PJM 5300 Module 3 Activity Risk Analysis Example

Course	PJM-5300 Project Risk Management
Module	Module 3
Paper type	Module 3 case study: activity risk analysis and management
Length	About 511 words, 4 pages
Format	APA 7 student paper
School	Thomas Edison State University
Program	M.S. in Management in Project Management
Updated	October 2026

Free sample paper for PJM 5300 Module 3

Sixty-Two Percent: What Three-Point Estimates Say About Meeting the Client's Start Date

Student Name

M.S. in Management in Project Management, Thomas Edison State University

PJM-5300: Project Risk Management

Mentor Name

Month Day, Year

What this page is doingThe title states the probability the analysis produces, the figure that changes the conversation with the client.

Sixty-Two Percent: What Three-Point Estimates Say About Meeting the Client's Start Date

Why Single Estimates Mislead

The original schedule added most likely durations along the critical path and promised the client 29 weeks, a figure the sales team had repeated in two meetings before anyone asked the vendor how sure it was. Kendrick (2015) warns that single-point estimates hide uncertainty and that, because delays on a path accumulate while early finishes rarely help, schedules built from most likely values are usually optimistic. Three-point estimates ask contributors for an optimistic, a most likely and a pessimistic duration, which brings their worries into the open.

The Estimates

The program evaluation and review technique, developed for the U.S. Navy's Polaris program (Malcolm et al., 1959), estimates an activity's expected duration as (optimistic + 4 x most likely + pessimistic) / 6 and its standard deviation as (pessimistic minus optimistic) / 6.

The path's variance is the sum of activity variances, 4.61, so its standard deviation is 2.15 weeks.

Activity	Optimistic	Most likely	Pessimistic	Expected (weeks)	Std. dev.	Variance
Line design finalization	3	4	7	4.33	0.67	0.44
Equipment fabrication by vendor	12	14	22	15.00	1.67	2.78
Shipping and installation	3	4	6	4.17	0.50	0.25
Commissioning, IQ and OQ	3	4	8	4.50	0.83	0.69
Performance qualification and approval	2	3	6	3.33	0.67	0.44
Critical path total	\| 29	\| 31.33	2.15	4.61

Probability of Meeting the Date

A 90 percent confidence date is about 34.1 weeks. The 29-week promise had a very low chance of being met.

Target	z = (target minus 31.33) / 2.15	Probability
32 weeks (client's target)	0.31	62 percent
34 weeks	1.24	89 percent
36 weeks	2.17	98.5 percent

What this page is doingTurning estimates into a probability for the client's own date reframes the schedule discussion from a promise to a level of confidence.

Limits of PERT

PERT assumes activities are independent and that the critical path will not change. Neither is certain: a late vendor could also delay installation crews, and a slow validation could push another path to become critical. Flyvbjerg (2006) argued that project forecasts suffer from optimism bias and recommended reference class forecasting, comparing a project with the actual outcomes of similar past projects. Our last two lines took 33 and 35 weeks, which supports the 34-week figure over the original 29.

Responses

Vendor fabrication contributes 60 percent of the path's variance, so responses target it.

Drafting validation protocols in parallel shortens the most likely validation time, and the factory visit gives early warning of fabrication slips.

Risk	Response	Type
Fabrication delay	Weekly progress calls, a factory visit at week 8 and a late-delivery penalty clause	Mitigate
Long fabrication tail	Order long-lead parts, such as the forming tooling, at contract signing	Mitigate
Validation delay	Draft IQ and OQ protocols during fabrication so they are ready on arrival	Mitigate
Remaining schedule risk	Agree a 34-week date with the client, with weekly updates	Accept with transparency

Conclusion

Three-point estimates show that the original 29-week promise was unrealistic, that the client's 32-week target has a 62 percent chance and that a 34-week commitment has about 90 percent. Responses aimed at vendor fabrication, the largest source of uncertainty, can improve those odds.

References

Flyvbjerg, B. (2006). From Nobel Prize to project management: Getting risks right. Project Management Journal, 37(3), 5-15. https://doi.org/10.1177/875697280603700302

Kendrick, T. (2015). Identifying and managing project risk: Essential tools for failure-proofing your project (3rd ed.). AMACOM.

Malcolm, D. G., Roseboom, J. H., Clark, C. E., & Fazar, W. (1959). Application of a technique for research and development program evaluation. Operations Research, 7(5), 646-669. https://doi.org/10.1287/opre.7.5.646

What the PJM 5300 Module 3 instructions ask for

The Module 3 case covers activity risk analysis and management, and a live session in this module discusses one of the case studies. Expect to gather three-point estimates for critical activities, compute expected durations and variances, find the probability of meeting a target date and plan responses for the riskiest activities. Show the calculations in tables, state the method's assumptions and say how you would check the result against past projects. Get the three estimates from the people doing the work, then check the result against the real durations of similar past projects. Lay every calculation out in a table so the arithmetic can be checked.

Inside the PJM 5300 Module 3 example

The case explains why single estimates mislead. A table applies PERT to five activities with expected durations, standard deviations and variances, and a second table computes the probability of meeting three target dates. A section states PERT's limits and checks the result against past projects with research on optimism bias. A responses table targets the activity contributing most variance, and the conclusion summarizes the dates and odds. The case also notes that the 29-week promise had been repeated to the client before anyone tested it, which explains why the analysis matters for credibility as well as planning. A responses table targets fabrication, the activity contributing 60 percent of the path's variance. A second table converts the path's spread into odds for three target dates.

PJM 5300 Module 3 rubric: what earns full marks

Mentors grade this case on correct calculations, clear interpretation, awareness of the method's limits and responses aimed at the largest sources of risk. Papers that convert estimates into a probability for a real target date show how analysis informs commitments. Checking the result against past projects demonstrates judgment. Targeting responses at the activity with the most variance shows that the analysis guides action. Comparing the PERT result with actual durations of past projects shows judgment beyond the formula. Recommending a commitment at a stated confidence level shows how analysis improves promises to clients. Correctly summing variances, not standard deviations, shows care with the method. Stating assumptions shows rigor.

PJM 5300 Module 3 help: mistakes that cost marks

Students lose points by adding standard deviations instead of variances, by forgetting to take the square root or by treating PERT results as certain. Others plan responses unrelated to the analysis. Sum variances along the path. Compute probabilities for real dates. State PERT's assumptions. Aim responses at the biggest sources of variance. Give the client a date with its probability, not a single promise, and check it against past projects. Aim your responses at the activity with the most variance, since that is where effort buys the most certainty. A free first sample on your own PJM-5300 activity risk case is available on request.

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More PJM 5300 and M.S. in Management in Project Management sample papers

PJM 5300 Module 3 questions, answered

Where can I find a free PJM 5300 Module 3 sample paper?

Three-point estimates and the probability of meeting a packaging line's start date are worked in the case above.

How is a PERT expected duration calculated?

Add the optimistic and pessimistic estimates to four times the most likely one, then divide the total by six.

How is the standard deviation of a project path found?

Add the variances of the activities on the path and take the square root.

Why are single-point schedules usually optimistic?

Delays accumulate along a path while early finishes rarely help, and most likely values ignore the long tail.

What is reference class forecasting?

Estimating a project by comparing it with the actual outcomes of similar past projects.

PJM 5300 Module 3 Case Study: Three-Point Estimates and the Chance of Meeting the Start Date Example