Project Selection

1. Project Selection Techniques for selecting projects

2. Learning Objectives • Understand basic evaluation models for selecting projects • Understand various techniques and approaches to evaluating potential projects • Understand the utility of computer tools in project selection • Be able to evaluate your organization’s techniques and suggest improvements

3. Why is Project Selection Important? • The FIRST STEP in successful projects • Wasted resources with starts and stops, high-risk, high-cost projects • Lost opportunity costs of not doing the “right” projects • Completion of projects that do not contribute to the organization’s strategic direction (throw-aways)

4. Overview of PS Issues • Project Management Office (PMO): What role should it play? How can it help? • Project Proposals: How is the list of potential projects built? • Strategically selecting best Projects: What global criteria should be used? • Project Selection: What local, individual criteria are important • Dealing with Uncertainty: How important is risk analysis at this stage?

5. Project Management Office What role should it play?

6. Potential Roles for the PMO • Define proposal formats and requirements • Collect proposals • Do preliminary screening based on criteria (local and global) • Convene Strategic Board (Decision makers) • Recommend and provide details to decision making board • Follow-up on getting project approved, funded, organized, and initiated.

7. Project Proposals How to document a potential project

8. Project Proposal:Content • Executive summary • Statement of need and business benefits of project • Nature of problem to be solved and general approach to a solution • Approach for implementation and support for the project • Description and experience of potential project team

9. Project Proposal:Statement of need and Business Benefit • Description of the need in general terms (non-technical) • Why it is a need now – urgency • Business Benefits • Tangibles and intangibles

10. Project Proposal:Technical Approach • More detailed description of problem to be addressed or project to be undertaken • Major subsystems of problem or project • Methodology or approach of solving the problem • Possibly alternative analysis • Special client requirements

11. Project Proposal:Implementation and support approach • Rough Order of Magnitude of effort and cost • Impacts on equipment, facilities, staff • In-house resource capability versus out-sourcing potentiality • Termination success statement • Potential logistic support needed • Other “success” needs

12. Project Proposal:In-house staff and skills requirement • Key project staff required • Estimate of skills required • Availability of required project staff • Impacts on organization departments and personnel

13. Project Selection Models Global and Local Criteria

14. Models – Benefits • Real world problems are much too complex to analyze in their entirety • A Model is an attempt to identify and isolate the “essential” elements of the real world problem in order to simplify enough for analysis • Models can provide valuable “insight” into the elements of a problem

15. Types of Models • Numeric versus Non-numeric • Stochastic versus Deterministic • Analytical versus Descriptive • Diagrammatic versus Textual • Complex, multifaceted versus Simple, single dimension

16. Characteristics of “Good” Model • Realistic – Should include all “important” variables of the real problem • Capable – Should be able to integrate the variables into the algorithm • Flexible – Should handle various combinations of variables, including new ones • Easy to use – Should be intuitive, not requiring a long or steep learning curve • Computerized – To alleviate the workload of using it

17. Non-numeric Selection Models • Sacred Cow (The boss wants it) • Mandatory due to operations • Mandatory due to competition • Mandatory due to legislation (legal) • Extension of existing activities, projects, products, or processes • Comparative Benefits (Opinion based) • Discussion • Delphi • Q-Sort

18. Q-Sort

19. Numeric PS Models:Profit / Profitability • Payback Period (PB) • Average Rate of Return • Discounted Cash Flow (NPV) • Internal Rate of Return • Profitability Index

20. Unweighted 0-1 Factor Model Unweighted Factor Scoring Model Weighted Factor Scoring Model Constrained Weighted Factor Scoring Model S = ∑(x), x=0,1 S = ∑(s), s=score S = ∑(s·w), w=weight S = ∑(s·w) ∏(c), c=constraint Numeric PS Models:Scoring

22. Benefits of Scoring Models • Structurally simple • Multiple decision criteria • Easy to modify • Easy to do “what if” or sensitivity analysis • Weights provide flexibility

23. Drawbacks of Scoring Models • It is a “ranking” method, but does NOT necessarily represent “true” value • Quantitative value may cause decisions without “judgment” • Assigning values sometimes is haphazard • Input value changes (assumptions) may cause large swings in results

24. Choosing the PS Model • Firms with outside funding often chose scoring PS models • Firms without outside funding often chose profit / profitability PS models • 80% of Fortune 500 firms also use “nonnumeric” PS models

25. Risk Analysis with Crystal Ball

26. Including Risk Analysis – Stochastic Models • Instead of assigning a fixed value to a raw score, assign a range of values and a probability. • Probability is usually more “realistic” • It may also be more “correct”

27. Areas of Uncertainty • Project timing & expected cash flow. • Direct outcome of project, i.e. what exactly will the project accomplish • Side effects and unforeseen consequences of project

28. Introduction to Monte Carlo Technique • Outputs are a result of an algorithmic combination of inputs • if the inputs cannot be determined with confidence, then provide a probability range • Monte Carlo Simulation picks an input value, based on the probability function, for each variable and calculates the result from the algorithm • This is done numerous times (500 or 1000) and the results are plotted

29. Crystal Ball • A Monte Carlo Tool that plugs into Excel • Any formula or calculation that can be done in Excel can be modified to use probabilities and Monte Carlo Simulation

30. Probability Distributions for Inputs

31. Risk Analysis: Output

32. Self Assessment • What are some of the roles of the PMO in project selection? • What should be included in a project proposal? • How does a Q-Sort work? • How does a Scoring Model work? • What is a Monte Carlo technique? • What is Crystal Ball? How does it work?

33. End