BUS 6573 Module 3 Scenario and Sensitivity Analysis Example

What If the Robots Save Less? Scenario, Sensitivity and Staging Analysis of a $140 Million Automation Decision

Student Name

American College of Education

BUS6573: Enterprise Financial Strategy and Operations

Module 3 Assignment

Instructor Name

September 2, 2030

Introduction

My valuation in the second module put the automation program about $21 million in the black at an 8 percent hurdle, with a return near 11 percent and its cost recovered in roughly six years. Those figures rest on forecasts of savings, cost, timing and the discount rate, each of which could prove wrong. This paper tests the decision under uncertainty. It varies the key assumptions one at a time, combines them into weighted scenarios, considers why forecasts of this kind tend to be optimistic and examines whether staging the investment could reduce risk and raise value.

Why Test the Forecast

Graham and Harvey (2001) found that sensitivity analysis is among the risk adjustments chief financial officers frequently use alongside discounted cash flow. Testing matters especially for projects whose value depends on a few uncertain inputs. Kahneman and Lovallo (1993) traced overconfident projections to a habit of reasoning from the details of the plan at hand, what they called the inside view, instead of asking how comparable ventures have actually turned out, the outside view. Engineering estimates for Cumberland's program come from a single pilot line and vendor quotes, the kind of inside view their argument warns about.

One Variable at a Time

Varying each assumption alone, with others at their base values, shows which matter most. If full-year savings are 25 percent lower, $21 million instead of $28 million, the net present value falls to negative $12.8 million and the return to 6.1 percent; if 25 percent higher, value rises to $54.7 million. A 15 percent capital cost overrun, to $161 million, cuts value to $3.4 million. A one-year delay before savings begin reduces value to $1.9 million. If savings grow 3 percent a year with wages, value rises to $38.9 million. At a 7 percent discount rate value is $29.0 million, and at 10 percent it is $6.6 million.

What the Sensitivities Show

The program's value is most sensitive to savings and to timing. A shortfall of about 15 percent in savings, a cost overrun somewhat above 15 percent or a one-year delay each brings the net present value close to zero. By contrast, a plausible change in the discount rate moves value less. Wage growth, which the base case ignored, works in the program's favor, since each avoided hour of labor becomes more valuable over time. These results direct management attention to the reliability of the savings estimate and to execution.

Combining Assumptions Into Scenarios

Real outcomes rarely vary one assumption at a time; problems tend to come together. Three scenarios were therefore defined with operations and engineering staff. The downside combines savings 25 percent below plan, a 15 percent capital overrun and a one-year delay, as might occur if integration with existing lines proves difficult. The base case uses the original assumptions. The upside assumes savings of $31 million rising 3 percent a year as wages climb. Their net present values are negative $44.7 million, $21.0 million and $55.2 million, with internal rates of return of 2.2, 11.0 and 15.3 percent.

Weighting the Scenarios

Management assigned probabilities of 25 percent to the downside, 50 percent to the base case and 25 percent to the upside, reflecting the pilot line's mixed results in its first months. Probability-weighted value comes to 0.25 times negative $44.7 million plus 0.50 times $21.0 million plus 0.25 times $55.2 million, or about $13.1 million. The program remains attractive on an expected basis, but there is roughly a one-in-four chance of losing substantial value, which the board should weigh against the company's limited capacity to absorb losses.

Correcting for Optimism

Research on large capital projects suggests the downside may deserve more weight. Flyvbjerg (2014) documented that large projects across many sectors commonly overrun their budgets and fall short of promised benefits, and argued for reference class forecasting, adjusting estimates using the record of similar past projects. Cumberland's own history includes a 2019 packaging line upgrade that came in 18 percent over budget and six months late. Applying that experience, the downside scenario is plausible rather than pessimistic, which strengthens the case for reducing exposure if possible.

Staging as a Real Option

The analysis so far treats automation as a single all-or-nothing commitment. McGrath (1999) argued that firms can learn cheaply by making modest first commitments that open, without requiring, larger later ones, which caps losses while preserving upside. Cumberland could automate the Murfreesboro plant first for $70 million and decide a year later whether to automate Cookeville, by which time the first plant's actual savings, cost and ramp-up will be known.

Valuing the Staged Approach

Under staging, the first plant's net present value is about $12.2 million in the base case, negative $20.6 million in the downside and $29.4 million in the upside. If results are base or upside, the second plant proceeds a year later at roughly the same value discounted by one year; if downside, it is canceled. With the same weights, staging is worth about $20.8 million on average, compared with $13.1 million for committing to both plants at once. Staging adds roughly $7.7 million of expected value by cutting the loss in the downside, at the cost of a year's delay in the upside.

Additional Safeguards

Several practical steps can further reduce risk. Fixed-price contracts with the equipment vendor, with penalties for late delivery, would limit overruns. Holding back a portion of payment until lines meet throughput targets would align the vendor's incentives with the company's. And tracking savings monthly against the plan from the first day of operation would give the board early warning, informing the decision on the second plant.

What the Board Should Watch

The analysis suggests three indicators for the board. Monthly labor hours avoided per line will show whether the core savings assumption holds. Weekly throughput during ramp-up will reveal delays early. And spending against the fixed-price contract will flag overruns. If the first plant's savings in its first six months run more than 15 percent below plan, the board should treat that as a signal to reconsider the second plant.

Limits of the Analysis

Scenario probabilities reflect management judgment rather than statistical estimates, and different weights would change the expected values. The staging calculation is simplified, treating the second plant's value as the first plant's value delayed one year. And the analysis does not include possible strategic benefits of automation, such as the ability to produce new allergen-free lines, which could add value beyond cost savings. These limits do not alter the main conclusion but suggest results should be read as ranges.

Conclusion

Testing the automation decision shows that its value depends most on savings and timing, with modest shortfalls or delays erasing it. Weighted scenarios give an expected net present value of about $13.1 million, with a meaningful chance of loss, and the company's own history suggests the downside is realistic. Staging the investment, automating one plant first, raises expected value to about $20.8 million by allowing the company to stop if results disappoint. The next module weighs the ethical, governance and sustainability dimensions of the decision.

References

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

Graham, J. R., & Harvey, C. R. (2001). The theory and practice of corporate finance: Evidence from the field. Journal of Financial Economics, 60(2-3), 187-243. https://doi.org/10.1016/S0304-405X(01)00044-7

Kahneman, D., & Lovallo, D. (1993). Timid choices and bold forecasts: A cognitive perspective on risk taking. Management Science, 39(1), 17-31. https://doi.org/10.1287/mnsc.39.1.17

McGrath, R. G. (1999). Falling forward: Real options reasoning and entrepreneurial failure. Academy of Management Review, 24(1), 13-30. https://doi.org/10.2307/259034