Stakeholder WinWin And Requirements Prioritization

1. Stakeholder WinWin AndRequirements Prioritization NupulKukreja 19thOctober 2015

3. Agenda • WinWin Negotations – What/Why? • The ‘science’ of decision making – what, why and how? • The role of decision making in Value Based Requirements Engineering & Prioritization (VBRE/RP) • Importance of ‘Planning’ • VBRP – what, why & how? • Practical Example

4. Will You Buy The Car? Picture the following dialogue between youand a car salesperson: You: I’d like to buy the fully loaded Honda Accord, for $25,500. I’ve done my homework. That’s the best price! Salesperson: You got it! Deal!Let’s finish the paper work.

5. Negotiation • Negotiation is traditionally viewed as a win-lose game between two parties • Even if you bought the car on your terms, you’d still feel you left something on the table • You’d feel it was too easy! • Moral: • DON’T say “YES” to everything • DON’T say “NO” to everything either • Than what do you say?

6. WinWin Negotiations • Negotiation, especially when multiple success critical stakeholders are involved should never be “Win-Lose” • There should always be a “WinWin” – even if one party feels they’re losing, they’ll “flip” the winners in their favor over time  Lose-Lose • WinWin != Satisfying Everyone • WinWin == Satisficing Everyone (It’s different) How’s it done?

7. WinWin Taxonomy (a.k.a. WIOA Model) • Win-Win Equilibrium: • All win conditions covered by agreements • No outstanding issues Win Condition: Stakeholders’ desired objectives stated in a form understandable by users, customers and other stakeholders and formalized only where necessary Issue: captures conflicts between win conditions and their associated risks and uncertainties Option: candidate solutions to resolve an issue Agreement: captures shared commitment of stakeholders with regard to accepted win conditions or adopted options

8. WinWin Negotiation Primer • Refine and expand negotiation topics • Collect stakeholders’ win conditions • Converge on win conditions • Define glossary of key terms • Prioritize win conditions on: Business Value vs. Ease of Realization • Reveal issues and constraints • Record issues and options • Negotiate agreements Shared taxonomy of topics to understand project scope Record first draft of stakeholder’s needs/wants for all to view Disambiguation and de-duplication Domain vocabulary to develop mutual understanding Degree of project success dependent on win condition Technological, social, political or economic feasibility Variance in prioritization provokes discussion of issues/constraints Issues recorded along with possible resolution tactics We also capture a 3rd dimension of “Relative Penalty” – Degree of project failure if WC not deilvered Mutually agree to win conditions/options Above steps accelerated by a “Shaper” i.e. a facilitator who guides the negotiation

9. WinWin Equilibrium • The state when: • All Win Conditions have been covered by agreements • No outstanding issues • Provides a ‘heat map’ of the current state of negotiations: • RED: Win Conditions (WC)/Options not agreed to or issue not closed • GREEN: WCs/Options agreed to or issues closed • YELLOW/AMBER: WCs/Options marked as candidates for ‘potential agreement’  further discussion may be required • Winbook provides capability to ‘see’ this heat map! • Every new feature request, expectation, benefit MUST BE LOGGED into Winbook – helps in having an up to date view of the ‘heat’ map w.r.t., the current state of negotiations

10. Winbook and WinWin Negotiations • Based on the WinWin Negotiation Framework and directly supports the WIOA Model • Winbook is a tool to ‘log’ the negotiation and show its ‘status’ as function of time • “Functional” Win Conditions to be captured in the user-story format (As a <role>, I can <activity> so that <business value>) • Dynamic prioritization of win conditions with sensitivity analysis capability • Winbook Tutorial available on CS577 class-website under “Tools & Tutorials” • WinWin Sessions are HUMAN centric and highly iterative. A tool like Winbook only helps ‘document/augment’ the process and not execute it

11. Negotiations over… What Next?

12. Insightful Questions • Given N requirements and budget/schedule constraints which ones to implement? • Which test cases should I run given time constraints? • What programming language should I choose? • Which design should I choose? • What framework should I choose? • What architecture should I choose? • Which project(s) should we choose? • Heck! How do I choose anything?

13. Decision Making – What? Definition:* • Decision making can be regarded as the mental processes (cognitive process) resulting in the selection of a course of action among several alternative scenarios • Every decision making process produces a final choice • The output can be an action or an opinion of choice. *Courtesy: http://en.wikipedia.org/wiki/Decision_making

14. Decision Making – Making a Choice Which apartment do you want to live in?

15. Making a Choice – How? • So, just how did you choose your apartment? • What all did you ‘see’ / evaluate before signing the lease? • Examples of possible criteria: • Rent per month • Location i.e., quality of area • Proximity to campus • Presence of a good looking neighbor  • …and probably several others

16. Analyzing the ‘Problem’ • You have the two key ingredients necessary for a decision problem: • A list of criteria • A set of alternatives • Problem: Given a list of criteria AND a set of alternatives select the alternative that best suits the given criteria Apartment Selection Criteria Decision Analysis Alternatives Rank ordered set of apartments Rank ordered set of alternatives

17. Decision Making – Why Bother? • Converts ‘art’ into science • Adds rigor to the act of decision making • Justification of choice of action i.e., why you chose what you chose? • Helps decrease legal liability Ex.: Why did Company A select the bid/tender of Company X over Y? (It’s not only cost ) • Documents the institutional memory that lead to that particular decision (i.e., helps trace back to provide justification of decision)

18. Decision Making – How do you do it? • If it is a well studied science (it is) does anything exist ‘out there’ to help practice this ‘science’? • There are various techniques that can be employed: • Multi-attribute utility theory (ISE 562 in Fall) • Analytical Hierarchy Process (AHP) • Simple Additive Weighting (SAW) • TOPSIS (Technique of Ordered Preference by Similarity to Ideal Solution) • …and many more (http://en.wikipedia.org/wiki/MCDA#MCDM_Methods)

19. Decision Problem – Look and Feel When considering multiple criteria in decision making the problem is often referred to as “Multiple Criteria Decision Analysis” (MCDA) or “Multiple Criteria Decision Making” (MCDM) Almost always has a matrix-like representation: Sij = Measure of how well Alternative ‘i‘ does on Criterion ‘j’

20. Okay, Great! But what has any of it got to do with VBSE? • Everything!!  • How do you decide: • Which requirement to implement first? • Which component to design first? • Which architectural style/pattern to use? • Which requirements to test first? • Which test-cases form part of the regression suite? • What all to prototype first? • For which component to write the “first line of code”? ControlTheory

21. Wait! But I’ve already done all of this before and I got it right too! • Probably! However… • Were you able to justify your choice i.e., how you came about choosing a specific option? • Was there ever a need to do so?  • Just “how” did you decide? • Perhaps intuition, gut feel, domain knowledge, tossing a coin, do as the Romans do… • Yes, a simple 1-10 works or even MoSCoW (Must, Should, Could, Would – have) but for relatively simple problems

22. Planning

23. Planning and Decision Making • What do we work on now? • What do we work on next? • How much money can/should we spend? • How much is being spent? • Are the risks being monitored/mitigated? • How does risk impact the plan? Important to plan around ‘value’

24. Purpose of ‘Planning’* • Why do we do it? • Reduce risk & uncertainty • Supporting better decision making • Establishing trust (i.e. frequent delivery) • Conveying expectations • Planning is a ‘quest for value’ • Attempt to find an optimal solution of the overall product development question: What should be built? *Agile Estimation & Planning – Mike Cohn

25. A Good Plan • One that stakeholders find sufficiently reliable • One that can be used as basis for decision making • Approximate time to market • An idea of the set of features • Made more precise as project moves on • Is a ‘living’ artifact showing the current status of the project to avoid last minute surprises • Is planned around ‘value’

26. Planning for ‘Value’* • Stakeholders needs must be understood • Just delivering features is not important • Necessary to balance scope, schedule, cost and value of features comprising the release • Various factors impacting prioritization • Financial value of having the features • Cost of development • Amount/significance of new knowledge • Product (what) • Project (how) • Reducing Risk (Business/Technical) • Schedule • Cost • Functionality *Agile Estimation & Planning – Mike Cohn

27. Decision Making and Planning for Value • Decision analysis techniques can be ‘overloaded’ to perform requirements prioritization… • …the rank-ordered output of decision making techniques could also rank-order requirements! • Requirements prioritized against the goals/needs/values of the stakeholders  VBRP • The prioritized requirements form the basis of the ‘plan’ – what is being delivered, for how much and by when?

28. The ‘Dimensions’ of Value • Value is a multi-dimensional quantity, a simple 1-10 may not cut it (too many ties – Must have, Must-must haves, must-must-must haves etc.) • Value lies in the eyes of the beholder …and so does its dimensions!  • Dimensions are ‘hidden’ within the ‘expected benefits’ of the various stakeholders • The benefits serve as the goals/objectives/criteria on which to prioritize the requirements • Point to consider: Are all dimensions* equally important? (*dimensions = benefits = criteria = goals = objectives)

29. Prioritizing Criteria/Value Dimensions • All criteria may NOT be equally important • But just HOW do you prioritize the criteria themselves? • A simple 1-10 (Yes, it works ) • A highly involved process like multi-attribute utility theory (MAUT) to get the utility functions for each criteria which shows the risk attitude of each criterion • Or another interesting technique - Project Success Sliders* * Radical Project Management by Rob Thomsett

30. Project Success Sliders 25% 50% 75% Success Criteria (defined at start of project) Image: Radical Project Management by Rob Thomsett

31. Project Success Sliders 25 1 It’s ‘subjective’ but an extremely effective tool to understand the importance of expectations and their relative tradeoffs! 50 2 100 4 75 3 They can be (and are) interpreted on a relative scale i.e., twice as important, half as much etc., 25 1 3 75 2 50 Image: Radical Project Management by Rob Thomsett

32. Putting It All Together You have: • Relative ranking of all criteria • List of requirements (or win conditions) What else do you need? • Scores! How well each requirement/win-condition does on each criteria You STILL need something else… • The decision analysis ALGORITHM!

33. Decision Analysis Algorithm: Given a set of criteria with possible weights and the measure of how the alternatives rank on the respective criteria find an optimal alternative The scale of the scores could be absolute, relative, 1-10 (Likert Scale), Fibonacci... …must be consistent across criterion column

34. Algorithms for Practicing VBRP • There are various algorithms in literature to choose from along with those from MCDA/M: • Kano Analysis • Planning Poker • 100-point assignment technique • Simple Additive Weighting • Quality Function Deployment (House of Quality) • Cost of Delay • Weigers’ Prioritization • Theory-W (Business value vs. Technical Feasibility) • TOPSIS • …and quite a few more 

35. A Practical Example • TOPSIS: Technique of Ordered Preference by Similarity to Ideal Solution (MCDM Technique) • Integrated in Winbook for prioritizing MMFs and win conditions • We’ll be using Business Value, Technical Feasibility and Relative Penalty as the criteria against which to rank the requirements • MMFs Prioritized against stakeholders’ value propositions/goals/objectives • Success Sliders for prioritizing value propositions

36. TOPSIS Primer Alternative 1 Ideal Alternative (S’) Criterion 1 Non-Ideal Alternative (S*) Alternative 2 Criterion 2 Aim: Rank order alternatives by their ‘closeness to ideal’ and ‘distance from non-ideal’ Criterion: Has ‘direction of preference’ i.e. more/less of the criterion is preferred Ideal: Best score for each criterion Non-ideal: Worst score for each criterion

38. Refinements to TOPSIS/VBRP • Prerequisite Handling (not yet integrated in Winbook) • Specifying MMF/WC prerequisites and factoring in prioritization • Simple solution: Priority of item less than all those in its prerequisite graph • Hierarchical Prioritization (partially integrated) • Prioritizing high level MMFs w.r.t. project goals • Prioritizing WCs w.r.t. MMFs • Prioritizing test cases w.r.t. WCs and so on

39. Points To Note • TOPSIS is ONE way of practicing VBRP • You could even perform COTS tradeoff analyses using it. (It’s a decision problem!) • Use the VBRP technique that is best suited to the situation • Some prioritization techniques do not lend themselves to a typical spreadsheet like analysis • The output of some techniques could be bucketed (categorized into the MoSCoW buckets) or ordinal (explicitly rank ordered)

40. Conclusion • Tools and techniques for prioritization are only one side of the coin… • …negotiations and discussions are the other. The latter must be held for the former to be of any value. Using the tool will NOT guarantee VBRP • There “maybe” a Homework on VBRP…keep a watch out for the announcement 