PJM380 Peer discussion responses 200 words each

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.

Required

Recommended


Professor comments:

Colleagues,

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?


POST1:

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.

References

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

POST2:

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.


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