MGMT 610 Week 4 DB Forum 2 Example

Discussion Board Forum 2: Thread and Two Replies

MGMT 610 Risk Management, Discussion Board Forum 2 (thread and two replies)

Thread by [Student Name]

The prompt, the grandstand project and the classmates' posts are composites standing in for the course's own forum; the textbooks, the peer-reviewed studies and Scripture are real; the requirements follow Liberty's public course guide for MGMT 610.

Thread

When our county began replacing the 1950s grandstand at its fairgrounds, the project team scored risks on a five-by-five probability and impact matrix. Two landed in the red corner: a late delivery of structural steel and the discovery of contaminated fill under the old foundations. The matrix treated them as equals. When our consultant later estimated them in dollars, the steel delay had a 45 percent chance of costing about $91,000, an expected value of roughly $41,000, while the fill had a 30 percent chance of costing $1.24 million, an expected value of about $372,000. The matrix had hidden a ninefold difference. Worse, the team had spent its first two risk meetings on the steel, because the fabricator had a history of late deliveries and everyone could picture the delay. The fill had no such story behind it; it was simply a 1950s site that had once held a county garage and its fuel tanks.

Cox (2008) explains why. Analyzing the mathematical properties of risk matrices, he showed that they have poor resolution, often assigning identical ratings to quantitatively very different risks, and that they can even rate a smaller risk above a larger one. Thomas et al. (2014), reviewing how risk matrices were presented in 30 papers from the oil and gas industry, add that the rankings a matrix produces depend on how its scales and colors are drawn, so two reasonable versions of the same matrix can order the same risks differently. Neither study says matrices are useless for a first sort, but both warn against using them to allocate money.

The PMBOK Guide separates qualitative analysis, which prioritizes risks for further attention, from quantitative analysis, which estimates their combined effect on project objectives through tools such as expected monetary value and simulation (Project Management Institute, 2017). Our team had stopped at the first step. After the consultant's estimate, we built a simple Monte Carlo model of the budget using three-point estimates for the twelve largest risks. Kwak and Ingall (2007) note that Monte Carlo simulation is valuable for project scheduling and costing but is used less than it could be, partly because managers find it complex. Ours took two afternoons in a spreadsheet. It showed only a 38 percent chance of finishing within the county's $14.6 million budget, which led the commissioners to fund environmental testing before demolition. The borings found petroleum-stained soil under the north end, and the remediation was designed and priced before construction began rather than discovered by an excavator.

Simulation is not magic. The model was only as good as our three-point estimates, and we had to treat the steel and concrete price risks as related rather than independent. Wilson (2015) presents risk analysis as a basis for deciding how to respond, not as an end in itself, and the value of our model was the decision it prompted.

James warned believers against saying that they would go to a city, trade and make a profit, since none of them can see even a day ahead, and urged them to say instead that they would act if the Lord wills (English Standard Version Bible, 2001/2016, James 4:13-15). An honest risk analysis is a form of that humility: it admits what we do not know and puts a number on it.

Classmates: has a risk matrix ever led your team to treat two very different risks the same way?

Reply to Grace

Grace, your thread described the heat map your church used for its capital campaign, with risks such as a major donor withdrawing and construction bids coming in high. I liked that the committee reviewed it monthly, which many teams never do.

One detail caught my attention. You mentioned that the committee changed the impact scale halfway through the campaign, from five levels to three, to make it simpler. Thomas et al. (2014) showed that changing the scales of a risk matrix can change how risks rank against each other. If the donor risk and the bid risk swapped places after the change, the committee may have shifted attention without any change in the actual risks. The PMBOK Guide recommends defining probability and impact scales at the start, in the risk management plan, so they stay consistent (Project Management Institute, 2017).

Jesus's builder works out the full price of the tower before laying a single stone (English Standard Version Bible, 2001/2016, Luke 14:28). A campaign that redraws its measuring stick midway makes that counting harder.

A small test would show whether it matters: score the top ten risks on both scales and see whether their order changes. If it does, the committee will know the scale, not the risk, moved its attention.

Did any risks change color when the scale changed?

Reply to Dev

Dev, your thread on the Monte Carlo schedule model for your bank's mobile app release was impressive, especially the finding that the March launch had only a one in four chance. I agree that simulation told your sponsor something the Gantt chart could not.

I wonder how the model treated the three testing phases. You mentioned that each had its own range of durations, drawn independently. Kwak and Ingall (2007) emphasize that simulation results depend on the quality of the inputs and the model's structure. If the same defect rate drives all three testing phases, their durations are likely to rise or fall together, and treating them as independent would make the results look more certain than they are. Correlated inputs usually widen the range of outcomes, which would push the chance of a March launch even lower.

Wilson (2015) stresses using analysis to choose a response. With a wider range, your team might consider adding a test environment rather than overtime, since a second environment shortens all three phases at once while overtime helps only the phase it is spent on. It would also be worth rerunning the model after the first test phase ends, replacing the estimate with the actual duration, so the sponsor sees the forecast tighten as the project learns.

Did your tool let you correlate those three phases?

References

Cox, L. A., Jr. (2008). What's wrong with risk matrices? Risk Analysis, 28(2), 497-512. https://doi.org/10.1111/j.1539-6924.2008.01030.x

English Standard Version Bible. (2016). Crossway. (Original work published 2001)

Kwak, Y. H., & Ingall, L. (2007). Exploring Monte Carlo simulation applications for project management. Risk Management, 9(1), 44-57. https://doi.org/10.1057/palgrave.rm.8250017

Project Management Institute. (2017). A guide to the project management body of knowledge (PMBOK guide) (6th ed.).

Thomas, P., Bratvold, R. B., & Bickel, J. E. (2014). The risk of using risk matrices. SPE Economics & Management, 6(2), 56-66. https://doi.org/10.2118/166269-PA

Wilson, R. (2015). Mastering risk and procurement in project management: A guide to planning, controlling, and resolving unexpected problems. Pearson FT Press.