Project Management Lecture 21

1. Project Management Lecture 21 • Readings Chapter 14 • Lecture 21 Short Project Management.XLSX • Lecture 21 Project Management.XLSX • Lecture 21 Event Management Wedding Planning.XLSX • Lecture 21 Stochastic Bid Analysis.XLSX

2. Project Management • Project management involves estimating the length of time to complete a project • Once a project has been undertaken then a project manager is responsible for carrying out the project on the assigned time table • How do the managers establish a time schedule • Generally based on average length of time for each component • Average length of time based on past experience • The length of time to complete each step is a random variable so the number of days to completion is a stochastic forecast

3. Project Management • Who does project management? • Engineers, managers, accountants • They estimate number of days to completion • Generally do not incorporate risk • Benefits of incorporating risk into project management analysis • Assign a probability to number of days until project is completed • Assign a probability to getting a project done in a fixed timeframe; potential to negotiate a bonus with a reasonable chance of success

4. Project Management • KOV for a project management problem is: How many days will it take? • There is no final answer until the project is completed • Answer is unknown PDF of days, weeks, or months to completion; e.g., roads in Texas • Simulation provides a methodology for estimating unknown PDFs • Formulate project managementproblem as a Monte Carlo simulation problem

5. Project Management as a Simulation Model • KOV is “Number of Days” to completion • Identify each task (step) for project • Specify order of each task for the project • Identify bottlenecks where tasks will wait on precious stages • Determine the PDFs for number of days (or weeks, months) to complete each task • Rely on experience from past jobs • Depend on experts or subcontractors for the time to complete each task • PDF may be dependent on resources available • PDFs could be GRKS distributions

6. Project Management • Critical to identify the order of the tasks and their linkages (dependencies), for example: • Task 10 starts after Tasks 5 and 8 are completed • The last task is number 11 and it starts after Task 10 is completed • Thus, tasks 5, 8, or 10 could hold up the whole project • If analysis shows 5 is the bottleneck is it worth investing more resources in Task 5 to get the project completed earlier?

7. Project Management • Create a simple Project Network Diagram to summarize the order of tasks • Drawn it in Excel with simple arrows and boxes • Network diagram shows potential bottlenecks

8. Project Management as a Model • There are 6 tasks and tasks 2 and 3 wait on 1, • Task 4 waits on 2, • Task 5 waits on 3 and 4, • The last task (6) waits on 5 • Assumes next task starts day after its predecessor ends • Days in column C are GRKS() stochastic

9. Project Management • Scheduled number of days to complete the project is 45 days • P(Days>45)=? • Red line shows • 95% CI of days

10. Spreadsheet of a Larger Project Management Analysis

11. Project Management Expanded • I like to add a second KOV, the Cost of the Project • We know the cost of a project is stochastic • So project management model can simulate PDFs for days and cost • In the example $/day costs for each task are multiplied by stochastic days for the respective tasks’ days

12. Bid Analysis in Business • Businesses are often asked to prepare bids for uncertain projects, such as: • Build a house • Build a road or bridge • Build an airplane • Past experiences help in bid preparation • The cost categories are commonly known • But what of the risks? • Risks are taken into consideration based on perceived risks or past experience

13. Bid Analysis • As an owner/manager, job one is to estimate how much to bid a contract • We can use the project management, cost analysis to estimate the best bid for a contract • The costs are at risk and if we bid to low our profits are reduced or an actual loss is incurred – bankruptcy is a possibility! • Bid to high and your company does not get the job

14. Bid Analysis in Business • How fixed price bids work • Contractors provide a fixed price bid • Must deliver finished product at the fixed price • If costs exceed expectations, contractormust absorb cost excesses in terms of reduced profits, which could turn into losses • Risks are: price of inputs (materials), cost & performance of sub-contractors, performance of materials, performance of finished product, liability for environmental quality during project, interest rate, weather, labor availability, etc.

15. Bid Analysis in Business • Bids for new projects can be modeled as a stochastic simulation problem • KOV is the simulated cost or minimum bid • Objective of management: submit a bid price that is low enough to get accepted, but high enough to have high probability of a profit • We can set it up as a simulation model with the objective that the bid insures a 90% chance of a profit

16. Bid Analysis in Business • Model formulation • KOV is the bid and probability of a profit • Bid = Sum of costs + Desired Profit • Stochastic variables are any factor which affects the cost and are uncertain • Break each cost category into its basic component • Ex: Labor costs = wages+contract labor + professional labor + management time + Other • Useestimates of the PDF for each labor cost item from an expert in that field to simulate each cost individually • Materials costs are risky, get estimates of PDFs from experts for each material or a fixed price bid

17. Bid Analysis in Business • Example model to bid on a research project in Brazil • Start with a simplified budget for the project • Notice all of the uncertainties

18. Stochastic Bid Analysis - Deterministic Best Case/Worst Case - Lowest Cost is $244,100 or the “Best Case” scenario - Average Cost is $350,850 or the “No Risk” scenario - Highest Cost is $462,600 or the “Worst Case” scenario - Stochastic Results of Budget Simulation 1000 iterations - Mean $351,379 - Minimum $266,419 Note: This is much higher than the “Worst Case” - Maximum $440,159 Note: This is less than the “Best Case” Probability of under bidding project for alternative bids: - P(costs > 375,000) = 33.89% - P(costs > 400,000) = 16.67% - P(costs > 425,000) = 2.4% - P(costs > 350,000) = 50.5%

19. Bid Analysis in Business • The bid if you ignore the risk • Average Cost is $350,850 Stochastic Analysis yields the following

20. Bid Analysis in Business • Because we are uncertain about the cost of each projectcomponent, we can run a scenario analysis on the costs

21. Bid Analysis in Business • Example of a bid analysis for building a house Activity Cost of Materials • Site Preparation 5K, 10K, 20K • Concrete 50K – 60K • Steel 75K, 80K, 90K • Lumber 80K – 100K • Electrical 30K • Sheetrock 21K – 25K • Exterior Walls 41K – 45K • Paint 18K – 25K • Floor Covering 18K – 22K • Interest Rate 7% – 8.5% • Overhead 30K – 35K • Profit Residual

22. Bid Analysis in Business • Example of a bid analysis for building a house

23. Contractor’s Bid Analysis

24. CDF of Profits for Alternative Bid Prices

25. Event Planner • Event planner KOVs • Number of days ahead to start planning an event • Cost of the event • Research application KOVs • Time to complete a research project • Cost of a project • Wedding planner • Probability of being ready on time • Cost of the event • Banquet planner

26. Event Planner