1. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-1

2. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-2 Chapter 4: Project Selection & Approval Important factors Selection Methods Value Analysis, Optimization

3. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-3 IS Project Growth Corcoran (1997): billions spent on technology every year Sources –users –top management –within information systems Process –idea –estimate benefits, costs

4. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-4 IS Project Motivation Cost cutting/avoidance Revenue maintenance/enhancement Entering new markets –data mining Gaining market share

5. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-5 Estimation Pitfalls INTANGIBLES –nebulous benefits better decision making HIDDEN OUTCOMES –time, budget subject to great error CHANGE –technology changes rapidly outdating many good project ideas

6. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-6 Organizational Treatment of IS Projects Hinton & Kaye (1996) - survey of 50 organizations CAPITAL: rigid cost-benefit analysis REVENUE: need to invest to keep up InvestmentCapitalMixRevenue training0%1%99% marketing4%9%87% info tech39%41%20% operations58%31%11%

7. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-7 Initial Risk Evaluation Project manager ability experience with project type, environment, language familiarity with modern programming practice availability of critical equipment, software completeness of project team personnel turnover project team size relative control of project manager over project team

8. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-8 Evaluation Techniques Economic & Financial –payback68% –cost-benefit63% –npv/irr40% Multifactor –checklist38% –project profile26% –scoring/rating models26% –multicriteria11% Mathematical Programming18% Expert Systems6%

9. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-9 Criteria Financial –net present value/internal rate of return –payback –profitability index/budgetary constraint Management –support business objectives –respond to competition –better decision making –satisfy legal requirements Development

10. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-10 SCREENING Eliminate proposals not meeting minimum requirements GOOD: quick BAD: tradeoffs disregarded

11. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-11 CHECKLIST FactorsMinimum Standards a way to implement screening assure implementation of policy limits

12. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-12 PROJECT PROFILE Display project features with standards Compares strengths, weaknesses ProjectCostNPV/CostStrategic? A265230,0000.43no A801370,0000.51yes A921790,0000.46no B622480,0000.11yes B837910,0000.22yes C219410,0000.41no

13. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-13 Cost-Benefit Analysis Accurately estimate all benefits –identify overall profit impact –in net present terms Accurately estimate all costs –overall profit impact, in net present terms RATIO: benefits/costs 1, profitable can adopt by highest ratio

14. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-14 Payback Identify the time needed for costs to be recovered simple doesn’t consider NPV

15. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-15 Value Analysis Keen (1981) DSS benefits usually very nebulous Unfair to apply cost-benefit analysis –benefit estimates unreliable Costs - identify as in cost-benefit Benefits - leave in subjective terms Managerial decision: are you willing to pay this much for that set of benefits?

16. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-16 Multicriteria analysis SMART - multiattribute analysis –identify criteria (including subjective) –measure utilities of alternatives over each criterion –elicit preference weights swing weighting - reflect range of options value =  of weights times utilities

17. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-17 Optimization 0-1 linear programming each project a 0-1 variable –can take on value of 0 (not selected) –or 1 (selected) optimize expected return to firm subject to constraints –budget –scarce resources

18. © McGraw-Hill/Irwin 2004 Information Systems Project Management—David Olson 4-18 Summary Initial evaluation of projects is where most are eliminated Companies need to avoid nonprofitable –if budget scarce, select most profitable Many risks need to be considered ideally identify net present costs, benefits practically need to consider intangibles