BUSI 650 Week 6 DB Forum 3: Replies Example

Discussion Board Forum 3: Replies

BUSI 650 Operations Management, Discussion Board Forum 3: Replies (two)

Thread by [Student Name]

The two classmates and their threads are composites standing in for the forum's own posts; the textbook and research cited are real, and the requirements follow Liberty's public course guide for BUSI 650.

Reply to Courtney

Courtney, your thread described the new patient tower at your hospital, now nine months behind schedule and 22 percent over its approved budget, and you attributed the problem mainly to the contractor. The contractor may share the blame, but research suggests the overrun was likely built into the plan from the start. Your thread mentioned that the board approved the tower after two rounds of cost cuts to the estimate, which is itself a warning sign: estimates that shrink to win approval rarely shrink in reality.

Flyvbjerg (2014) reviewed research on megaprojects and summarized its central finding in what he calls an iron law: big projects run late and cost more than planned, and they do so repeatedly. He explains the pattern partly through what he calls survival of the unfittest, in which projects with optimistic estimates are more likely to be approved than realistic ones, so the projects that get built are often those whose costs were understated. A hospital tower is smaller than the megaprojects he studied, but the same dynamics, optimistic estimates and pressure to win board approval, apply.

Meredith and Shafer (2016) present project management tools such as the critical path and time-cost trade-offs, which help control a project once it is underway. The research suggests a different fix for the remaining phases: compare the hospital's estimates with the actual outcomes of similar hospital projects and adjust them accordingly, an approach Flyvbjerg has advocated, rather than relying on a bottom-up estimate alone. An estimate built from the project's own plan inherits the plan's optimism.

Does your hospital have data on how its earlier construction projects compared with their budgets? That history would be the place to start.

Reply to Marcus

Marcus, your thread argued that your beverage distributor's sales managers should stop overriding the statistical forecast, because their changes seem to make shortages and overstocks worse. Your frustration is understandable, especially after the summer when your warehouse ran out of a best-selling sports drink, and the research supports part of your conclusion.

Fildes et al. (2009) analyzed more than 60,000 forecasts and outcomes from four supply chain companies. They found that managers adjusted forecasts frequently. Large adjustments, typically based on information such as a promotion or a new account, tended to improve accuracy, whereas minor tweaks seldom helped and frequently hurt. Upward adjustments were less likely to help than downward ones, consistent with optimism among people close to sales.

That suggests a rule instead of a ban. Your distributor could permit adjustments above a threshold, perhaps 10 percent, when a manager records the reason, and compare, product by product each month, how close the adjusted and the untouched forecasts came to actual sales. Meredith and Shafer (2016) note that forecast error should be measured and monitored, and this rule would make the managers' contribution measurable. A summer promotion with a grocery chain is exactly the information a statistical model cannot see.

Two further steps would help. First, the distributor could show each manager a quarterly report of how their own adjustments performed, which turns the rule into feedback rather than policing. Second, it could separate the forecast from the sales target, since managers who are measured on hitting a number have reason to push the forecast toward it. Do your sales managers currently document why they change a forecast?

References

Fildes, R., Goodwin, P., Lawrence, M., & Nikolopoulos, K. (2009). Effective forecasting and judgmental adjustments: An empirical evaluation and strategies for improvement in supply-chain planning. International Journal of Forecasting, 25(1), 3-23. https://doi.org/10.1016/j.ijforecast.2008.11.010

Flyvbjerg, B. (2014). What you should know about megaprojects and why: An overview. Project Management Journal, 45(2), 6-19. https://doi.org/10.1002/pmj.21409

Meredith, J. R., & Shafer, S. M. (2016). Operations and supply chain management for MBAs (6th ed.). Wiley.