PJM380 Peer discussion responses 200 words each

I’m trying to study for my Management course and I need some help to understand this question.

Please reply to both POST1: and POST2: in at least 200 words each. I have also included the professors comments and references for you. The professors comments do not need a reply.



Professor comments:


Start digging now … I am looking for your thoughts on this one. Note Task 1 is Start-to-Start with Task 2, and then Task 2 and Task 1 have a precedence relationship with Task 3. What do you make of this?

Do you think this can impact the project end date?

Here is another clue, Colleagues.

Tasks 1, 7, and 8. Do you see the slack? What does that say to you? Tasks 2, 3, 4, 5, and 6 are our Critical Path. What does that suggest our Project Timeline might be?

Something else to ponder.

The original intent is the triangle issue where task 1 is a start-to-start with task 2 — and it also is finish-to-start with Task 3 — while task 2 is a finish-to-start with task 3. Do you see any implications there for the timeline of the project?

I understand another question. So long as the PM manages the flow there should be little issue. Task 2 is a start -to-start with task 1, so, are we bound to start task 1 immediately (as depicted) or can we wait — based on the slack we see?


The linked bar chart shows the activities, their duration in days, and the types of relationships. The duration of Task 1 is currently two days however that may not be correct. The duration of Task 1 follows a triangle distribution with parameters of 1, 2, and 8. The project manager needs to calculate the triangle distribution to figure out the actual duration for Task 1.

Triangular Distribution

According to Martinelli & Milosevich (2016), “three values are used to describe a very simple and popular triangular distribution” (p. 403). The values, minimum (L); most likely (M); and maximum (H), represent the task duration in days. For Task 1, the minimum (L) is 1; the most likely (M) is 2, and the maximum (H) is 8. The values are used to calculate the mean using the following formula: (L + M + H)/3 or (1 + 2 + 8)/3 = 3.67 days (Martinelli & Milosevich, 2016).

Triangular Distribution.png

Note. Adapted from Project management toolbox: Tools and techniques for the practicing project manager (2nd ed.) by R.J. Martinelli & D.Z. Milosevich, 2016, John Wiley and Sons, p. 404.

According to the triangular distribution, Task 1 will most likely take 2 days. However, the task could take anywhere from 1 to 8 days. The mean for the task is 3.67 days. This means that the distribution is asymmetrical as the most likely value does not equal the mean (Iordanova, 2020).

Project End Date

The linked bar chart shows that Tasks 1 and 2 start on the same date. However, Task 2 lasts approximately 5 days. Task 3 starts after Task 2 is complete. So, as long as Tasks 1 and 2 are completed before Task 3 is scheduled to start, the project end date should not be impacted.


Iordanova, T. (2020, January 19). Bet smarter with the Monte Carlo simulation. Retrieved from https://www.investopedia.com/articles/07/monte_car…

Martinelli, R. J., & Milosevich, D. Z. (2016). Project management toolbox: Tools and techniques for the practicing project manager (2nd ed.). Hoboken, NJ: John Wiley and Sons


There is risk everywhere when it comes to projects. There are risks that are expected and are mitigated by any means, and then there is unexpected risks that can cause harm to a project, but how much harm and where is what risk management is used to find out. Martinelli & Milosevich (2016) state that during a project, “a project manager will face a situation where they have along list of risk events, and little clue of the impact they may have on the project goals,” and that “a Monte Carlo analysis can be performed to quantifiably evaluate the potential impact of the critical risks.” One of the tools part of the Monte Carlo that is used to find unexpected risks during a project and the duration that they may last is the use of triangular distribution. The triangular distribution “a common formula used when there is insufficient historical data to estimate duration of an activity. It is based on three points that consider estimation uncertainty and risk” (PMI, 2017).

Looking at the linked bar chart above, a project manager can make out several points that can describe the process of the project. One of the major points is that there is a connection between Task 1, and Task 2 and the possible risk on the schedule that these activities may have. Using the uncertainty and risk tool of triangle distribution, the project manager can take three points and create a risk assessment. These three points are: Most Likely (M), Optimistic (O), and Pessimistic (P). Once the PM has gathered the points, then it can be plugged into either the formula of Triangular Distribution, which is (P+O+M)/3, or use a similar formula of Bata Distribution (PERT) (which is used when an ample amount of historical data is present (PMI,2017)), which is (P+4ML+O)/6 (Martinelli & Milosevich, 2016, pg 404). Taking Task 1 and plugging it into either formulas using the parameters given, the Project Manger would get:

Triangular Distribution: (8+1+2)/3 = 3.68 days

Beta Distribution: (8+4(2)+1)/6 = 2.84 days

Using the risk techniques of triangular and beta distribution, project managers are able to see that Task 1 will take roughly 3 days to complete. Knowing this information, and seeing that the beginning of Task 3 is in relationship to the end of Task 2, and Task 2 has a length of 5 days, Task 1 should not be a risk, or should be considered a low level risk at most, and should have no effect on the project end date.

Martinelli, R. J., & Milosevich, D. Z. (2016). Project management toolbox: Tools and techniques for the practicing project manager (2nd ed.). Hoboken, NJ: John Wiley and Sons

Project Management Institute (PMI). (2017). A guide to the project management body of knowledge (PMBOK® Guide): Agile practice guide (6th ed.). Newton Square, PA: PMI Publications.