PM 340 Week 5 Managing Uncertainty Example

Risk, Ambiguity and a February Blizzard: Managing Uncertainty in the Final Weeks of a Museum Gallery Project

[Student Name]

University of Phoenix

PM/340: Project Delivery and Measurement

Week 5 Assignment

[Instructor Name]

[Date]

Prairie River Museum of Natural History, its risks, responses and figures are composites written for a model paper.

Eight weeks before its opening on the Saturday before spring break, the Omaha museum this course has followed, Prairie River, is installing its Pleistocene mammal hall. The Week 4 earned value analysis showed the project about 2.7 weeks behind, with a recovery plan in place. After the expected overrun and the second installation crew, only about $36,000 of the $300,000 contingency is uncommitted. The remaining weeks hold uncertainties of several kinds. This paper sorts them, plans responses and explains how the team built enough resilience to absorb what it could not predict.

Kinds of Uncertainty

The current standard treats uncertainty as broader than risk and describes several forms it takes: risk, ambiguity, complexity and volatility (Project Management Institute [PMI], 2021). Perminova et al. (2008) argued that uncertainty should be understood as a context for risk, in which managers lack knowledge needed to make decisions, and that managing it relies on reflection, flexibility and learning, not only on calculation. Ward and Chapman (2003) made a similar case for broadening risk management into uncertainty management, so that teams look at sources of variability and ambiguity as well as at discrete events. The museum's uncertainties fit four categories:

Risks: discrete events whose likelihood and effect can be estimated, such as a case failing its humidity test.

Ambiguity: unclear meaning, such as whether the university's loan agreement requires its own conservator on site during installation.

Complexity: many interacting parts, such as three media stations sharing a show-control system with the lighting.

Volatility: rapid, unpredictable change, such as Omaha weather in February affecting deliveries and crews.

The Risk Table

The team scored the main measurable risks by probability and cost impact, giving each an expected value:

Case fails humidity test and needs resealing (40 percent; $18,000; expected $7,200): mitigate by testing the last eight cases a week early with spare seals on hand. Owner: registrar.

Low-reflection glass for the last four cases arrives late again (30 percent; $25,000; expected $7,500): mitigate by approving standard glass as a temporary fallback for two cases. Owner: project manager.

Media software fault during the soft opening (25 percent; $12,000; expected $3,000): transfer by a service clause requiring the studio to provide on-site support for the first two weeks. Owner: education director.

Injury to a specimen during installation (5 percent; $60,000 plus reputational harm; expected $3,000): avoid by requiring two trained handlers and no specimen moves after 3 p.m., when crews are tired. Owner: registrar.

Minor punch-list items unfinished at opening (60 percent; $6,000; expected $3,600): accept, with a plan to complete them in the first week. Owner: facilities manager.

The total expected value of threats is about $24,300. That fits within the $36,000 of uncommitted contingency but leaves little room for risks nobody has named yet, so the director agreed to keep $50,000 of the management reserve available until opening day.

An Opportunity

Uncertainty includes good surprises. A university field crew announced in January that it had recovered a nearly complete mammoth skull from a Nebraska gravel pit, and national media covered the find. The team assessed an opportunity: if the museum could display a cast of the skull at opening, attendance and press coverage could rise. The response is to enhance: the curator contacted the university, which agreed to share scan data, and the fabricator quoted $9,000 for a printed cast. Rather than draw on the thin contingency, the development director asked a board member who had followed the dig to fund the cast, and the gift arrived within a week.

An uncertainty register with no opportunities in it is only half a register.

Ambiguity: Learning Instead of Estimating

The loan agreement says loaned fossils must be installed "under appropriate supervision." The museum read this as its own conservator; the university's collections manager might read it as hers. Assigning a probability to a misreading would not help. The team's response was to ask: the registrar called the university, which confirmed it would send its collections manager for two days. The installation schedule was adjusted to group the loaned specimens on those days. The standard describes this kind of response, reducing ambiguity through information, experiments and expert input (PMI, 2021).

Complexity: Small Tests

The show-control system links media players, lighting cues and sensors at three stations. Interactions among them could produce faults no one predicts. Rather than trying to model every interaction, the studio ran the full system for 72 hours in its own shop and then for a week in the gallery before specimens were installed, logging every fault. Two faults appeared, a lighting cue that blanked a screen and a sensor that triggered on cleaning carts, and both were fixed before opening.

Volatility: Keeping Options Open

February weather in Omaha can stop deliveries and crews for days. The team cannot forecast a blizzard eight weeks out, so it built options. Final crate deliveries were moved a week earlier and staged in a climate-controlled storage area. Installation tasks were sequenced so crews could switch to indoor finishing work if trucks could not arrive. The second crew was contracted with an option for four extra days.

Watching for Secondary Risks

Responses create risks of their own. The second crew means more people in the gallery at once, which raises the chance of a damaged case edge or a dropped tool near a specimen. The registrar answered with a simple rule: specimen moves happen only when the second crew is working at the far end of the hall. Earlier deliveries mean crates sit on site longer, so the facilities manager added the staging room to the museum's nightly security round and checked that its humidity log was being read every morning.

Resilience in Practice

In the fifth week before opening, a storm closed roads for three days. Crates were already on site, crews worked on lighting and graphics instead of case moves and the extra crew days were used the following week. The opening date held. The measurement plan from Week 3 helped the team see the effect quickly: earned schedule fell by half a week and recovered within ten days.

Conclusion

The museum's final weeks show that uncertainty is not one thing. Measurable risks were scored, given responses and owners and covered by a reserve sized against their expected value. An opportunity was pursued. Ambiguity was resolved by asking, complexity by testing and volatility by keeping options open. Together with the planning, delivery and measurement work of earlier weeks, these responses gave the project the resilience to absorb a blizzard and open on time.

References

Perminova, O., Gustafsson, M., & Wikström, K. (2008). Defining uncertainty in projects: A new perspective. International Journal of Project Management, 26(1), 73-79. https://doi.org/10.1016/j.ijproman.2007.08.005

Project Management Institute. (2021). A guide to the project management body of knowledge (PMBOK guide) (7th ed.). Project Management Institute.

Ward, S., & Chapman, C. (2003). Transforming project risk management into project uncertainty management. International Journal of Project Management, 21(2), 97-105. https://doi.org/10.1016/S0263-7863(01)00080-1