An Exploratory Study of the New Product Development Process Utilized by Software Companies Using Agile Product Development Approach

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1 An Exploratory Study of the New Product Development Process Utilized by Software Companies Using Agile Product Development Approach (What are the most critical factors that make a product successful using the Agile Approach?) George Lazarevic October, Alonso Drive San Jose, CA george.lazarevic@know-place.biz

2 AN EXPLORATORY STUDY OF THE NEW PRODUCT DEVELOPMENT PROCESS UTILIZED BY SOFTWARE COMPANIES USING AGILE PRODUCT DEVELOPMENT APPROACH (ARTICLE DRAFT)... 3 BIOGRAPHY... 3 INTRODUCTION... 3 BACKGROUND... 4 DETAILED PROBLEM STATEMENT... 5 LITERATURE REVIEW... 6 PROBLEM STATEMENT SURVEY INTRODUCTION TO THE SURVEY SECTION ONE: BACKGROUND RESULTS SAMPLING PLAN DESCRIPTIVE FINDINGS DISCRIMINANT ANALYSIS FINDINGS RESULTS DISCUSSION LIMITATIONS OF THE STUDY POSSIBLE CONTRIBUTIONS TO THE DISCIPLINE, AND CONCLUSION BIBLIOGRAPHY

3 An Exploratory Study of the New Product Development Process Utilized by Software Companies Using Agile Product Development Approach (Article Draft) Biography George Lazarevic has extensive experience in product management and product marketing, having worked for various high-tech and software companies in the San Francisco Bay Area for more than10 years. He focuses on product marketing/management, entrepreneurship, business opportunity sales, leadership, and the organizational aspects of high-tech business. He is currently working on various projects related to emerging product development methods and its practical approaches. Besides consulting for high-tech companies, Lazarevic is pursuing a doctorate in business at Golden Gate University in San Francisco. He holds MSCS and MBA degrees. Introduction The software development process, among other things, is a creative, intellectual, innovative, design oriented activity. Promising NPD (New Product Development) methodologies in the software industry have emerged during the last few years. These methods are not only, in many aspects, different from traditional methods of product development in other industries, but also from other software methodologies used before the mid-1990s. The purpose of this study is to investigate NPD processes in number of software companies that are using Agile methodologies of development. Under Agile name umbrella there are several different software development methods. Agile 3

4 methodologies are focusing on adaptation of software product requirements rather than on pre-defined specifications. Focus is on the people rather than on the stringent process; emphasis is on innovation and quality rather than documentation. An objective of this study is to find out how to better the Agile NPD organization. Background New Software Product Development (NSPD) is a process by which a new software product (or service, or combination of both) is developed. The economy of today is becoming everyday more knowledge oriented. This economy is characterized by shorter product lifecycles, an emphasis is on innovation, and a quickening pace of technological developments. One of the main industries of the knowledge-based economy is the software industry. Traditional Economy Manufacture Labor Efficiency Management Hardware Tangible Knowledge-based economy Service Brainpower Innovation Leadership Software Intangible Table: The contrast of traditional and knowledge-based economy (Urban, G. & Hauser, J., 1993) 4

5 For software companies of today, NSPD is becoming not an option but an essential requirement. New products are daily released on the market. The success of a newly released product can determine the success of the company. Detailed Problem Statement In today s knowledge-based economy, software products have a prominent role. Today s software market is estimated to be over $200 billion (applications and systems software sales). The annual growth of the software industry is estimated to be around 10%. Many software companies are failing, without reaching profitability level, or even establishing substantial sales. In addition, there are serious issues related to the quality of the software released. According to the Standish Group (2001), a market-research firm, faulty software cost American firms $100 billion last year. A majority of the software products don t make to the market at all. The software industry is very competitive and in many aspects still very young. Many of the problems in the software industry can be traced to poor planning, selection and execution of the new product development process. New, more adequate software development methodologies are emerging to address these issues. Some practitioners are claming (Cockburn, 1999) that the Agile methodologies work well for certain types of projects (those with under 50 developers, changing requirements, highly qualified developers, close contact with a customer). However, there are no known studies, at this point, to fully establish what are the most influential factors that help, or hinder, the NSPD using the Agile approach. 5

6 Literature Review New product development area topics are interesting both for academics and practitioners. A number of authors have published research summarizing what type of research has been conducted already in this area, and have identified the areas for future research (Ann Craig, Susan Hart, 1992). Craig and Hart have divided studies in the NPD area according to the different approaches that have been undertaken, specifically: The scope of the study whether generalist (to identify the set of critical success factors) or specialist (to investigate one particular area of NPD indepth); The methodological approach adopted; The level of analyses; Whether failure, or success, or both is measured; The way in which success is measured; The type of product development investigated A research conducted by Booz, Allen and Hamilton (1985) is one of the most cited comprehensive researches in the NPD subject area. Booz, Allen and Hamilton have been conducting comprehensive research of the NPD process at Fortune companies, both in the U.S.A, and internationally since the 1950s. Their generalist research introduced several concepts including product-life cycle, and the new product idea mortality curve. Although different results are reported in different articles about how many new 6

7 products are failing - ranging from 10% to 90% - Booz, Allan and Hamilton are reporting than more than 40% of new products are failing. Cooper (1987) conducted research of NPD processes at more than 200 different companies in different areas of business. The results of his seminal research helped him to establish thirteen different phases of product development process. 1. Initial screening 2. Preliminary market assessment 3. Preliminary technical assessment 4. Detailed market study/market research 5. Business / financial analyses 6. Product development 7. In-house product testing 8. Customer tests of product 9. Test market/trail sell 10. Trail production 11. Pre-commercialization business analyses 12. Production start-up 13. Market launch Cooper (1993) also found out that the probability of new product success increased if all thirteen steps are conducted well. However, his studies also show that most of the companies did not conduct all thirteen steps for various reasons. The strict structure of Cooper s thirteen phases does not work the best, in most situations, for 7

8 software companies, where time to market is often the most crucial component of product development. In Cooper s work different phases and components of NPD process were analyzed. His more recent studies show, for example, that in 74% of projects the detailed market study was scored as deficient either done poorly or not done at all (Cooper 2001). Initial screening, was rated as the weakest overall activity, scoring lowest on proficiency scale (Copper 2001). Pederson (1993) in his doctoral dissertation based his research on previous studies conducted by Cooper and others. He conducted a survey of NPD processes used by consumer companies in the canned goods food industry. This doctoral dissertation is devoted the software industry and could be beneficial for some practitioners in the industry. In addition, the results of the dissertation were supported the previous findings of Cooper. Responding and listening to customer s needs is often cited as very important part of successful NPD. In an annual survey, conducted by Industry Week and Price Waterhouse Coopers Consulting (2002), seventy percent of the respondents listed customer needs as the primary focus of NPD strategies. After that, the next-closest factor cited, low product cost (only 13%), then innovative features (11%), and first to market (5%). This study is highly dependant on the industries that are included in this survey. The study confirms the need for effective communication with the customers. Many studies have as a final objective to help improve the NPD process. Davenport et al. (1996) detail, however, that a company s NPD process can not be easily reengineered. First, often there is a problem that the NPD process is misunderstood by different parts of an organization or individuals. In addition, the NPD process is not 8

9 sufficiently documented, if documented at all. Finally, because of the strategic importance of NPD for a company, changing a process is risky, especially if it is producing acceptable outcomes. Many studies and practice have shown that an ideal NPD process that works for all industries, organizational structures and companies doesn t exist. Many researchers are trying to identify common key success factors. Some critics, like Markus Erlich and John F. Mills (2001) are advocating additional emphasis on qualitative research and to conduct qualitative research to improve or verify quantitative findings. Also, the authors call attention to questionable selection of some widely used independent variables in the NPD research. Although there are characteristics of NPD processes that are common for different industries, there are significant differences between industries. The software industry is relatively young industry that is growing and evolving. Some of the experiences and findings from other industries can be used; other findings are not always applicable due to what are characteristics of software development process. Writing software is a collaborative and highly intellectual effort. In addition, writing software is dynamic, time constrained work with changing requirements. In his research paper Cockburn (1999) has a people-centric view of software development which is often in contradiction to methodologies used in the practice in traditional software development and other industries. What are called Agile methods encompass different methods that began to emerge from the mid 90 s. Emphasis of these methodologies is on creativity, change, speed and quality. These methodologies were previously known as the lightweight methodologies. 9

10 Using the Agile method, development is not overburdened with different processes. Emphasis with these methodologies is on software development as more of a design activity, rather than a construction activity. McCormack s study (2001) have tried to identify what are the key success practices for NSPD process and are pointing to wider use of Agile methods: An early release of the evolving product design to customers Daily incorporation of new software code and rapid feedback on design changes A team with broad-based experience of shipping multiple projects Major investments in the design of the product architecture The influence of these methods is increasing. The Giga Group (2002) estimates that 10% of corporate IT organizations now use Agile methods, 25% are exploring them. The Giga Group also estimates that in next year and half, more than 2/3 of IT organizations will be using some form of Agile process (2002). In one of the most recent studies MacCormack, A, Kemerer, C, Cusumano, M & Crandall, B (2002) conducted a research at HP of around 25 project that had been conducted at that company. The authors have highlighted some of the practices that help improve effectiveness of the Agile approach. Although this study is limited by number of respondents, number of success variables presented and is focused only one company - this is one of the good known rear studies focusing on quantifying the success factors of the Agile approach. Problem Statement 10

11 The software industry is one of the driving industries of the knowledge economy. Software companies are facing a number of challenges, both internally and externally. Due to stiff competition, software companies find themselves under the influence of increased pressure to produce innovative versions of software in shorter time periods. The competition in the industry is growing, and resulting that profit margins are shrinking. This study has the purpose of identifying key success factors for software companies using Agile approach in NPD process. This study hopes to determine what factors contribute most to the success of a software product developed using the Agile approach. Research Questions: Primary Research question: What are the most critical factors that contribute to success of NSPD process using the Agile methodologies? Some of potential investigative questions: Are some management methods used in new software product development more effective than others? Among different Agile methodologies (XP, Scrum, Adaptive, Crystal Family, DSDM ) are there some specific approaches more successful than others? If yes, under what circumstances are some Agile methodologies more successful than others? Does the combination of heavy-weight and Agile methodologies help - or hinder - successfulness of the software product under development? 11

12 (Usually there is combination of the multiple methodologies while developing a software product. This question inquires about a real-life situation when in addition to Agile some other methods are utilized.) Survey Survey is developed to have 30 questions. The discriminant analysis is often used to analyze known groups to determine relative influence of specific factors for deciding into which group various classes fall (Copper, Schindler, 2001). In this case the factors that contribute the most to successful product and unsuccessful product will be identified using the discriminate analyses. Introduction to the Survey This section accompanied the survey that was ed to the respondents of the research. In this section Introduction to the Survey, necessary instructions are provided to a respondent of the survey to help her/him fill the survey. What is the Agile approach? Agile encompasses number of lightweight methodologies like; Extreme Programming, Scrum, Crystal, FDD, Adaptive Software Development and others. Agile approach is characterized by close work with the customers, quick response to every changing requirements, less documentation, and close interaction within the product team. Is my product developed under Agile? 12

13 If you are not sure is your project an Agile; you can compare characteristics of your project with some of the main characteristics of the Agile approach: Development is broken down into a number of sub-cycles, each of which is geared to producing a subset of the functionality to be provided in the final product; a prototype is released to selected customers at a very early stage of development; the development process encompasses mechanisms to ensure rapid feedback on the impact of ongoing design changes. (MacCormack, A, Kemerer, C, Cusumano, M & Crandall, B., 2002). What is objective of the study? The primary objective of the survey is to establish what are the most influential factors that help, or hinder, the New Software Product Development using the Agile approach and to establish relationship between those factors, if any. How to complete the survey? Here are the instructions that were accompanying the survey. Please, think about a product (Product X) that was developed using the Agile approach and answer the questions below. Please, fill the survey thinking only about this project - resulting in the Product X. The project can be success, or failure, or something in between. If you have any questions about the survey, please feel free to contact [deleted by the author]. Scroll 13

14 down in order to fill out the survey, please. This survey takes about 15 minutes to complete. Thank you for your participation in the survey. Section One: Background 1. What is your job title? Product /Project Manager/Director Product Development Manger/Director Engineer/Developer/Consultant VP Marketing / Engineering/ CTO President Other, Please Specify 2. How many years of experience you have practicing Agile methodology? < >15 3. What kind of Agile approach you practice? Extreme Programming Crystal SCRUM FDD DSDM Adaptive Software Development Other 4. Please, indicate what percentages of your company s total new products undertaken under Agile development within the last year? <10% 10-30% 31-50% 51-70% 71-90% >90% 5. How would you rate success of the Product X (5 scale rate)? Unsuccessful Moderately Very Successful Successful 6. What was the primary criterion used to measure success of the Product A? ROI 14

15 Other Sales volume Payback period Internal rate of return Net present value Profit contribution Finish on schedule Finish with desired quality Finish within the budget 7. Which of the following categories best describes the product A? New to the world (Products that are new inventions at the time of introduction) New category entry (Products that take a firm into a category new to it) Addition to product line (Products that are line extension to the company product markets) Product improvements (Current products those were significantly better) Repositioning (Products that are targeted for a new use of application) Other 8. What is an extent of combining formal non-agile approach with Agile approach during the project? Not significant Minor Some Significant Very significant 9. Was there a presence of single product champion? No Yes - from Engineering Yes - from Sales Yes - from Marketing Yes - from Finances Yes - from Sales Yes - from R&D Yes - from General Management Other 10. Coordination between the groups within the company was successful. Slightly Neutral Slightly 15

16 11. There was a strong support by general management. Slightly Neutral Slightly 12. Collaboration within the product group was successful. Slightly Neutral Slightly 13. User stories were efficiently written. Slightly Neutral Slightly 14. Release planning was efficiently managed. Slightly Neutral Slightly 15. Release planning meetings were efficiently managed. Slightly Neutral Slightly 16. Code testing was done successfully. Slightly Neutral Slightly 17. The development group consisted of top developers. Slightly Neutral Slightly 18. The developers were successfully formally trained in the Agile approach. Slightly Neutral Slightly 19. The developers are successfully informally trained in Agile approach. Slightly Neutral Slightly 20. How many people were in a core development team? >200 16

17 21. Development was changing (adapting) in regards to deliverables? Slightly Neutral Slightly 22. Developers were very motivated for the project. Slightly Neutral Slightly 23. Developers were very familiar with the Agile Approach. Slightly Neutral Slightly 24. The code was under collective ownership (developers were able to change code of other people). Slightly Neutral Slightly 25. The product prototype was provided very early in the project. Slightly Neutral Slightly 26. What percentage of the final product s functionality was included in the first prototype? 0-20% 21-40% 41-60% 61-80% % 27. The Agile project participates were totally dedicated to the project (committed to the project and were not confused by multiple priorities or being pulled elsewhere). Slightly Neutral Slightly 28. Daily system builds were delivered throughout Agile development. Slightly Neutral Slightly 29. The members of the developing team regularly reviewed another person s code before it was included in build? Slightly Neutral Slightly 17

18 30. There was a lot of fun, humor during the development. Slightly Neutral Slightly Results Sampling plan The target respondent groups are software product owners, who manage delivery of a software product using the Agile approach. These people are responsible for products success and are intimately familiar with each step of the development process. The aforementioned people are working under various roles and titles like: Development Engineer/ Leader, Product Manager/Director, Product Marketing Manager/Director, Project Manager/Leader, and Engineering Manager/Director. The sampling frame is professional groups that are covering the topics related to development of software products. The method used is a non probabilistic sampling; the members will be selected from the groups, where we can likely find quality, number and type of respondents needed for the survey. Within these mailing groups, the respondents will be people who managed and owned software product delivery using the Agile approach. The sampling framework from this study was drawn from people who have experience managing or participating in a software project conducted using one of the Agile methods. The survey was conducted by surveying members from the five 18

19 reputable Agile methodologies yahoo groups. One follow up was sent to remind respondents about the approaching deadline for end of the survey. Overall, there were 28 respondents during the period of two weeks (03/17/03 03/31/03). Previously, conversations with five experts in the filed were conducted. In addition, a small test survey with 4 selected respondents was conducted. They were not a part of the main survey. Overall response rate was about 4% although the response rate might be to somewhat higher because it is questionable how many people are in active membership of these groups. The survey was located on a web site and it was 30 questions long. The respondents were asked to think about a product that was developed using the Agile approach and to fill out the survey thinking only about one project. Descriptive Findings Who are the people who have responded to the survey? Most of the people who responded to the survey are technical experts and leaders (Engineer/Developers/Consultants) 54%; then the Product / Project Managers (Directors) 19%; and then VP Engineering/ VP Marketing / CTO and Coaches both 11%. Most of the respondents (54%) have somewhere between 1-4 years of experience practicing Agile method; followed by people who have 5-10 years (21%) and with people less than 1 year (21%). Only 28% of the respondents claimed that an extent of combining formal non-agile approach with Agile approach during the project was significant or very significant. The most prevalent size of the Agile core development team is from 4 to 10 developers (54% of respondents). Less than 50% of the final products functionality was 19

20 included in the first prototype in 51% of the cases (0-20% - 36%; 21-40% - 25%; 41-60% - 18%,..) Most dominant Agile method, according to the survey, is Extreme Programming (44%), followed with DSDM and SCRUM (each 22%); all other Agile methods are only 16%. Agile methodologies are becoming more popular and according to the survey about 50% of respondents company s total new products were undertaken under Agile development within the last year. However, for some companies Agile methods are still in experimental phases; about 24% of all respondent s companies less than 10% of new products were undertaken under Agile development within the last year. Most of the respondents considered finishing on time with desired quality (about 70%) as the most important criteria to measure success of the Agile product. That points towards more technical orientation of the respondents. Full information about response in the survey can be found in the Appendix. Discriminant Analysis Findings In order to find out differences between successful and unsuccessful product development, the respondent s data is analyzed primarily by discriminant analysis. A discriminant analysis is used to study differences between two groups, successful and unsuccessful product development. The independent variables consist of the items that describe product development process using the Agile approach; the dependant variables is rate of success of the product development of Products X, using the Agile approach. 20

21 Discriminant analysis is used to model the value of a dependent nominal variable based on its relationship to one or more predicting independent variables (Cooper &Schindler, 2001). The dependant nominal variable ( product success variable in the question 5 - q5) and number of independent variables (variables in these questions: q10 q19, q21- q25, q27 - q30) are used in this study. The independent variables are ones which describe the best the Agile product development process. In order to perform discriminant analyses data transformation was conducted with questions 5 variable inquiring about Agile product success. The discriminant analyses were conducted to differentiate between successful product (variable value =1) and all other including slightly successful, neutral and slightly unsuccessful (variable value = 0) Agile project (there were no respondents that graded their product unsuccessful). Independent variables are treated as scale (interval) variables although in the strictest sense there are nominal (ordinal) variables. However, according to many practitioners and theorist, it was demonstrated that the scale (disagree, slightly disagree, neutral, slightly agree, agree) are robust enough to be treated as interval scale for data analysis (Perreault, Young, 1980). In practical market research this type of scale is mostly treated to be interval scale (Conover, 1980). The discriminant analyses presented were conducted using stepwise method of discriminant analysis. Several different criteria were used to obtain the best possible results. Wilks lambda was used to measure the best separation of dependant variables. Values of Wilks lambda closer to zero and further from one represent higher discrimination. In our case, the Wilks lambda value was which represent reliable verification. Second factor used was statistical significance. Statistical significance 21

22 exists if results does not represent random sampling fluctuations only (Cooper &Schindler, 2001). The level of significance was for Wilks lambda at zero level which represent reliable indicator for successful analysis. The third and final criterion was percentage of correctly classified projects as successful or others. The discriminant analyses model is accurately predicting up to 96.4% cases. For successful project it goes fully to 100% and only misclassifies one case from fourteen of cases with zero as value of the variable. Wilks' Lambda Test of Function(s) 1 Wilks' Lambda Chi-square df Sig Standardized Canonical Discriminant Function Coefficients Question 22: Developers were very motivated for the project. Question 24: The code was under collective ownership (developers were able to change code of other people). Question 25: The product prototype was provided very early in the project. Function Using the discriminant equation we can predict whether a product using Agile product be successful or not: 22

23 D = * q * q * q25 Original Count % Classification Results a SUCCESS Predicted Group Membership Total a. 96.4% of original grouped cases correctly classified. In the previous discriminant analyses, stepwise method was used (probability of F for entry was 0.08 and for removal 0.13). In the second discriminant analysis (probability of F for entry was 0.05 and for removal 0.10), only one predictor variable is identified (q22). That was expected since that variable was the most dominant variable in the previous analysis. Predicted group membership using this model dropped to 85.7%. Wilks' Lambda Test of Function(s) 1 Wilks' Lambda Chi-square df Sig

24 Original Count % Classification Results a SUCCESS Predicted Group Membership Total a. 85.7% of original grouped cases correctly classified Totals Percentage Extreme Programming % Crystal 0% SCRUM % FDD % DSDM % Adaptive Software Development 1 1 4% Totals Table 1B: Success rate and different kinds of Agile <1 years 1-4 years 5-10 years years >15 years Totals Extreme Programming Crystal SCRUM FDD DSDM

25 Adaptive Software Development 1 1 Totals Table 2B: Years of experience and different kinds of Agile methods >200 Totals Extreme Programming Crystal SCRUM FDD DSDM Adaptive Software Development 1 1 Totals Table 3B: Number of people in the development team and different kinds of Agile methods >200 Totals Not successful 1 1 Neutral

26 Successful Totals Table 4B: Number of people in the development team and Success of the Agile project Not Significant Minor Some Significant Very Significant Totals Not successful 1 1 Neutral Successful Totals Table 5B: Extent of combining formal non-agile approach with Agile and Success of the Agile project Results Discussion Results from using discriminant analysis were very good with correctly classifying from 85.7% to 96.4% of the cases. Three main factors were identified that separate the best successful from all other projects. Those three factors were identified per Standardized Canonical Discriminant Functions Coefficients table: 26

27 Question 22: Developers were very motivated for the project. Question 24: The code was under collective ownership (developers were able to change code of other people). Question 25: The product prototype was provided very early in the project. If the respondents agreement with the statements in the questions 22 and questions 24 was higher - then the Agile process is more likely to be successful; however, if the respondents agreement with question 25 was higher then it would more likely lead to unsuccessful product. The most important factor is determined by answers to the question 22. The predictor factor in the Standardized Canonical Discriminant functions table based on the questions 22 is which is much higher than two other coefficients. If the probability for F is lower, the question 22 variable is the only variable that discriminates between successful and all other Agile projects. Additional two variables increase successful classification for just about 10% with different probability for F factor. It is not surprising that motivated developers are the key for success of the product. In the knowledge economy people are far more important factor than in other more labor oriented economies. So, we have another confirmation that Agile methodologies reliance on people is emphasized with importance of them being extremely well motivated. As Agile methods are crafted for people, motivation of the members of the development team is one that key success guides of the overall Agile project. 27

28 The purpose of this study is not to address how to best motivate people. Each individual carries own motivational riddle which is not static but is part of overall question how to best motivate the complete team. A number of studies was done with often very partial and conflicting views about the best ways to motivate members of the team. According to the results of the paper special motivation should be given how to best motivate the development team and according to the results of the study that is a crucial factor that separates successful from all other projects. The second strongest factor for the group membership is based on degree to which the code was under collective ownership. Collective code ownership assumes that every team member can change other person s code and contribute to solution. Collective ownership does not mean that all people are responsible - and in reality, no one is but to encourage synergy, collaboration and team work. This finding, that more people are involved in the team work, is consistent with the earlier finding in this paper about very motivated developers more people motivated they would have good support to be involved in building successful team work and work with others in various capacities and helping where needed. Importance of reaching a state when the group is much bigger than sum of the individuals is at core of different Agile methods. Individuals are contributing to each other and overall the development group reaches a hyper-productive state (Sutherland, 2001). The third strongest factor for the group membership is based on early product prototype. Most of the respondents seem to be interpreting this question in the light of changing, evolving product requirements. If there was less of the product prototype at the start of the Agile process it is likely that product would be successful. 28

29 Respondents were rating somewhat better Agile projects conducted using Extreme Programming and DSDM (Table 1B). However, according to the research these results were not statistically significant. Larger sample study is needed to provide answers which aspects of certain methods work better and which methods overall show the better results. Most of the respondents have between one and four years of experience using Agile. That confirms what is known that increasing use of the Agile methods are somewhat new phenomenon. The number of people in the Agile project varies with the most of the project having between 4-20 people. The most people in the project were between in less than 10% of the cases (Table 5B). Limitations of the study Agile methods are very new; clear definitions of different NSPD approaches are often non-existent, modified by organizations using, and changing. Some people do not recognize the encompassing name Agile (earlier somewhere called Lightweight) for this method; they recognize the name of the particular method they already use (e.g. XP). Therefore, challenge of this research is to obtain scientifically significant number of reliable respondents from software companies practicing the Agile approach. This type of survey - in which you gather number of relevant project information about various Agile project and analyze results - to the best of the author s knowledge was not done before. A lot of studies related to Agile are drawn from either direct experience of people who participated in the Agile project or from small number of case studies. Due to relatively modest number of respondents in this study some of the 29

30 results might not be completely representative. Larger sample size will be needed to confirm findings in the similar future surveys. Most of the respondents graded positively (from moderately successful to very successful) successfulness of their own and selected Agile project. Although specifically asked to select a project that can be success, or failure, or something in between only one of the respondents selected project that was unsuccessful (or between moderately successful to unsuccessful). For future research, it would be beneficial to have number of respondents providing information about to various degrees unsuccessful product. The development of a successful product is a complex endeavor. The Agile methodology is relatively new, rarely researched area. Often the question is what type of methodology to apply and is a project and a team best suited for one of the Agile methodologies or some other methodology. Possible Contributions to the discipline, and Conclusion Successful NPD has long been one of the most effective ways of maintaining a competitive advantage and differentiating a company s market offering from its competitors. In new and dynamic software industry, successful NPD is a matter of survival for these companies. NPD using the Agile methodologies is becoming more popular way to produce quality software product in a timely way. However, efficiency for this method and how to enhance this process has not been studied sufficiently. This study attempts to study these processes and to find some answers what the ways to better this process. This was on of the first attempts to approach to this topic, from more quantitative analysis side, 30

31 providing results that would hopefully guide some future research related to key success factors of the Agile projects. Bibliography Anonymous. US Industry and Trade Outlook 00. Department of Commerce and The Mc Graw-Hill Companies: Washington, DC. p.28-4 Booz, Allen & Hamilton. (1982). New Products Development in the 1980's. Booz Allen & Hamilton Inc. 31

32 Cockburn, A.. (Oct, 1999). Characterizing People as Non-Linear, First-Order Components in Software Development. Humans and Technology. Humans and Technology Technical Report. TR Cooper, D. & Schindler, P. (2001). Business Research Methods. McGraw-Hill. Cooper, R.G. & Kleinschmidt, E.J.. (1987). What Makes a New Product Winner: Success Factors at the Project Level. R&D Management. Vol. 17 No. 3. Cooper R., & Edgett, S.. (2001), NPD Practices: The dark side of time and time metrics in product innovation. Visions Magazine. Product Development and Management Association 2001, Pp 21 Cooper R., & Edgett, S.. (2001), NPD Practices: The dark side of time and time metrics in product innovation. Visions Magazine. Product Development and Management Association Pp 33. Craig, A. & Hart, S.. (1992). Where to Now in New Product Development Research. European Journal of Marketing. MCB University Press Limited: Bratford, UK Conover, W. Practical Nonparametric Statistics. Second Edition. (1980). New York: John Wiley & Sons. p. 92 Davenport, T.H. & Prusak, L.. (1993). Working Knowledge: How Organizations Manage what They Know. Harvard Business School Press. Boston. Erlich, M. & Mills, J.F.. (August, 2001). A critical review of new product development performance research: Centre for Strategy and Performance, Department of Engineering, University of Cambridge: Cambridge, UK. Giga Group. Barnett L. & Narsu U. (Apr, 2002). Lessons Learned Practicing Agile Development. Giga Group. Boston, MA Hayes, M.. (May 20, 2002). Quality First. Information Week. Industry Week and PricewaterhouseCoopers Consulting. (April, 2002). Value- Chain Survey. New Product Development. Pp. 65 MacCormack, A. (Winter 2001). Product-Development Practices that Work: How Internet Companies Build Software. MIT Sloan Management Review. MacCormack, A, Kemerer, C, Cusumano, M & Crandall, B.. (2002). Flexible Models of Software Development: Must we trade off efficiency & quality? Submitted to IEEE Software. 32

33 Pederson, G.. (1993). An exploratory study of the new product development process utilized by selected consumer companies in the canned goods food industry. Golden Gate University: San Francisco. Perrault, W. Jr. & Young, F.. (February 1980). Alternative Last Square Optimal Scaling: Analysis of Nonmetric Data in Marketing Research. Journal of Marketing Research. 17. Sliwa, C. (Mar, 2002). Users warm up to agile programming. Computerworld: Framingham, MA. Sutherland, J. (2001). Agile Can Scale: Inventing and Reinventing SCRUM in Five Companies. Cutter IT journal. Vol. 14, No. 12 The Standish Group. (2001). Extreme CHAOS. The Standish Group, Inc.: Dennis, MA. Urban, G. & Hauser, J.. (1993). Design and Marketing of New Products. Prentice-Hall: Englewood Cliffs, NJ. 33

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