How to caluculate ROI when investing in a Business Intelligence / Data Analytics project

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1 White Paper How to caluculate ROI when investing in a Business Intelligence / Data Analytics project LÛCRUM, Inc. John Bostick March, 2011

2 LÛCRUM, Inc. LÛCRUM is a premier strategic consulting firm that provides breakthrough strategies for financial services, health services, manufacturing, utilities and general business. LÛCRUM's capabilities span the breadth of business systems and technology solutions. Capabilities include data management and data warehousing, analytical reporting, project management, business analytics and data architecture.

3 How to calculate ROI when investing in a Business Intelligence / Data Analytics project *and certainly a wrong way to address ROI as well! With the most recent exciting story behind IBM s Watson computer competing against celebrity Jeopardy contestants, it s again time to talk about what Business Intelligence and Data Analytics can do for you. First and foremost, it s common knowledge among CFO s, CIO s, and other executives that over the last 15 years the Road to Business Intelligence is littered with failed projects and half-done initiatives. Looking backwards, most of these initiatives failed not because of technology or competency of the personnel involved, but rather due to the lack of a true ROI analysis by the business users before the project got started. By using the words true ROI analysis, this white paper will show examples of the kind of detail required to establish a tangible economic baseline for any data analytics or intelligence initiative. Several iterations calculating the ROI are normal and require deep business planning by the user community. IT personnel do not normally do these types of business planning exercises which means that their participation is not required. In addition, traditional IT lacks the facilitation and leadership experience that is needed to complete the ROI planning exercise. What at first seems to be a fairly straight forward ROI analysis gets quickly blurred for several reasons. Most of the rationale lies in the area of expectations. Why? To be sure, the lure of technology as the focus instead of the Business ROI Analysis is part of the problem. Industry experts agree that there are 5 or so most common reasons that lead to failure. Failure in this sense of the word means not getting the original return off of the investment, budget-overruns, lack of useful functionality as define by the business users, and missed timeframes on the initiative itself. Here are the most common 5 situations: 1. Wrong Sponsorship: The initiative must have a business sponsor and not an IT sponsor. Like any tool, the tool-maker is not important; it s the persons using the tool that make the difference. Too often, IT leadership decides to solve the reporting and information sharing requirements once and for all. Since the users are not static, the requirements are not static, the data isn t static, and it s extremely tough to try to solve and then deliver. The road to heaven is paved with correct assumptions. 2. Treating the initiative as a discrete project. Business Intelligence is not project-based but more so Journey-Based. Discrete projects are laid out very carefully with requirements and designs 1 P a g e

4 documented and formally approved up-front. once the initial iteration is finished. Data analytics projects are just getting started 3. Lack of education of what to expect and how much the user community must participate. Inevitably, all Business Intelligence initiatives have changing requirements. Simply put, the business is constantly changing and thus, the questions one must ask about the business are constantly being tweaked and modified so as to ask the correct question. For example, commodity prices are at record highs this year; there weren t last year. Oil and other energy prices were on an upward spiral in 2007 and 2008 only to see excess capacity due to declining demand throughout the recent recession. Government legislation has made hiring full-time employees more expensive with the latest healthcare reform. Certainly labor has shortages and is more expensive; other labor has global capacity and thus is shifting from US-only to a global outsourcing center. Last but not least, global currencies are constantly changing and thus, making imports and exports change in their gross margins. The old saying, the only thing constant is change comes to mind. 4. Change in Business Leadership and/or Information Technology Leadership. Reorganizations are a fact of all businesses. With the points made in #3, the external factors in every market cause the internal management organization to adjust and shift constantly as well. 5. Believing you are finished. Again, there s no finish. Just like any honed process in a business, data analytics are a processed-based support system for the organization. Again, relative to ERP-style applications, BI initiatives never stop. They are never finished. ERP applications are implemented, tested, and then put into production where they simply run and run and run. Getting back to Watson: IBM publically claimed to invest $30M in creating the data and the technology to provide knowledge worker style answers for the Jeopardy game. Is that a lot of investment for most Fortune 500 companies? Can there be a clear ROI roadmap leading to a successful long-term initiative? Possibly, although certainly high risk. Let s take an example of a large company. In fact, for illustration purposes, let s take the Fortune 500 th company as an example. Well, it s Blockbuster, so let s take the 501 st one instead, Comerica. 2 P a g e

5 Comerica Incorporated is a financial services company headquartered in Dallas, strategically aligned into three major business segments: The Business Bank, The Retail Bank, and Wealth & Institutional Management. Comerica Bank locations can be found in Michigan, California, Texas, Florida and Arizona, with select businesses operating in several other states, as well as in Canada, Mexico and China. Comerica reported total assets of $57,1 billion at the end of March Comerica ranks among the 25 largest banking companies and has a presence in seven of the 11 largest U.S. cities. In 2009, the company reported revenues of $3.15 billion and net income of $217 million. At $3.15 billion in revenue, that equates to $60.5 billion per week in revenue and $4.1 M in net income per each of the 52 periods as well. They have 9,100 people with total payroll and benefits adding up to about 25% of the reported revenue on an annual basis or about $80,000. In looking at a large organization like Comerica, there s many areas in need of Business Intelligence. To be sure, data analytics is the center of the business user s universe and the technology is only the enabler. Let s dig deeper into what kinds of questions a user may have at a financial services firm like Comerica. The right frame of mind for one of these business knowledge workers is to think in what we call increase/decrease words. Here are some examples in the area of Commercial Banking (all factious but accurately portrayed): 1. Comerica has a desire to cross-sell more of their services to their existing commercial banking customers. a. Segment and profile existing clients in commercial banking. b. Identify single relationship clients most likely to buy specific category of other retail or wealth management products. c. Incorporate learning into field materials and training for cross-selling. d. With over 5,000 commercial customers, a single additional new client relationship to just 4 % of these would yield 200 new clients at a statistical average of $1,445 per relationship or $289,000 additional annual revenue. 2. The commercial loan credit analysts are trying to identify better ways to pro-actively identify bad risk. So the process may look like this. a. Conduct annual portfolio loss analysis by region and then by portfolio manager. b. Communicate results by categorizing the worst commercial loan officers to senior management. 3 P a g e

6 c. Take appropriate action to improve loss ratio. d. Extrapolate learning from both bad and good loan officers. Communicate to management across entire management organization. e. Our worst loan officers are costing the company over $23 M in above-average losses. Saving 15% of this amount would generate $3.3 M. 3. Improve potency of commercial customer leads. Tradition field marketing including canvassing, direct mail, telemarketing, and community relations has seen a recent decrease in productivity for gaining new clients for the bank. New methods are needed. a. Current hit rate is approximately 2 out of 53 cold calls. b. Create profile of prospective clients most likely to buy commercial services and use profile to create more receptive cold call leads. c. Improving the appointment rate from 2 to 2.3 (15% increase) would generate 125 new clients company-wide which will result in $324,000 in annual additional revenue. 4. Increase enterprise value of commercial client. a. Profile clients that use 5 or more services of the bank. b. Communicate profile to field. c. Develop screening methods, develop field sales materials, and improve field-training in overcoming likely objections. d. An increase of an average of 3.4 products per commercial client to 4.08 (20% increase) would provide $825,000 additional revenue on an annual basis. 5. The recent new funding of Small Business Administration ( SBA ) loans by the Obama administration has presented a green-field of growth for Commercial Banks to attract Small and Medium businesses that have existing relationships with existing loans a chance to restructure those loans and bring them into Comerica. Typically, 10-year loans, these loans could range from $1.0 M to a maximum of $5.0 M at a borrowing rate of 5%. The bank receives a healthy up-front fee for sponsoring and processing the loan and an additional fee over 10 years to manage the loans payment process. a. Educate Commercial Sales Force as to the business model for the SBA loans. b. Identify potential small and medium businesses that would fit the SBA profile. c. Establish a marketing campaign to contact, educate, and qualify candidate firms. d. By closing 100 loans at Comerica at an average of $2.5 M, this would equate to $250 M in additional assets. Up-front fees would be over $20,000,000 and processing fees would be an additional $2,000,000 over the 10-year period. Furthermore, these loans are backed by government guarantees and thus don t effect the borrowing base of the bank. 4 P a g e

7 Totaling the first 4 examples would have a savings or revenue improvement of M annually and a financial expense savings of $3.3 M. Adding in #5 would provide significant value to the firm. In each business case, the numbers used were provided by the departments that would carry out the plans. The authors of the above business cases provided very conservative numbers in their case. Is this kind of return real? Two LUCRUM clients in particular followed this roadmap and generated over $20M in greater profits in the initial 12-months after an average investment of $700K. ROI and the IT Business Intelligence Platform. It is recommended that the business provide 5-7 of these initiatives to provide a larger set of financial improvements. One single area with solid business improvement can holistically justified the journey of Business Intelligence. Once the business cases have been formally established, establishing the budget for the IT-related expenses can be identified and set against the increases in productivity. The timelength set for the ROI for the initial Business Intelligence depends on the company s accounting and investment policies and practices. The IT investments will be a combination of People and Technology. Using Comerica s example, there will be 5 persons from IT assigned to the initiative; they will leverage existing server and storage capacity within IT, and make no new technology purchases for the tools except for a SAS statistical analysis 2-person user license. Total investments will be $ 350,000 over the initial 6 month period. Summary: The above examples suggest that Business Intelligence is really thoughtful business strategies using data as a weapon. It doesn t center on the technology, the IT strategy enabling the technology nor the actual project for project s sake. 5 P a g e

8 For additional information LÛCRUM, Inc Montgomery Road, Suite 160 Cincinnati, Ohio

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