1. Predictability in Project Performance using Applied Statistics Rajeev AndhariaPMP, CISA, CISSP, ITILv3 Expert Co-Author “Six Sigma for IT Management” rajeev@myBTP.in
2. Agenda The PM Challenge Key Concepts Some Key Techniques Sensitivity Analysis & Criticality Index Monte Carlo Some thoughts Approximate: 30 minutes
3. The Project Management Challenge… Boss:I need the Cost number PM:I need details Boss:give me a number now. I wont hold you to it. PM:U will put the number in ur Budget. U will forget we had this conversation & beat me when the project goes “overbudget” Boss: Give me a number or I will beat you right now PM: Ok, it will cost $ 1 million Boss: That’s too high PM: If you already know the number why are you asking me? Boss: you should feel involved & accountable PM: I rather be a developer There are no facts about the future—everything that hasn’t happened is only an ESTIMATE. Boss PM
4. The Choice… Would you go to an orthopaedist who did not use X-rays? J.M. Furbringer
5. Key Concepts Predictability: Performance: Statistics: degree to which a correct forecast can be made either qualitatively or quantitatively Accomplishment measured against preset standards of accuracy, completeness, cost, and speed. set of tools for collecting, organizing, presenting and analyzing numerical facts or observations. provides tools for forecasting using data & models.
6. Key Concepts Project Performance Management Why Statistics & Project Management? increasing the “probability of success” of achieving the unique outcome within the given constraints (i.e. scope, time, cost, quality, risk & resource) improving predictability in project performance using proven practices in “applied statistics” & project management
7. Key Technique-1: Activity Criticality Index Given the activity duration estimates, the project manager wants to identify the critical activities. Popularly used technique: CPM Alternate technique: Criticality Index based on Sensitivity Analysis
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9. Sensitivity analysis is a technique for systematically changing parameters in a model to determine the effects of such changes. The Criticality Index expresses how often a particular task was on the Critical Path during the analysis.
13. Tell me something more on Monte Carlo Analysis? Step 1: Create a parametric model, y = f(x1, x2, ..., xq). Step 2: Generate a set of random inputs, xi1, xi2, ..., xiq. Step 3: Evaluate the model and store the results as yi. Step 4: Repeat steps 2 and 3 for i = 1 to n. Step 5: Analyze the results using histograms, summary statistics, confidence intervals, etc.
14. Parting thoughts… Conclusions are judged to be sturdy only if the neighborhood of assumptions is wide enough to be credible and the corresponding interval of inferences is narrow enough to be useful.” Edward E. Leamer (econometrician)
15. Parting thoughts… Stakeholder Management can be significantly improved by increased Predictability in Project Performance. Earned Value Analysis Decision Theory Expected Value Sensitivity Analysis Probability Distributions Quality Tools
