Bob Phillips, director of operations at B&W Systems, was put in charge of an important project. This assignment was the result of a recent B&W board meeting in which Grace Johnson, the vice-president of marketing, had presented a new product concept Forecasto. This cloud computing forecasting system was specifically designed to meet the needs of small- and medium-sized organizations. Johnson indicated a price point in the $200 range. Her primary concern was timing. Specifically, once the competition found out about the product there could be several additional entrants into this potentially lucrative market. The board meeting concluded with the chief executive officer tasking Phillips to look into the implementation of Forecasto in a timely manner and report his findings to the board at the next meeting.

BACKGROUND

B&W Systems designed and distributed a variety of management software products through the Internet and retail outlets like Best Buy. The company was considering the development of an Internet-based forecasting system. This system was designed specifically for the new start-up and small business owner. Phillips, after consulting with the technical staff and reviewing historical efforts, had developed the task descriptions, time estimates and immediate predecessor (IP) relations (see Exhibit 1). Phillips planned to use existing software components during the development phase as a means of keeping project costs and the overall time frame within bounds. Nevertheless, multiple task time estimates were formulated due, in part, to the inherent uncertainties associated with software development.

B&Ws management team had established a 35-week completion time for this effort. A preliminary assessment by Phillips indicated that some of the project tasks would need to be shortened to meet the management deadline of 35 weeks. Accordingly, the project manager had prepared a set of task-crashing estimates (see Exhibit 2). Phillips knew that this was an important project to manage and that he would have to do a thorough analysis for the board. He needed to estimate the completion time and budget for the project. Furthermore, he knew that he would need to determine the probability that the project could be completed within the deadline of 35 weeks.

Phillips knew that the board would want to know the minimum expected time in which the project could be completed and the probability of completing the project in this time. In addition, Phillips wanted to assess the additional costs for reducing the project time to the required 35 weeks, and which specific tasks could be crashed to achieve this milestone. He thought that there could be some potential issues that might cause the market assessment to take longer than expected. Phillips wanted to investigate the impact on the crashing solution if the expected time for task B (market assessment) was increased from seven to nine weeks. He had thought of an idea that could decrease development time significantly. Therefore, Phillips also wanted to see the impact on the crashing solution if the expected time for task D (development) was decreased to seven weeks.

The management team would certainly want to see the crashing cost function at the next board meeting, so Phillips had to produce that as well. He was curious to discover whether or not the crash cost curve was non-linear.

Phillips had taken a course on project management in business school. He was eager to use some of the techniques he had learned, such as the Program Evaluation and Review Technique (PERT), project crashing and linear programming, to do the analysis on this project. He only had one week to complete the analysis, thus he was eager to get started.

1. What is the estimated completion time for this project? What is the estimated project budget? What is the probability that the project can be completed in 35 weeks? (Hint: For the probability question, the answer to the question is in the 3% range. (The answer key indicates 3.09%.) But simply document key assumptions and show the work. It could be helpful to construct a new table with the Expected Time, Variance, ES, EF, LS, LF, Slack for each Task. The Expected Completion Time is 40 weeks. Double Hint: Using the NormDist function in Excel (the deadline, expected completion time, std deviation of the project, cumulative probability))

2. What is the additional cost for reducing the project time to the required 35 weeks? Which specific tasks do you recommend crashing in order to achieve this milestone? Breifly explain why you selected those tasks? (Please note: It is not required to calculate the cost minimization function to respond to this question (although you can if you want to, but it is not a requirement.) The aim with question #3 is for you to intuitively select the task(s) to crash in order to bring the project to completion in 35 weeks, and to explain why you chose those tasks to crash. There is no right / wrong answer (per se), this question is asking you to make a judgement call on which task(s) to crash to reach 35 weeks (and why).

3. What is the impact on the crashing solution (from Question #3) if the expected time for task B is increased from seven to nine weeks? (Hint: This is a basic What-If analysis, based on your response to Question #3. Please note that Task B has a large amount of slack.)

4. What is the impact on the crashing solution (from Question #3) if the Expected Time for task D is decreased to seven weeks? (Hint: Note the term Expected Time and your answer could vary depending on the judgement call in question #3).

Forward Passing Backward Passing Cakcuate Here Aways is EF Cakuat LS-ES or Times) 226 ES ET MostMostExpected Variance 6 Task Optimistik Lkely PessimisticTime Crash Costs Start Time Finsh Time Start Time Finish Time Slack 3.00 7.00 6.33 8.33 8.83 5.00 0.11 1.00 0.44 2.78 0.00 3.00 3.00 10.00 18.33 27.17 18.33 24.50 28.67 067 0.00 C 0.00 CP 8 Market assessment 10. 10. $ 20,000 6 25,000 $15,000 30,000 15,000 $ 45,000 65,000 20,000 $ 10,000 20,000 10,000 3.00 9 CDesign 9.33 18.33 11 ETosting 12 F Ravising 13 Documentation 14 H Quality assurance 15 Pricing 16 Production 17 K Distrbution 18 19 3.67 10.00 18.3 10.67 9.5024 18.33 24.50 28.67 30.67 0.00 CP 7.67 7.67 0.00 CP 0.00 CP 0.00 C 0.00 CP 0.00 CP 19. 0.11 BE 15,000 4 18,000 S 1.36 D S 20,000 4 $ 30,000$10,000 0.69 CE 5 10,000 3 15,000 S 5,000 5,000 28.67 30.67 2.00 3.36 F,6,H,I 40,000 5 50,000 $ 10,000 25,000 10,000 5.50 5 15,000 2 Critical Path Tasks 39.17 10.22 Begin with the Expected Project Length and backward pass Total Path Standard Deviation 3.20 wecks Since the EFT of an activity is always (EST Expected Time), we begin by asking what is the Earliest time that we can Start a Task, based on the Earliest Finish Times The Estimated Budget of this Praject is the Sum of the Normal Costs of the Activities 205,000 60.28% Proboblaty of Completing the Project within 40 Weeks? Using the NomDist function in Excel fthe deadine, expected completion time, std deviation of the project, cumulative probablity