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Chapter 2

Chapter 2. Strategic Management and Project Selection. Problems With Multiple Projects. Delays in one project delays others Inefficient use of resources Bottlenecks in resource availability. Project Results. 30 Percent late Over half 190 percent over budget Over half 220 percent late.

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Chapter 2

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  1. Chapter 2 Strategic Management and Project Selection

  2. Problems With Multiple Projects • Delays in one project delays others • Inefficient use of resources • Bottlenecks in resource availability

  3. Project Results • 30 Percent late • Over half 190 percent over budget • Over half 220 percent late

  4. Challenges • Making sure projects closely tied to goals and strategy • How to handle growing number of projects • How to make projects successful

  5. Project Management Maturity • Project management maturity refers to mastery of skills required to manage project competently • Number of ways to measure • Most organizations do not do well

  6. Project Selection and Criteria of Choice • Project selection… • Evaluating • Choosing • Implementing • Same process as other business decisions

  7. Types of Companies • Companies considering projects fall into two broad categories: • Companies whose core business is completing projects • Companies whose core business is something else • They can also be broken down as: • Companies looking at projects to do for others • Companies looking at projects to do for themselves

  8. Project Companies • Must select which projects they will bid on • Generally based on… • Their expertise • Resource they have availability • Their chance of winning bid • Preparing a bid is expensive • They do not want to waste that effort on bids where they are unlikely to be successful

  9. Non-Project Companies • Must decide which potential projects they will pursue • Available capital is the major constraint • Profitability is often the major criteria • Must evaluate approaches when there is more than one project that can accomplish a goal

  10. Models • Models are used to select projects • All models simplify reality • That is, they only look at the key variables involved in a decision • The more variables included in a model, the more complex it becomes • Simpler models usually work better

  11. Types of Models • Stochastic Model • A model that includes the probabilities of events occurring within the model. In other words, the same inputs might yield different outputs at different runs. Also known as a probabilistic model. • Deterministic Model • A model that does not include probabilities. Given the same inputs, the outputs will always be the same.

  12. Criteria For Project Selection Models • Companies only want to undertake successful projects • Projects that fail waste resources and hurt profitability and competitiveness • Projects that succeed improve profitability and competitiveness • It is not possible to know ahead of time if a project will succeed or fail • In fact, there is a continuum of possible results from total success through absolute failure

  13. Criteria (Continued) • Companies need a way of weeding out the bad projects while keeping the good ones • No model can predict with absolute certainty • No model could predict • The Exxon Valdez wreck • The explosion of the Challenger • What we want is a model with a “good batting average”

  14. Model Criteria • Realism • Capability • Flexibility • Easy to use • Inexpensive • Easy to implement

  15. Realism • Needs to include all objectives of the firm • Needs to include the firms expertise as well as its limitations • Needs to report results in a fashion that allows different projects to be compared, e.g. how do we compare a project to lower production cost and one to raise market share

  16. Capability • Model needs to be sophisticated enough to deal with all projects • Varying resource requirements • Varying time periods • Varying probabilities of success • Needs to be able to select the optimum projects among all contenders

  17. Flexibility • Needs to be able to work with all projects • Needs to be updated as the firm and its environment evolves

  18. Easy to Use • Needs to be quick to gather the data and easy to use • Easy to be able to “fit” the project in the model

  19. Inexpensive • Do not want the model to eat up all the savings that result from using the model • Expenses include the cost of writing and maintaining the model • Also includes the expense of gathering the data needed by the model

  20. Easy to Implement • This is less of an issue with modern spreadsheets • However, a model to be used to evaluate all the firm’s projects should be centrally maintained

  21. The Nature of Project Selection Models • Models turn inputs into outputs • Managers decide on the values for the inputs and evaluate the outputs • The inputs never fully describe the situation • The outputs never fully describe the expected results • Models are tools • Managers are the decision makers

  22. Different Factors Affecting Outcome • Many factors affect the outcome of a project • Some are one-time factors • The cost of an item • Others are reoccurring • Maintenance • Not all factors are equally important • Critical factors on one project may be trivial on another project

  23. Types of Project Selection Models • Nonnumeric models • Numeric models

  24. Nonnumeric Models • Models that do not return a numeric value for a project that can be compared with other projects • These are really not “models” but rather justifications for projects • Just because they are not true models does not make them all “bad”

  25. Types of Nonnumeric Models • Sacred Cow • A project, often suggested by top management, that has taken on a life of its own. It continues, not due to any justification, but “just because.” • Operating Necessity • A project that is required in order to protect lives or property or to keep the company in operation. • Competitive Necessity • A project that is required in order to maintain the company’s position in the marketplace.

  26. Types of Nonnumeric Models Continued • Product Line Extension • Often, projects to expand a product line are evaluated on how well the new product meshes with the existing product line rather than on overall benefits. • Comparative Benefit • Projects are subjectively rank ordered based on their perceived benefit to the company.

  27. Numeric Models • Models that return a numeric value for a project that can be easily compared with other projects • Two major categories: • Profit/profitability • Scoring

  28. Profit/Profitability Models • Models that look at costs and revenues • Payback period • Discounted cash flow (NPV) • Internal rate of return (IRR) • Profitability index • NPV and IRR are the more common

  29. Payback Period • The length of time until the original investment has been recouped by the project • A shorter payback period is better

  30. Payback Period Example

  31. Payback Period Drawbacks • Does not consider time value of money • More difficult to use when cash flows change over time • Less meaningful over longer periods of time (due to time value of money)

  32. Discounted Cash Flow • The value of a stream of cash inflows and outflows in today’s dollars • Also know as discounted cash flow or just discounting • Widely used to evaluate projects • Includes the time value of money • Includes all inflows and outflows, not just the ones through payback point

  33. Discounted Cash Flow Continued • Requires a percentage to use to reduce future cash flows • This is known as the discount rate • The discount rate may also be know as a hurdle rate or cutoff rate • There will usually be one overall discount rate for the company

  34. NPV Formula

  35. NPV Formula Terms A0 Initial cash investment Ft The cash flow in time period t (negative for outflows) k The discount rate T The number of years of life • A higher NPV is better • The higher the discount rate, the lower the NPV

  36. NPV Example

  37. Internal Rate of Return [IRR] • The discount rate (k) that causes the NPV to be equal to zero • The higher the IRR, the better • While it is technically possible for a series to have multiple IRR’s, this is not a practical issue • Finding the IRR requires a financial calculator or computer • In Excel “=IRR(Series,Guess)”

  38. Profitability Index • a.k.a. Benefit cost ratio • NPV divided by initial cash investment • Ratios greater than 1.0 are good

  39. Advantages of Profitability Models • Easy to use and understand • Based on accounting data and forecasts • Familiar and well understood • Give a go/no-go indication • Can be modified to include risk

  40. Disadvantages of Profitability Models • Ignore non-monetary factors • Some ignore time value of money • Discounting models (NPV, IRR) are biased to the short-term • Payback models ignore cash flow after payback

  41. Scoring Models • Unweighted factor model • Weighted factor model

  42. Unweighted Factor Model • Each factor is weighted the same • Less important factors are weighted the same as important ones • Easy to compute • Just total or average the scores

  43. Unweighted Factor Model Example Figure 2-2

  44. Weighted Factor Model • Each factor is weighted relative to its importance • Weighting allows important factors to stand out • A good way to include non-numeric data in the analysis • Factors need to sum to one • All weights must be set up so higher values mean more desirable • Small differences in totals are not meaningful

  45. Weighted Factor Model Example Figure B

  46. Analysis Under Uncertainty—The Management of Risk • Everything to do with projects is risky • Some projects, like R&D, are more risky than others, like construction • Risks include… • The timing of the project and its associated cash flow • Risk regarding the outcome of the project • Risk about the side effects

  47. Risk and Uncertainty • What the decision maker does • What nature does

  48. Uncertainty • Pro forma financial statements • Risk analysis • Simulation (requires detailed probability information)

  49. Comments on the Information Base for Selection • Accounting data • Measurements • Uncertain information

  50. Accounting Data • Cost and revenue are linear • Cost-revenue data derived using standard cost standardized revenue assumptions • Costs may include overhead

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