecard Example This process also shows the benefits of modeling. The process of finding causal relationships and trying to form hypothesis between operational changes (such as training) and achievement of strategic objects (which can also be called goals) lead to the discovery of more strategic objectives and iteratively leads to more measures. Measurements, also known as indicators, can be leading or lagging. Leading indicators are indicators that show changes before the strategic objective is obtained. For instance, a lower defect rate would be seen in advance of increased customer satisfaction. Leading indicators are also called performance drivers. The act of measuring defect rate will encourage developers to test more carefully (perhaps). Leading indicators also give early feedback on the success or lack of success toward achieving strategic goals. Lagging indicators are measurements of the achievement of the strategic objective. Lagging indicators are also referred to as outcome measures. For instance, total revenue and total cost are direct measures of profit (neglecting the intricacies of accounting and tax codes). A successful balanced score card will have both leading and lagging measures. Outcome measures without associated performance drivers do not show how the outcome will be achieved. For instance, for the outcome measure of defect rate, associated performance driving measures such as measures of staff education or measures of use of

151 testing tools must be established. Without them, the outcome measure may not be achieved. [74] [75]. 136 Performance drivers not linked to outcome measures have no demonstration of value. For instance, measurements of staff education will drive line level managers to arrange training for staff. Without a causal link to an outcome measure such as higher productivity, lower defect rate or higher staff retention, the value of this training cannot be established [73] [75] Balanced IT Scorecards The example developed in the previous section described applying a traditional balanced scorecard approach to a company whose business was primarily producing software for purchase. A more common case is that of an organization that engages in a business other than software, but has internal groups dedicated to producing specialized software to support the organizations business. In this case, the business has overall strategies and goals that are not focused on software but are instead focused on goals for the overall business. The internal software groups with the larger organization serve to support and enable overall business strategies. Similar to the way the software group can be thought of as enabling the larger organization to achieve its strategy, it s possible to construct an IT specific balanced scorecard that can be shown to enable the strategies of a traditional balanced scorecard and thus the strategies of the larger organization [75] [76]. Grembergen describes a hierarchy of scorecards with the lower levels supporting or enabling higher levels. From [75]:

152 137 IT Development Balanced Scorecard Business Balanced Scorecard IT Strategic Balanced Scorecard IT Operational Balanced Scorecard Figure 26 Balanced Scorecard Cascade [75] In [75], a case study of the application of this approach as used by a group of Canadian insurance companies is presented. This example is presented below as an illustration of this technique. The first step in this process is to establish who the key stakeholders are and their value propositions. This is expressed in [75] by considering the key questions each stakeholder group would ask to determine satisfaction of their value propositions. From [75]: Stakeholders Key Questions Board of Directors Executive Management Committee What value does IT deliver? Does IT enable or retard business goal achievement? Does IT advance organizational innovation and learning? Is IT well managed? Line of Business Management Are we getting value for our IT

153 Customers (internal users) investments? How does IT influence the customer experience? Does IT favorably affect productivity? Is IT positioning the group (line of business) for future market demands? Audit and Regulatory Are the organization s assets and operations protected? Are the key business and technology risks being managed? Are proper processes and controls in place? IT Organization Are we doing the right things for the business and employees? Are we effective and efficient? Where do we need to improve to meet our goals? Have we satisfied all key stakeholder interests? Can we attract/retain the talent we need to meet business needs? Are we fostering a culture of innovation and learning? 138 To address these questions an IT balanced scorecard was established. Its objectives were to demonstrate the value added by IT, link operational plans to IT strategic goals (as with any balanced scorecard), and establish, communicate and report measures of IT effectiveness. From [75], the following IT balanced scorecard was established. CUSTOMER ORIENTATION Perspective question How should IT appear to internal customers (end users and division managers)? Mission To be the supplier of choice for all information services, either directly or indirectly through supplier partnership. Objectives Customer satisfaction CORPORATE CONTRIBUTION Perspective question How should IT appear to the executive committees and Boards in order to be considered a significant contributor to company success? Mission To enable and contribute to the achievement of business strategies through the effective application of information technologies and methods.

154 139 IT/business partnership Application development performance Service level performance OPERATIONAL EXCELLENCE Perspective question At which services and processes must IT excel to satisfy the stakeholders and customers? Mission To deliver timely and effective IT services at targeted service levels and costs. Objectives Process excellence Responsiveness Backlog management and aging Security and safety Objectives Strategic Contributions Synergy achievement Business value of IT projects Management of IT investments FUTURE ORIENTATION Perspective question How will IT develop the ability to change and improve in order to better achieve the IT and company vision? Mission To develop the internal capabilities to learn and innovate and to exploit future opportunities Objectives Service capability improvement Staff management effectiveness Enterprise architecture evolution Emerging technology research Sets of measures, not reproduced here, were established to determine satisfaction of the objectives listed above. As noted earlier, both leading and lagging measures are needed. The key observation is that this balanced scorecard has components that are specific to the IT group, those listed in the operational and future orientation. Additionally, there is a linkage to higher level organization strategies. The satisfaction of the needs of the supported lines of business is addressed through the customer orientation. The linkage to overall corporate strategies is made through the corporate contribution perspective Corporate Governance In [77], an application of the balanced IT scorecard approach to achieving corporate governance is presented. Corporate governance is a set of procedures and policies established to direct activities toward satisfying the goals of shareholders (primarily,

155 140 wealth creation). It is an attempt to address the agency problem, where the goals of internal parties within the corporation may conflict with the goals of the owners (shareholders). Shleifer [78] defines corporate governance as: Corporate governance deals with the ways in which suppliers of finance to corporations (shareholders) assure themselves of getting a return on their investment. How do the suppliers of finance get managers to return some of the profits to them? How do they make sure that managers do not steal the capital they supply or invest it in bad projects? How do suppliers of finance control managers? A balanced IT scorecard approach can link IT strategies and objectives back to the overall corporate strategy. The overall corporate strategy includes a financial perspective that represents the interests of investors. Balanced scorecards can drive both IT and business groups through performance drivers (measurement that serve as leading indicators) and can report performance through output measures (lagging indicators). In this manner there is assurance that the IT organization returns some business value and does not invest in bad projects and in the adequacy of IT controls [77]. IT governance can also be achieved through project portfolio management. 5.3 Project Portfolio Management / IT Governance A portfolio is a collection of projects and programs or other work that are grouped together to facilitate effective management of that work to meet strategic business objectives. The projects or programs of the portfolio may not necessarily be interdependent or directly related [4]. The portfolio exists to achieve strategic goals and

156 consists of both planned and in progress projects and programs. A program is a 141 collection of supporting projects to achieve some business goals. In this section, project will be used to indicate either a project or program. The challenge of portfolio management is twofold: Select projects that are aligned with the strategic goals of the organization and optimize financial value subject to resource and time constraints Monitor and control the selected projects to successful completion. This includes the possibility of terminating projects that are failing due to poor requirements or failures in technology selections. The goal of portfolio management is to ensure that the organization is doing the right work rather than doing work right [79]. Doing work right is addressed by project management. As such, the focus is on prioritization and selection of projects, project governance and tracking and control of projects. Weill [80] makes the observation that for portfolio management to be effective, all (IT) investments and expenditures must be included. Weill presents an analogy to a personal investment portfolio where only new investments are considered, but on-going costs such as mortgage payments are not. In a similar way, both lights-on on-going maintenance and infrastructure costs and costs for new development must be considered in a project portfolio. Project portfolio management is a means to achieve corporate or IT governance as described in section For the purposes of this thesis, project portfolio management is defined as a set of process to evaluate, select, prioritize and monitor potential and in progress projects. Key points include [81]:

157 Aligning the portfolio with corporate strategies Optimal allocation of capital Optimal allocation of resources Risk management, particular focused on risks to achieving strategic goals Measuring component contributions. That is, measuring the projects within the portfolio against the other goals Portfolio management can be seen as a framework within which to conduct the valuation activities explored in other parts of this thesis. Critical is that it also provides a means to track and measure achievement of value and to provide feedback into making better 142 measures of value in the future. This can be done by carefully measuring actual achievement of value and comparing it with estimates. The portfolio management process assesses and monitors projects against multiple criteria to ensure that maintain alignment with strategic and business goals and that only projects that contribute to the organizations success will be funded [82]. 5.4 Alignment with Organization Strategies and with IT Goals and Architecture The organizational balanced scorecard, section 5.2.2, and the IT balanced scorecard, section 5.2.4, concisely list the goals and measures of those goals for overall organization and for the IT department or group respectively. Much of the available literature is focused on using balanced scored cards to rate the organization s level achievement of the goals expressed and to drive the organization towards achievement of those goals. Little work is found in the literature on measuring individual project level requirements and goals against the higher organization level goals expressed by balanced scorecard techniques. Studies of techniques for ranking and aligning individual projects against the goals in organizational and IT balanced scorecards would be a direction for future

158 143 research. For purposes of this thesis, it is proposed that each project be rated against a list of measures from the organizational balanced scorecard and against a list of measures from the IT balanced scorecard. Against each measure a project can be rated as not-aligned (0), low alignment (1), medium alignment (2) or well aligned (4). A numeric average of against all measures can be used as the alignment for the project. An example of this technique is shown in section 3.3 for project critical success factors. 5.5 Discussion A project s alignment with the goals of the organization and with the goals and enterprise architecture of the IT group within the organization are seen as additional factors in determining the value of the project. A survey of the literature found little guidance on how to relate projects to the higher level goals of the organization and to those of the IT group. As this is a key factor in project valuation, it would be a useful direction for additional research. Use of these factors in the ranking and selection of projects is given in Chapter 6 and Chapter 7.

159 144 Chapter 6 A Proposed Multi-Dimensional Framework for Project Valuation 6.1 Introduction Current practice typically fails to perform adequate valuation of software projects. Techniques such as the earned value technique measure cost rather than value. When valuation techniques are attempted, only limited dimensions, such as the financial value of the project are considered. The valuation of projects must be done in multiple dimensions using both quantitative and qualitative techniques. Qualitative evaluation can be done along several dimensions including alignment with overall corporate strategies, alignment with enterprise architecture / IT strategies and against factors associated with project success or failure. Corporate and IT strategies can be expressed using balanced scorecard techniques as seen in section 5.2. Projects can also be evaluated against project success factors seen in section 3.3. Quantitative (financial) techniques are described in section Chapter 4. In that chapter, the basic techniques were presented with a focus on commercial projects with a marketable product. These techniques were extended to include a quantification of benefits for projects that are strictly internal to the organization using process measures. Time is a significant additional dimension. Projects need to be reevaluated at multiple points in their life cycle. At project initiation, a go/no-go decision is made based on the high level project scope and benefits described in a business case or alternatively with a simple project request. After application of good requirements techniques, several of which are described within section 3.2, more of the cost and benefits of a particular

160 145 project are understood and known. At that time, it is appropriate to revisit the business case, make updates based on the latest information and to reevaluate whether to proceed with the project. In a similar way, project valuation should be done after all significant stages in the projects life. The business case should be updated and reevaluated after an initial design is completed, after completion of coding and testing of an initial version of the product and when the product is ready for deployment. This approach is sometimes referred to as establishing toll gates or stage gates. At defined points in its life cycle the project must past toll gates in order to maintain funding to continue. The process framework required to evaluate projects relative to each other and against predefined yardsticks is the domain of portfolio management. A defined repeatable process, as prescribed by portfolio management techniques, is an essential element of project valuation. Portfolio management was examined in section 5.3. Additionally, although rarely done, post deployment and throughout the operational life of the product, the actual benefits and maintenance costs should be tracked to allow feedback into the evaluation and portfolio processes. Without feedback using actual measurements, process improvement attempts are at best guesses. This feedback can be incorporated as part of a portfolio management process.

161 Overview of the Framework The proposed framework for project valuation evaluates projects along multiple dimensions Portfolio Based Approach The proposed framework uses a portfolio based approach. Multiple portfolios are established and funded based on the type of firm and the goals of the firm. Each receives a percentage of the total available funding. Firms can direct investments by varying the percentage each portfolio receives of the total funding. Each project is ranked and evaluated against others within the same portfolio Quantitative (Financial) Measures The choice of inputs into financial measures and the types of uncertainties present are dependent on the project s supplier and customer and on the nature of the project. Internal projects use process measures to determine future revenues or cash flows. External projects depend on sales and marketing forecasts Qualitative Measures Projects have different value for different stakeholders. Each stakeholder has their own sources and measures of utility. Additionally, there is always uncertainty and potential errors in quantitative calculations. Due to these factors, it is important to consider qualitative measures such as alignment with the firm s strategic goals and IT goals and architecture. Evaluation against project critical success factors can be seen as a measure of the risk that the project will not be successful.

162 Iterative Nature of the Process Valuation should be redone as the project progresses. More details are understood and uncertainties are resolved. At various points in the life of the project, it should be reevaluated and should continue only if it is still attractive relative to other potential work. Post completion assessment of the project should also be done to evaluate the accuracy of the valuation process. This is an important part of potential process improvements. 6.3 Project Evaluation Framework The proposed project evaluation framework is shown below in Figure 27. It is described in section 6.4.

163 148 Type of Firm (section 6.8) Strategic Goals of Organization (section 5.2) Proposed Project Determine portfolios and relative funding of each portfolio (section 6.3) Determine type of project and relevant portfolio (Section 7.6.3) Understand Perspective of Project (section 6.3) Cost Estimates for Project Is Project for External Sale? Yes Estimates of maintenance and support costs No Process Measures (Chapter 3.3) Sales or Marketing Forecasts Evaluate with respect to Critical Success Factors (Section 3.3) Evaluate with respect to Organization s Strategic Goals (Section 5.4) Evaluate with respect to IT Goals and Architecture (Section 5.4) Financial Measures (Chapter 4) Determine Nature of Project. Select Relevant Financial Measures (Figure 24) Yes Is Project within Investment Boundary? (section 6.9) No Don t Conduct Project Rank project against other potential projects within its portfolio Track success of project against financial measures, success factors, organization goals and IT goals At Project End or Cancellation, measure success against Project Evaluation with respect to Organization and IT Goals. No Yes End Project? Process Improvement Efforts Figure 27 Project Evaluation Framework

164 Project Valuation Process 0) The establishment of separate portfolios for different classes of projects is necessary as a precursor to the process. The funding and establishment of different portfolios are influenced by the type of firm (section 6.8) and by the strategic goals of the organization (section 5.2). 1) The first step in the process is to classify the project into one of the established portfolios. Project portfolios are discussed in section 6.7 and a proposed set of portfolios is given in section ) It is necessary to understand the perspective of the project. It is being evaluated by an organization supplying software or an organization purchasing software. Is the product for sale or internal use? If for sale, is it for the general market or a particular customer. The approach for the quantitative valuation of projects producing software products for sale in the general market or to particular customers is fundamentally different from the quantitative valuation of projects producing software products for internal use by the firm. These key distinctions determine what measures serve as inputs into the calculation of value. The perspective is seen as determining the relevant inputs into quantitative calculations. (see section 6.5) 3) The choice of which financial calculations apply is dependent on the nature of the project. If it is strategic in nature and dependent on external markets and competition then game theory approaches may be useful. If there are uncertainties or if there is flexibility, then option techniques can be applied. For projects addressing internal needs with more certain scope and benefits, basic financial measures are applicable. The nature of the project is seen as determining the type of relevant quantitative calculations. See Figure 24 and section 4.6. There is also a dependency on the perspective of the project. See section ) The quantitative (financial) valuation can be compared against the investment boundary. If the risk is unacceptable for the level of return, the project should simply be rejected. See section ) Financial measures of a project are simply one dimension of its evaluation. Other dimensions, more subjective in nature, are also significant. Other dimensions include strategic alignment with organization goals (section 5.4), alignment with IT goals and architecture (section 5.4) and chance of project success based on critical success factors (section 3.3). Also see section 6.6. a. The strategic goals of the organization can be expressed using a balanced scorecard. b. The goals of the IT department and enterprise architectural can also be expressed via a balanced scorecard approach.

165 150 c. Evaluation can be done against lists of project critical success factors. d. These evaluations can be done with simple ranking schemes. 6) Each project should be ranked against other potential projects within the same portfolio by combining quantitative and qualitative evaluations. The relative significance of each dimension of evaluation would need to be evaluated empirically. 7) Projects may be ranked by presenting data within a simple table or visually. Assuming that a project portfolio approach is taken, projects are classified by type into a particular portfolio. Within each portfolio projects are relatively ranked. For visual representation of project data, bubble plots can be used. Bubble plots as a valuation technique are presented in [83]. One possible visualization scheme is to represent project financial return, for instance, ROI or NPV, as the size of the bubble on these plots. Project risk can be represented as the color of the bubble. Higher risk projects will appear as red, medium risk projects will appear as amber, low risk projects will appear as green. The mapping of risks to these colors will be dependent on project type. The axes of the bubble plots can be chosen to represent either alignment with the organizations goals, alignment with IT goals and enterprise architecture, satisfaction of project critical success factors and project urgency/timeliness. The dimension of urgency/timeliness can be used to represent the delay in conducting the project. Some projects may address opportunities that vanish if not addressed quickly. Two of these dimensions can be examined at a time in a single bubble plot. By plotting different dimensions, different perspectives of project value can be obtained. 8) Projects should be reevaluated as they progress. Based on this reevaluation, they may continue or be cancelled. 9) Metrics collected during and after the project can serve a role in process improvement efforts. 6.5 Effect of Supplier and Customer Types The complicated nature of the task of project valuation can be simplified by categorizing projects and by understanding the organizations involved in producing and consuming software. Certain valuation techniques will be seen as more applicable to certain classes

166 151 of projects. At the highest level, the first aspect that must be understood is that value is dependent on perspective. The value of a project for the developing organization or supplier is distinct from that of the customer organization. Any attempt to measure value must begin by answering value for whom?. With respect to the supplier, two classes are readily apparent: external supplier and internal supplier. An external supplier is an outside organization seeking to sell software and services to customer firms. An internal supplier is department or group within the firm. Who is the supplier? External Firm Internal Group or Department Figure 28 Supplier Types The value proposition of an external supplier is potentially conflicting to those of the customer. The supplier will rationally seek to maximize its obtained value by seeking the optimum combination of number of sales and revenue per sale without regard to the value sought or obtained by the customer. Value is delivered to the customer only as a byproduct of the supplier s desire to establish repeat business, desire to improve reputation and good will to obtain other customers or as a contractual obligation. Win-

167 Win techniques, described in section 3.2.4, attempt to address this conflict by establishing conditions where the value proposition of supplier and customer become 152 aligned. It is unclear whether or when Win-Win approaches involving multiple organizations result in more value obtainment for each involved party or whether more value is ultimately obtained when each party selfishly seeks its own goals. For the supplier, this points to a choice between establishing long-term mutually beneficial relationships with customers and trying to maximize revenue and profit without regard to particular customers. For the customer, this points to a choice between tough negotiations techniques to establish lower costs or the establishment of long term mutually beneficial relationships with suppliers at potentially higher costs, but with more value or benefits. Establishing the validity of Win-Win approaches is beyond the scope of this work. The goals of internal software development groups and those of their customers, internal business groups ideally are better aligned. Both should seek to maximize value for the owners of the firm. This can be achieved by systematic valuation of projects and relative evaluation of projects through portfolio techniques. Internal groups, both software development groups and business groups, can, of course, have value propositions that differ from the goal of maximizing value for the firm. This is known as the agency problem. Although not investigated within this thesis, the agency problem is a common problem in many human endeavors. The personal goals of individuals can conflict with those of the wider organization they are employed to serve. Ideally, incentive schemes can be used to align personal and organizational goals.

168 153 With respect to the customer, a distinction is seen between IT projects aimed at producing a commercial product for sale, designated here using the somewhat dated term shrink-wrapped, commercial products built on contract (bespoke software) and software built for internal use by the firm. The first key question is who the ultimate customer is: the general marketplace, a specific customer or an internal business group within the firm. Who is the customer? General Public Single or small number of customers Business Group within the firm Shrink Wrap Bespoke Internal Figure 29 Customer Types The combination of types of suppliers and types of customers leads to Table 26. The perspective column indicates from whose perspective project value is evaluated. For instance, consider video games (shrink wrap project type). For the supplier, that is, the firm that designs, develops and markets the game, the potential value is based on

169 154 complex estimates of production costs and forecasts of future sales and revenues. For the customer, the potential value of the game is based on a known cost, the purchase price, and a benefit equal to the very personal subjective evaluation of the entertainment provided by the game. It should be noted that in the general case, for most other types of shrink wrap projects, the value from the customer s perspective can be measured by process measures (section 4.5). Table 26 Supplier-Customer Type Summary Supplier Type Customer Type Project Type Perspective Inputs to Financial Value Calculation External General Public Shrink Wrap Supplier Inputs: Cost Supplier estimates, sales and revenue External Supplier External Supplier External Supplier Internal Supplier forecasts. General Public Shrink Wrap Customer Inputs: Cost of software, process measures. Single or small Bespoke Supplier Inputs: Cost number of estimates, customers terms of contracts Single or small Bespoke Customer Input: Cost of number of contract, customers process measures Internal Customer Internal Firm Input: Cost estimates, process measures The inputs to calculations, those for costs and revenues, for financial measures of value are seen to vary in the above table. The basic calculations remain as shown in the

170 155 financial methods of Chapter 4. In the above table, in the internal customer/internal supplier case, both the internal supplier, an IT group or department, and the internal customer, a business group are assumed to have the firm s goals. Agency problems can exist in firms, but are assumed resolved for the purposes of this section Shrink Wrap Projects (Supplier s Perspective) Shrink wrap products have traditionally been those intended for direct sale to the public (or to a specific subset of the general public, for example, graphic designers). The term shrink wrap, although anachronistic with increased distribution via direct downloads onto varied devices, will be used within this thesis for any product sold in the general market and for the projects producing these products. With all types of projects, the valuation is a matter of comparing benefits with costs. In the case of shrink wrap products from the supplier s perspective: Development Costs Support and Maintenance Costs Calculation of Value using Financial Techniques of Chapter 4 Compare returns against other possible investments Marketing Estimates of Future Sales and Revenues Figure 30 Shrink Wrap Projects Financial Value Calculation (Supplier's Perspective) The biggest unknown here is the estimate of future sales and revenues. The techniques used by marketing to estimate sales are beyond the scope of this thesis, but the financial

171 156 valuation techniques, examined in Chapter 4, support sensitivity studies which allow the analysis of errors in those predictions. Here, since it is unlikely that support and maintenance costs can be charged to end customers, these costs are seen as an expense which reduces project value for the supplier. Also, of note is that valuation techniques such as real options and game theory are particularly relevant. Investment in a prototype or limited function first release can be evaluated using real options techniques as a means to value the flexibility of making future investments should the pilot be successful. Game theory is useful as a means to model and understand competition in the market. Table 27 Assumptions, Measures and Uncertainties of Shrink Wrap Projects (Supplier's Perspective) Assumptions Relevant Financial Measures Greatest Uncertainty Marketing or other groups outside of the software engineering group can provide reasonable estimates of future sales and revenues. Accurate cost estimates are available. Relevant Financial Measures: Basic financials measures (NPV, ROI, IRR, payback period) and advanced techniques such as real options and game theory are relevant. Estimates of future sales and revenues Shrink Wrap Projects (Customer s Perspective) From the perspective of an end customer, the cost of the project, that is the cost of software plus deployment and maintenance costs are well known or can be well known relative to the uncertainties developing organizations (suppliers) face with cost estimates. For potential benefits, process measures as discussed in section 4.5 are useful. Process measures are useful for determining the value of software used internal within the organization.

172 157 Purchase Costs Support and Maintenance Costs Calculation of Value using Financial Techniques of Chapter 4 Compare returns against other possible investments Process Measures Figure 31 Shrink Wrap Projects Financial Value Calculation (Customer's Perspective) Table 28 Assumptions, Measures and Uncertainties of Shrink Wrap Projects (Customer's Perspective) Assumptions Relevant Financial Measures Greatest Uncertainty Support and maintenance costs are paid by the customer. Basic valuation techniques (NPV, ROI, IRR, payback period). Real options and game theory techniques do not apply. The real challenge is to estimate support and maintenance costs or ultimately in determining the total cost of ownership Bespoke Projects (Supplier s Perspective) Bespoke builds are custom builds or enhancements of a software product for a particular customer or customers. These differ from shrink wrap products in that the future revenue is usually known, that being the revenue specified in the contractual agreements between the supplier of software and its customer(s). Unlike shrink wrap products, support and maintenance costs may be paid by the customer. The financial valuations techniques studied in Chapter 4 are relevant. Of note, in this case, revenues and possibly maintenance and support costs (potentially zero for the software firm if the customer is paying) are well known. The task of determining development costs is more challenging

173 158 due to the unique nature of each custom build. Also, of note is that the static analysis techniques such as NPV calculation, ROI and IRR are more relevant. This is because presumably the terms of payment and the requirements of the project are firmly specified within contractual agreements. Real options, which model flexibility and game theory approaches, which model competition and the marketplace are less relevant. Support and maintenance costs may be a source of revenue not expense. As seen earlier, with shrink wrap support and maintenance almost certainly are an expense. Also significant, the revenue may be well known, as it is probably contractually specified. The greatest uncertainty is seen in development costs and support and maintenance costs. Development Costs Support and Maintenance Costs Calculation of Value using Financial Techniques of Chapter 4 Compare returns against other possible investments Revenue as specified in contract Figure 32 Bespoke Projects Financial Value Calculation (Supplier's Perspective) Table 29 Assumptions, Measures and Uncertainties of Bespoke Projects (Supplier's Perspective) Assumptions Relevant financial techniques Greatest uncertainty Support and maintenance costs are contractually specified and may represent a source of revenue for the supplier. Basic techniques (NPV, ROI, IRR, payback period) apply. Development costs, particularly because bespoke projects may be unique and novel in nature making cost estimation more difficult.

174 Bespoke Projects (Customer s Perspective) This case is identical to the Shrink Wrap (Customer s Perspective) case. From the perspective of an end customer, the cost of the project, that is the cost of software plus deployment and maintenance costs are well known or can be well known relative to the uncertainties developing organizations (suppliers) face with cost estimates. For potential benefits, process measures as discussed in section 4.5 are useful. Since the software product is used internally, process measures can be used to quantify potential savings from business process improvements. Purchase Costs Support and Maintenance Costs Calculation of Value using Financial Techniques of Chapter 4 Compare returns against other possible investments Process Measures (Section 4.5) Figure 33 Bespoke Projects Financial Value Calculation (Customer's Perspective) Table 30 Assumptions, Measures and Uncertainties of Bespoke Projects (Customer's Perspective) Assumptions Relevant Financial Measures Greatest Uncertainty Purchase costs and support and maintenance costs can be well known by the customer. Both may be specified contractually. Basic valuation techniques (NPV, ROI, IRR and payback period) apply. Process measures.

175 Internal Projects Internal projects refer to software development efforts internal to the firm. These are customer products for use internal to the firm needed to satisfy the needs of particular business groups or to meet strategic objectives. Since there is no direct payment made by an external customer, we must seek alternative ways to measure and specify the benefits of the project. Process measures can be used to produce quantitative measures. Development Costs Support and Maintenance Costs Calculation of Value using Financial Techniques of Chapter 4 Compare financial returns against other possible investments Revenue as specified in the context of internal process measures (Chapter 4.5) Figure 34 Internal Projects Financial Value Calculation Table 31 Assumptions, Measures and Uncertainties of Internal Projects Assumptions Relevant Financial Measures Greatest Uncertainty Accurate cost estimates are available Basic valuation techniques (NPV, ROI, IRR and payback period). Process measures, development costs and support and maintenance costs can all be uncertain and errors can impact value calculations. 6.6 Qualitative Evaluations In addition to financial measures based on process measures, the alignment of the project with respect to strategic alignment with the firm and alignment with enterprise

176 161 architecture is significant and should be used as part of project evaluation. The strategic goals of the firm can be identified through the use of business or organization level balanced scorecards. IT balanced scorecards can give a summary of the firms architectural directions and of IT department level goals. Projects can be evaluated against critical success factors as a means of evaluating risk and as a means of evaluating the potential for successful completion. This is illustrated below. Project Characteristics Compare against Organization s Strategic Objectives Compare relative alignment against other proposed projects Figure 35 Project Evaluation against Firm's Objectives Project Characteristics Compare against Organization s IT Objectives and Enterprise Architecture Compare relative alignment against other proposed projects Figure 36 Project Evaluation against IT Goals and Architecture Project Characteristics Compare against Project Critical Success Factors Compare relative ranking against other proposed projects Figure 37 Project Evaluation against Project Success Factors

177 Project Portfolios Firms typically have more projects than resources. One task of portfolio management is to select the best projects given constraints on resources. Portfolio management techniques typically try to classify projects into categories. This allows for the following advantages. Distribution of funding across project categories. For instance, business applications could receive 25% percent of the total project, exploratory projects 10% and infrastructure upgrades 65%. Within each project category, projects can be evaluated relative to each other. Essentially, each project category can be treated as a separate portfolio. Certain valuation techniques may apply only to certain categories of projects Weill MIT CISR Framework (Categorization by Investment Type) In Weill [80] the MIT Center for Information Systems Research (CISR) IT Framework is presented. Projects are classified along two dimensions, new vs. sustaining investments and along the dimension of asset class. The distinction of new vs. sustaining is that a firm must invest in new development to maintain competitive advantages. If the entire IT budget is consumed to maintain existing infrastructure and applications, the firm will lose competitiveness relative to others in its industry. Four asset classes are described in Weill [80]. Transactional automation of manual or repetitive tasks to cut costs and/or increase throughput. Informational providing information for finance, accounting, management, compliance and process monitoring and improvement. Strategic projects done to gain a competitive advantage or to remain competitive in the market. Infrastructure creation of shared IT services used by multiple applications, for example, network resources or shared servers.

178 163 Each of these asset classes can have projects that are focused on new development or on sustaining existing applications and functionality. As noted earlier, firms not spending on new development have grim long term prospects. IT governance (section 5.2.5) can be achieved by establishing separate portfolios for each class of project and be allocated funds to each portfolio to enforce desired strategic goals. For instance, separate funding for new vs. sustaining projects will prevent on-going demands for maintenance projects from preventing projects focused toward growth. The key point is that a categorization scheme is required. Different classes of projects require different means of assessment, prioritization and different sources of funding. A separate portfolio can be established for each asset class (type of project) and for new and sustaining projects within an asset class. This allows comparisons of projects of similar nature within each portfolio and more importantly directs funding toward certain classes of projects. For instance, more spending can be directed toward projects of a strategic nature, perhaps less toward infrastructure projects. While not directly related to the valuation of an individual project, project categorization can direct funding towards particular classes of projects and is related to the return and value obtained by the mix of projects conducted. The benefits expected from each category also vary by category. The following diagram is from [84]. It shows the possible benefits from each category (class) of project.

179 164 Superior quality Premium pricing Larger margins Higher Return on Assets 50% fail Some spectacular successes 2-3 year lead Premium pricing More sales from modified and enhanced products Increased control Better information Better integration Improved quality Strategic (13%) Informational (20%) Increased Sales Competitive advantage Competitive necessity Market Position Cut costs Increase throughput Transactional (13%) Infrastructure (54%) Business Integration Business flexibility Reduced marginal cost of BU s IT Reduced IT costs Standardization Higher sales per assets Lower cost of goods sold 25-40% return Higher market valuation, faster speed to market Smaller short run margins and lower ROA Figure 38 Returns from the Four Project Categories (based on [84]) A key point to observe in the above figure is the relative percentages that typical firms spend for each asset type, or equivalently for each class of project. These figures can serve as benchmarks for a firm to evaluate its spending relative to other firms. While benchmarks are not useful to valuation of individual projects, they can be used to direct funding for different types of projects. Ultimately, this direction of funding determines the returns and value of the set of projects done by the organization. More detailed data on an industry level can be obtained from MIT CISR, but is not presented here Ross Beath (MIT CISR) Categorization by Management Objectives In Ross [85] a classification of projects by management objectives is presented. Projects are classified along two dimensions. The first dimension is the time frame to profitability. Some investments are for short term profitability, some for enabling longterm growth of the firm. The second dimension is technology scope, which is whether

180 the project s benefits are related to a specific business process or need or whether they are more global in scope. 165 Business Solutions PROCESS IMPROVEMENT EXPERIMENTS TECHNOLOGY SCOPE Shared Infrastructure RENEWAL TRANFORMATION Short-Term Profitability Long-Term Growth STRATEGIC OBJECTIVE Figure 39 Project Classifications (from [85]) The technology scope is seen to vary from individual application level changes to address specific business needs to corporate wide technology changes. The strategic objective dimension is seen to run from addressing specific short term operational needs to addressing strategic objectives such as new market entry. Within this framework, Ross [85] classified projects into four types: Process Improvement Process improvements are changes to meet specific operational needs. An example is a new order entry system to automate a previously manual process. Renewal

181 166 Renewals are upgrades or expansions in existing technologies needed for increased efficiency or for maintainability. An example is an upgrade in the version of a vendor purchased product, such as a DBMS, to remain on a supported version. Experiments Experiments are tests of new technologies done in order to evaluate them and understand their applicability or research and development type activities. Transformations Transformations are changes in the core infrastructure when it is determined that it is insufficient to meet business needs or to support a new business model. An example is the development of an infrastructure to support E-commerce for a previously brick and mortar only company. The nature for evaluation and prioritization of projects in each category is different [85]. For instance, a business case approach is appropriate for process improvement projects, but possibly not for experiments. Static NPV or ROI evaluations of experiments alone would result in their rejection. Real option and game theory analysis as shown earlier in this thesis might indicate value, but Ross [85] suggests that these types of efforts need to be evaluated and funded based on a strategic evaluation. Additionally, based on the classifications, the source of funding for individual projects may be different. Process improvements (defined here to be efforts addressing specific operational needs rather than process improvement in the traditional software engineering sense) should be funded by the individual business units receiving benefit while transformations or experiments should be funded at a CIO or other executive level. The key point is once again that projects are initially classified by type to create portfolios of projects of related type. The funding of each portfolio and the evaluation of projects within each portfolio may differ as expounded in later sections of this thesis.

182 Proposed Categorization Scheme As seen in the preceding two sections, it is possible to define varied project classification schemes. For use within this thesis the following categorization scheme, based on Weill s work will be used. The category, Mandatory, is suggested in [83]. Empirical validation of this is outside the scope of this work, but future work on the effectiveness of alternate categorization schemes is an area that demands more research. Eight classes of projects are seen. Transactional, Informational and Infrastructure projects are seen as either New or Sustaining. Ross (section 6.7.2) provides examples of how infrastructure projects depending on their technological scope and purpose (focused on short term or long term profits) can determine whether they are new or sustaining efforts. Clearly a simple upgrade to the latest version of a DBMS or OS is a sustaining type of project. Development of extensive data centers to support turning a brick and mortar type store into one focused on E-commerce is an example of a new infrastructure project. It is assumed that strategic projects, by their nature, are new development efforts. Similarly, mandatory projects by their nature are seen as sustaining.

183 168 Projects Transactional Automation of manual or repetitive tasks to cut costs and/or increase throughput. Informational Providing information for finance, accounting, management, compliance and process monitoring and improvement. Strategic Projects done to gain a competitive advantage or to remain competitive in the market. Infrastructure Creation of shared IT services used by multiple applications, for example, network resources or shared servers. Mandatory Driven by external legal or regulatory needs or to satisfy internal or external audits. New Sustaining New Sustaining New New Sustaining Sustaining Figure 40 Proposed Project Classification Scheme The usefulness of process measures (section 4.5) as a valuation technique is very heavily dependent on project type. Process measures are useful for valuation of transactional, informational and infrastructure projects. Table 32 Usefulness of Process Measures by Project Type Project Type Transactional Informational Strategic Usefulness of process measures for valuation Useful Useful For strategic projects, defined as those that

184 169 move the firm into new markets, create radically different products or reinvent the firm (for example, changing from a brick and mortar store to E-commerce) not useful Infrastructure Mandatory Useful for renewal type projects (section 6.7.2). For transformation type projects (section 6.7.2) less useful. Not useful. The relevant question is the cost of the project versus the cost of withdrawing from the business or versus the cost of fines, penalties and lawsuits. Process measures are relevant to access alternate approaches. For strategic projects, often the future markets cannot be estimated with any certainty. This might be the case for firms entering new markets or creating entirely new products. For instance, firms competing early in the MP3 player market could not have forecasted the tremendous growth of this media. Additionally, for radically new technology, expenses are difficult to estimate. Early adopters of J2EE technology probably could not have accurately estimated hardware or maintenance costs. For projects of this nature, funding and the decision to proceed need to be made at senior levels based on a somewhat subjective understanding of market and technology trends. It is interesting, that despite this uncertainty and imprecise measure of value, it is these types of projects that ultimately determine the firm s survival, leading to great gains or losses. Real option techniques and game theory are particularly applicable.

185 For mandatory projects, process measures are not necessarily useful. 170 Compliance and regulatory projects are seen as a cost of doing business. Careful calculation of value is not necessarily useful. They may need to be done regardless of value, or alternatively, the value of doing them can be seen as the value of being able to continue to conduct business. Table 33 Relevant Financial Measures by Project Type Project Type Transactional, New Transactional, Sustaining Informational, New Informational, Sustaining Strategic, New Infrastructure, New Infrastructure, Sustaining Mandatory, Sustaining Relevant Financial Measures Basic Financial Measures (NPV, ROI, IRR, payback period) Basic Financial Measures (NPV, ROI, IRR, payback period) Basic Financial Measures (NPV, ROI, IRR, payback period) Basic Financial Measures (NPV, ROI, IRR, payback period) Basic Financial Measures (NPV, ROI, IRR, payback period) plus advanced measures (real option and game theory techniques) Basic Financial Measures (NPV, ROI, IRR, payback period) plus advanced measures (real option and game theory techniques) Basic Financial Measures (NPV, ROI, IRR, payback period) Potentially none. These projects are done to address regulatory or legal requirements and generally must be done regardless of cost to remain in a particular market or business. In some sense, the value of the project is that of remaining in business.

186 171 In the above table, advanced financial measures are seen as appropriate for projects that have strategic value (strategic projects or large new infrastructure projects that fundamentally alter the firm). These techniques have less value for informational or transactional projects where there may be less managerial choice (flexibility) and no need to consider competition from other firms. 6.8 Types of Firm The strategic focus of the firm is related to firm s strategic objectives. It is best seen as input into the process of defining the firm s objectives, perhaps as part of the process of defining a balance scorecard at the level of the firm. Indirectly, the type of a firm plays a role via an assessment of the characteristics of a project relative to the strategic objectives of the firm. Three dominant strategies exist [86]. Product Leadership: The firm competes by being on the leading edge of technologies and functionality and by offering higher quality. The focus is on new cutting edge technologies and on improved quality. Price Leadership: The firm competes by operating in higher volumes and lower per transaction costs. IT initiatives that lower costs and create efficiency are favored. Customer Intimacy: The firm attempts to customize services to particular customers and to provide comprehensive services. Tallon [64] presented an example of how the type of the firm could relate to the types of projects which are emphasized. The following table is from [64]. Table 34 Value in Different Firm Types Price Leadership Customer Intimacy Product Leadership Source of Value Best total cost Best total solution Best Product Example Firms Dell, Costco, Merrill Lynch, Intel, 3M, Sony Jetblue Capital One

187 Core Processes Supplier Relations, Production and Operations Role of IT Pursue automation and supply chain integration Customer Relations, Sales and Marketing Support Offer personalization and mass customization 172 Product and Service Enhancements Support the design of new product offerings Relating this back to the proposed project categorization framework, the following can be inferred. Table 35 Project Type Emphasized by Firm Type Strategic Focus of Firm Price Leadership Customer Intimacy Product Leadership Types of Projects Emphasized Transactional Informational Strategic Empirical validation of the above relationships is outside the scope of this work, but could yield insight into the problem of project categorization. Relative funding of portfolios to support particular project types may vary based on firm type. For instance, as suggested above in Table 35, firms with a strategic focus of product leadership might focus a relatively higher percentage of funds on portfolios of strategic projects. 6.9 Investment Boundary The investment boundary is a concept from modern portfolio theory. It expresses how much risk the organization is willing to tolerate for a given return. Relative to the investment boundary, projects can be rated as acceptable, marginal or unacceptable.

188 Investment boundaries can be established for various financial measures. ROI over a given period and NPV are shown below. 173 Additionally, the investment boundary is expected to vary based on project type. For instance, a higher chance of loss may be tolerated for strategic projects than for transactional or informational. The investment boundary will be seen to shift upwards or downwards based on project type. C h a n c e o f L o s s Investment Boundary Unacceptable Acceptable 0% 20% 40% 60% 80% 100% 120% 140% 160% ROI over given period Figure 41 Investment Boundary: ROI vs. Chance of Loss

189 174 C h a n c e o f L o s s Investment Boundary Unacceptable Acceptable NPV Figure 42 Investment Boundary: NPV vs. Chance of Loss 6.10 Discussion A proposed framework and process for the valuation of projects was presented. A project portfolio based approach was used. Projects were classified into a relevant portfolio and ranked against projects within that portfolio. The valuation of each individual project was done along multiple dimensions, both quantitative and qualitative. Projects should be reevaluated at multiple times as they are being conducted and after completion. Metrics collected during these reevaluations can be used for process improvements.

190 175 Chapter 7 Application of the Framework 7.1 Example Assume there are five internal software projects that need to be evaluated. Each is valued using process measures, an example of which is given in section From this, using the financial measures such as NPV, IRR, ROI, payback period can be calculated as shown in Chapter 4. The risk of loss for each project can be determined based on an estimate of the cost if the project fails and an estimate of the likelihood of this occurring. Additionally, each project is rated for its alignment with organizational strategy (section 5.4), its alignment with IT strategy / Enterprise architecture (section 5.4) and against a set of critical project success factors (section 3.3). This example shows how relative ranking of projects, steps six and seven, in the proposed process can be accomplished. Steps one through five, as described in the preceding paragraphs have been illustrated in other sections of this thesis. Assume that each project costs $ and they have the returns shown below. Additionally, the organization has capital and resources to conduct only one project. The task at hand is to assign a value to each project and to choose the best one to fit the organization s needs.

191 176 Table 36 Example of Use of Framework Projec t # Alignment with Organization al Strategy 1 Negative (0.25) Alignment with IT Strategy and Enterprise Architectur e Negative (0.5) 2 Moderate (2) Moderate (1.9) Project Critica l Succes s Factors Return (NPV) Low (1.1) Low(1) 2.l High (2.5) Moderate (2.2) 0 5 Moderate Moderate (2.1) (1.8) 0 ROI 283 % 183 % 233 % 267 % 186 % Payback Risk of Loss Period (based on (Months ) investment boundary, Figure 41, and estimate of chance of loss) 12 In acceptable region 12 In acceptable region 24 Boundary 12 Unacceptabl e 12 In acceptable region At a first pass, looking at this table, any investments that fall outside the investment boundary should be rejected. The investment boundary is the minimum return required for a given level of risk or equivalently the maximum risk acceptable for a given return. (see Figure 41 and Figure 42) The firm executives set this boundary to establish the returns needed to tolerate a given risk of loss. On this basis alone, project 4 would probably be rejected. This is interpreted as it being too risky for its level of returns. Project 4 would be rejected because it is too risky for the given return (despite having the largest overall return). This is based on its estimated chance of failure and the investment boundary shown in Figure 42. Despite its high return, we are assuming that it is too risky, that is, it is outside the investment boundary.

192 177 To establish choose among the remaining four projects, we need to consider other non-financial factors such as alignment with organizational strategies, alignment with enterprise architecture and chance for success when evaluated against project critical success factors as well as financial factors. Figure 43 examines alignment with Firm goals/strategies and with enterprise architecture and IT strategies. From this it is seen that although financially project 1 is desirable it is poorly aligned with the organization and IT. It should probably be rejected on this basis. Project 3 is on the investment boundary (see Table 36), meaning it is risky relative to the potential financial returns. Additionally, it has low alignment with organization and IT, so it should also be rejected. In this figure, the size of the bubbles show relative NPV of each project and the projects acceptability with respect to the investment boundary is shown as in the legend. From Figure 43, projects 2 and 5 have similar value with respect to financial returns and alignment with organizational strategies/goals and IT strategy / architecture.

193 178 Figure 43 Project Evaluation with respect to Organization and IT Goals Another view of these projects (Figure 44) examines each against project critical success factors. It is seen that based on these factors, project 2 has a much better chance of successful delivery. Perhaps it has a more experienced project team or a team co-located with the end users. Based on this evaluation, project 2 should be selected over project 5

194 179 Figure 44 Project Evaluation with respect to Organization Goals and Project Success Factors Another view, Figure 45, with each project evaluated against IT architecture and goals and against project critical success factors. It confirms that project 2 is the best available investment for the firm among the five potential projects.

195 180 Figure 45 Project Evaluation with respect to IT Goals and Project Success Factors 7.2 Discussion The above example showed how projects within a portfolio could be evaluated with respect to multiple dimensions. In the example, projects were evaluated with respect to financial measures, project critical success factors, alignment with organizational goals and alignment with IT goals and architecture. It was seen that each dimension discriminates between projects and by examining different dimensions, project selection can be achieved.

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