Assignment attached. Please complete with the format below.
- Title Page
- Executive Summary (2-3 paragraphs that summarize your conclusions and recommendations - this is what you are paid for!)
- Introduction/Assumptions
- Presentation (e.g. the process you employed to solve the problem, be sure to explain all the steps you've taken and demonstrate your logic)
- Outcomes (tables, graphs, other visuals)
- Conclusions (make sure you answer all the questions)
- References, as appropriate
Summary: First, we have estimated the minimum duration to complete the project, also known as the critical path. There were ten possible paths to the activities to complete the project in minimum time. Five of the paths start with A, and five starts with B. We have critically evaluated each activity to calculate the estimated duration to complete the activity. Path with activity A - C - D - H - J - K has a maximum duration(critical path) to complete the project. As we have a project due to 70 days, our critical paths take 65.83 days to complete the projects. So, there is an 85.31 percent chance to complete the project on time. On the contrary, 14.69 percent chances to not completing the project on time. In our second scenario, 64.93 average days would ensure a 95% chance of completing the project in 70 days. We have 700 per day overhead cost, so we have one activity to crash in this situation: Activity A has a per-day crashing cost of 500. We don't have information regarding priorities of cost and time. So, we have only three maximum days for crashing. This will be reduced the total project cost by $600, and the entire project duration will be 62.83 days. As we have a total normal cost equal to 103400 now, we have 102400. Other activities have crashing costs greater than daily overhead costs, so crashing would not be appropriate for such activities. We have to take care of the tradeoff between crashing and overhead costs. We will move forward with other activities crashing if we prioritize early completion. Finally, we have crashed the project to assess the tradeoff between cost and time overrun. We have crashed all the activity in the critical path, and we have found that we can decrease the total project duration by 14 days by considering 19500 additional project crashing costs. We have evaluated per activity cost by their respective maximum crashed days available. Another scenario is that by crashing only activities A, J, and K., We can decrease the number of days with crashing cost only 9500. Again, it's solely dependent upon our priorities. Another scenario is by crashing only activity A. We can decrease three days by crashing cost only 1500. Introduction: About the Company: Capital Investment, Inc. (CI) is a small investment banking firm specializing in securing funds for small- to medium-sized technology firms. CI uses a standardized project format for each client engagement. The only items that need to be changed in the standard network of activities are the duration (activity times) and occasionally adding any unusual circumstances for the client engagement. MaryBeth Simms is assigned to the XYZ Company as a project manager partner. She has compiled the following information and activity time for XYZ Company. Figure Network diagram Critical path A-C-D-H-J-K Activity Estimated Duration Normal Normal cost ($) Crash Cost per day Maximum Crash Time Slope Total Crashing Cost Reduced time A 7.00 3,000 500 3 -625.00 1500 4.00 B 4.33 5,000 1,000 2 C 5.00 6,000 -- 0 5.00 D 20.00 20,000 3,000 3 -1000.00 9000 17.00 E 11.00 10,000 1,000 2 F 7.00 7,000 1,000 1 G 12.00 20,000 3,000 2 H 6.00 8,000 2,000 1 -1200.00 2000 5.00 I 9.00 5,000 2,000 1 J 5.00 7,000 1,000 1 -1500.00 1000 4.00 K 22.83 12,000 1,000 6 -653.47 6000 16.83 Crashing Cost 19500 Expected Completion Time 65.83 Completion Time After Crashing 51.83 Network Diagram Paths with Activity A as starting point. Path A-C-D-H-J-K: 65.83 Critical Path (Max Estimated Duration) Path A-C-G-H-J-K: 57.83 Path A-C-E-F-H-J-K: 63.83 Path A-C-E-F-I-K: 61.83 Path A-C-G-I-K: 55.83 Paths with Activity B as starting point. Path B-C-D-H-J-K: 62.16 Path B-C-G-H-J-K: 55.16 Path B-C-E-F-H-J-K: 61.16 Path B-C-E-F-I-K: 59.16 PathB-C-G-I-K: 53.16 Conclusion and Recommendations: First, we have estimated the optimal duration to complete the project, also known as the critical path. There were ten possible paths to complete the project. Five of the paths start with A, and five starts with B. Then, we have critically evaluated each activity to calculate the estimated duration to complete the activity. Path with activity A - C - D - H - J - K has maximum duration to complete the project. As we have a project due to 70 days, our critical paths take 65.83 days to complete the projects. We have evaluated per activity cost by their respective maximum crashed days available. We don't have information regarding priorities of cost and time. Another scenario is that by crashing only activities A, J, and K., We can decrease the number of days with crashing cost only 9500. It's solely dependent upon our priorities. Another scenario is by crashing only activity A. We can decrease three days by crashing cost only 1500. We have 700 per day overhead cost, so we have one activity to crash in this situation: Activity A has a per-day crashing cost of 500. So, we have only three maximum days for crashing. This will be reduced the total project cost by 600 dollars, and the total project duration will be 62.83 days. As we have a total normal cost equal to 103400 now, we have 102400. Other activities have crashing costs greater than daily overhead costs, so crashing would not be appropriate for such activities. We have to take care of the tradeoff between crashing and overhead costs. We will move forward with other activities crashing if we prioritize early completion. So, there are 85.31 percent chances to complete the project on time. On the contrary, 14.69 percent chances to not completing the project on time. Therefore, 64.93 average days would be necessary for our second scenario to ensure a 95 percent chance of completing the project in 70 days. Finally, we have crashed the project to assess the tradeoff between cost and time overrun. We have crashed all the activity in the critical path, and we have found that we can decrease the total project duration by 14 days by considering 19500 additional project crashing costs. Case Study #2 – Forecasting Ahmed is the Sales Manager at a large corporation that manufactures engines for recreational vehicles (four-wheelers and utility vehicles such as those sold under the brand name Gator™). The company has been in business making engines for over 15 years but has only sold these small engines for the past eight years. After much growth in the industry, the company is questioning whether sales can be sustained at these levels. Recessions tend to impact discretionary spending as the company observed a few years ago. Executives are considering building a new facility, expanding existing facilities, or maintaining the status quo. Of course, they are also concerned that another recession might severely impact sales. To address these strategic questions, Ahmed must prepare a sales forecast and report his best prediction to upper management and the board. Fortunately, there is a significant amount of historical data available. However, Ahmed must choose the most appropriate forecast and make a sales recommendation to the executive committee. He will also need to rely upon his intuition and experience as a sales manager to ensure the conclusions he makes are logical and rational. Year Actual Sales 1 $3,400,000 2 $3,820,000 3 $3,644,000 4 $3,212,000 5 $3,622,000 6 $4,484,000 7 $4,674,000 8 $5,060,000 Next Year ??? Requirements Ahmed will want to compare several forecasts. • Two-year historical moving average • Four-year historical moving average • Exponential smoothing In the case of exponential smoothing, he must choose the best coefficient and will compare: • α = 0.2, • α = 0.5, and • α = 0.8. Case Study Questions 1. Compute the next year’s sales based on each of the five different forecasts. 2. Determine the accuracy of each forecast using MAD (mean absolute deviation). 3. What is the sales forecast that Ahmed should present to the executive board for next year? (Justify your recommendation with appropriate tables, graphs, calculations, etc.) Please submit only one document as your report to the Blackboard submission link. Your report should include the following sections: • Title Page • Executive Summary (2-3 paragraphs that the executives will use for their decisions) • Introduction / Assumptions • Solution (how did you solve the problem and specific processes deployed in your solution) • Outcomes (tables, graphs, calculations, etc.) • Conclusions and Recommendations (remember to answer all questions completely) Enrichment Suppose Ahmed uses a regression analysis of the data for the next year’s sales forecast. 1. Show a graph of the regression analysis and indicate the relationship between variables. 2. Compute the coefficient of correlation. 3. What is the next year’s sales forecast? 4. Is this prediction worse than, equal to, or better than your prior recommendation(s)?