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The Problem of IS Planning Generating Ideas

The Problem of IS Planning Generating Ideas. Ken Peffers Associate Professor of MIS UNLV February 2005. Presentation Agenda. Motivation and history Case study Research agenda. Setting the Scene. SIM Interchange 2002—Snowbird Resort Utah 400 CIOs from around the country

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The Problem of IS Planning Generating Ideas

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  1. The Problem of IS PlanningGenerating Ideas Ken PeffersAssociate Professor of MIS UNLV February 2005

  2. Presentation Agenda • Motivation and history • Case study • Research agenda

  3. Setting the Scene • SIM Interchange 2002—Snowbird Resort Utah • 400 CIOs from around the country • Two issues dominate meeting • Security • Managing the IS portfolio • Where to allocate resources to IT investment in the firm • Y2K and EC had hidden this problem

  4. Maintenance Operations Decision-making Strategic Managing the IS Project Portfolio • McFarlan speaker at SIM • Strategic Grid • Managing the portfolio 1980 • CSF (Rockart, 1979) • Top down method to manage IS portfolio • Why CSF? Only executives have strategic view.

  5. Strategic Option Bets10 + years Tactical SupplierIntegration Payoff Operations Value Chain Operations Strategic3 years SupportActivities Maintenance ChannelIntegration Cost saving1 year Service The IS Portfolio 20 Yrs Later Knowledge necessary to determine what is important all available in the executive suite?

  6. The IS Portfolio 20 Yrs Later • More dimensions for allocating attention/resources • Political & cultural • Project size--$10 million, $100 K, $5 K projects • Infrastructure • Sourcing • Seven dimensions—many cells • How many ways are there to create dissatisfaction?

  7. CIOs Concerned, Unsure How • To identify most important new systems • To determine what innovative IS users will pay for • To identify the essential and valuable features for new system

  8. Portfolio Planning Project Application Features Requirements Determination Idea Generation Feasibility Decision Making Design Evaluation Planning Framework

  9. Critical Success Factors • John Rockart 1979 • Problem: Most of the IT budget going for maintenance and incremental improvements • How to carve out resources to fund strategic initiatives? • Solution: critical success factors • Identify the 6 or 7 things that have to go well for the firm for it to succeed • Identify IT investments to support those factors

  10. Toward a solution • Use knowledge distributed around in and outside of the firm. (Execs don’t have all the answers) • Need for method to use this knowledge effectively. (Bottom up methods produce unusable portfolios of ideas.) • Wouldn’t it be nice extend CSF to incorporate knowledge of many around the organization? (But keep focus on what’s important)

  11. New method for identifying important innovative applications • Application of practical applied research methods from marketing, called “laddering.” • Critical Success Chains (CSC) • Use knowledge of many • Create meaningful models of what is important for the firm (or customers, etc.) • Understand reasoning

  12. Setting: Digia, Inc. • Digia small Helsinki R&D firm, specializing in developing applications for mobile communications industry • Our mandate: identify “killer cocktails” for mobile financial services

  13. Critical Success Chains at Digia • Pre-study scoping • Data collection—structured interviewing • Analysis • Content analysis • Clustering • Modeling • Ideation workshop • Post workshop analysis

  14. Prestudy at Digia • Participant sample • Industry experts and lead end-users • Experts: most knowledgeable scientists, professionals, and managers • End users: wealthy, educated, technologically sophisticated, mobile, SMS users • Identified 40, contacted 18 experts & 14 lead users • Collected idea from each for stimuli • Converted ideas into four bland application descriptions

  15. Data collection: Structured Individual Interviews • Asked participant to rank-order ideas • For higher ranked ideas • “Why would that application be important to you?” • Series of “why is that important to you?” questions • “What about the application made you think it would do that • Transcribed responses as chains

  16. Example chain Personal values Performance impacts Expected system feature

  17. Analysis • Resulting data • 147 chains, more than 1000 statements • Content analysis • Qualitative clustering to assign similar statements common label (construct) • 114 constructs • Clustering • Cluster chains to minimize construct variance within cluster • Modeling • Transformed clusters into five network models

  18. Example CSC Network Model

  19. Ideation workshop • Objective: translate 5 CSC models into feasible application projects • Business and R&D people • Chairman, Nokia Key Account Exec., 2 bus. Mgrs, 2 eng. Mgrs • Five hours on one day • Goals: ‘back of envelop ideas’ • No outside help

  20. Business model

  21. Workshop results • 3 ideas: My Financial Advisor, Transaction Assistant, Mobile Wallet • For one model it was apparent that Digia wouldn’t be a part of the value chain. “Let’s move on.” • For the last two maps, participants decided to treat them as one.

  22. Post Workshop Analysis • Prepare workshop results for presentation • Interaction model • Business value model

  23. Interaction Model

  24. Business Model

  25. Results for Digia • According to Digia executives, results of the analysis exceeded their expectations • Rich information about what lead users might value • Modeling with reasoning to help turn preference into applications • Solid information to support development • Plan to develop some of the application ideas

  26. CSC benefits to decision making and development • Potentially uses knowledge of many about what applications may be important • Suppliers, customers, employees • Models reasons why applications important • Promotes system ‘buy-in’

  27. Agenda—Current Research • Peffers, K. and C. Gengler, “How to Identify High-Payoff Information Systems for the Organization,” Communications of the ACM, 46:1, January 2003. • Peffers, K., C. Gengler, and T. Tuunanen, "Extending Critical Success Factors Methodology to Facilitate Broadly Participative Information Systems Planning," Journal of Management Information Systems, 20:1, 2003, 51-86. • Peffers, K. and Tuunanen, T., “Using Rich Information to Plan Mobile Financial Services Applications with Maximum Positive Impact: A Case Study,” Information & Management, 42:3, 2005, 483-501.

  28. Research in Progress • CSC applied to requirements engineering • Helsingin Sanomat • Develop Multi-channel access to sell advertising • Data collection similar to CSC • Follow up survey to participants

  29. Research in Progress • Compare CSC and other methods • In design stage • Matched sets of case studies to compare the outcomes of CSC vs FG, CSF, etc. • Extended research on RE • 2008 EURO games and games leading up to it • Sonera

  30. Research in Design stage • Requirements engineering. Survey of methods and synthesis—in design stage • Requirements engineering—integrating CSC RE method with UML

  31. Other Idea Generation methods • Focus Groups • Good for exploring customer preferences for features • Weak on modeling aggregated ideas • Surveys • Must have ideas in advance • Good for determining importance of ideas

  32. Research that’s needed • Idea generation for IS planning • Demonstration projects: “action research”

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