FIN 360 Week 5 Scenarios and a Decision Recommendation Example

Reviewed by Davina Cresswell, MBA · University of Phoenix · Updated

This FIN 360 Week 5 example uses the completed financial model to test scenarios and turn the results into a recommendation. University of Phoenix FIN 360 closes with scenarios and a decision recommendation, and in this final FIN/360 assignment BS in Finance students show that a model's value lies in the questions it can answer, not the single forecast it produces. The coffee chain's owners asked whether they can open twelve cafés in three years without new equity. The paper defines base, downside and upside scenarios from the drivers identified as least certain, runs each through the model, builds a two-way sensitivity table for same-café growth and food costs, compares three expansion paths, including a paced plan tied to results, and recommends the path that balances growth with covenant safety, presented as a short memo to the owners and their bank.

CourseFIN 360 Financial Data Modeling (FIN/360)
Week5
Paper typeScenario analysis and recommendation paper
Lengthabout 1,003 words, 4 double-spaced pages plus title page and references
FormatAPA 7 student paper
SchoolUniversity of Phoenix
ProgramBS in Finance
UpdatedSeptember 2026

Free sample paper for FIN 360 Week 5

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Twelve Cafés, Ten or Twelve Paced? Base, Downside and Upside Scenarios, a Two-Way Sensitivity Table and a Recommendation to the Coffee Chain's Owners and Their Bank

[Student Name]

University of Phoenix

FIN/360: Financial Data Modeling

Week 5 Assignment

[Instructor Name]

[Date]

The coffee chain and all figures are composites written for a model paper; methods and research findings come from the sources listed.

What this part is doingThe title lists the three plans compared, which is the decision the model was built to inform.
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Over four weeks, the coffee chain's model gained a structure, drivers, forecast statements and schedules with monthly covenant tests. In the base case, twelve openings over three years fit within the chain's credit line and covenants. The owners now ask how confident they can be and whether a different pace would be wiser. A single forecast answers what will happen if the assumptions are right; scenarios answer what happens if they are not, which is the question owners actually face. This paper uses the model to answer it.

Building the Scenarios

The historical analysis identified same-café growth and food costs as the least certain drivers, and new-café ramp-up as a secondary uncertainty for openings in a new city. The scenarios vary these together in plausible combinations.

The base case uses same-café growth of 2.5%, cost of goods sold of 30.5% and the historical ramp. The downside assumes a softer economy and competition: same-café growth of zero, cost of goods sold of 32% as coffee prices stay high and new cafés reaching only 90% of mature sales by year three. The upside assumes same-café growth of 4%, cost of goods sold of 29.5% as coffee prices ease and the historical ramp.

Results for Twelve Cafés

In the base case, net income rises from about $6.0 million to $8.3 million, the revolver peaks at about $2.1 million and the tightest fixed charge coverage is about 1.42. In the upside, net income reaches about $9.7 million, the revolver peaks under $1 million and coverage never falls below 1.6. In the downside, net income is about $4.1 million in year two, the revolver peaks near $5.4 million and fixed charge coverage falls to about 1.18 in the summer of year two, breaching the 1.25 covenant.

What this part is doingReporting peak borrowing and the tightest covenant, not only profit, puts the results in the terms a lender uses.
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A Two-Way Sensitivity Table

To see how the two main drivers interact, the model computed the lowest fixed charge coverage for combinations of same-café growth from minus 1% to 4% and cost of goods sold from 29.5% to 32.5%. The table shows a boundary: coverage stays above 1.25 as long as same-café growth is at least 1% when food costs are 31%, or at least 2% when food costs are 32%. Below that line, twelve openings on the base schedule would breach the covenant. The owners can compare the line with current trends each quarter, since the choice between growth and safety depends mostly on where results fall relative to it (Brigham & Houston, 2022).

Three Expansion Paths

The model compared three paths. Plan A opens twelve cafés on the base schedule. Plan B opens ten, dropping two in year three, a simpler but less flexible compromise. Plan C, paced, opens four in year one and then four in each later year only if trailing same-café growth is at least 1.5% and fixed charge coverage at least 1.40 at the time of commitment; otherwise it opens two.

In the base and upside cases, Plans A and C produce identical results, and Plan B produces less profit by year three. In the downside, Plan A breaches the covenant, Plan B comes close at about 1.26 and Plan C, which would open only two cafés in each of years two and three, keeps coverage above 1.32 and the revolver below $3.5 million.

What this part is doingComparing paths across scenarios shows that pacing preserves the upside while avoiding the downside breach, which a single plan could not show.
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Recommendation

The owners should adopt Plan C, the paced plan. It captures the full expansion if conditions resemble the base or upside cases and protects the covenant if they deteriorate. The triggers are measurable from monthly reports the controller already prepares, so no new data are needed. The owners should also ask the bank to reset the fixed charge covenant to 1.20 for the expansion period, which the downside results suggest would provide a useful cushion and which the paced plan makes a reasonable request. Graham and Harvey (2001) found that sensitivity and scenario analysis are widely used by financial officers to evaluate projects, and presenting the paced plan with its triggers gives the bank the same kind of evidence.

Limitations

The model simplifies. It uses average ramp-up curves, assumes rent terms like current leases and treats headquarters costs as mostly fixed. It does not model a severe recession or the loss of the roastery. The downside is a plausible stress, not a worst case. Results are only as current as the inputs, so the model should be updated quarterly with actual results.

Maintaining the Model

The controller will own the model, update actuals monthly and rerun the scenarios before each opening decision. Changes to structure will follow the version control process set in week one, and the bank will receive the updated covenant projection each quarter (Benninga, 2014).

Conditions That Would Shift the Advice

This advice assumes the downside is a realistic stress, not a remote one. If the bank declines to reset the covenant, the owners should add a condition to Plan C: no year-three openings unless coverage has stayed above 1.45 for six months. If a better-capitalized competitor announces cafés in the chain's core markets, the owners should run a new scenario with lower same-café growth before committing to year two. If coffee prices fall sharply, the upside case becomes more likely and the owners could consider accelerating year-three openings.

Communicating the Result

The memo to the owners and bank is two pages: the question, the three scenarios in a small table, the sensitivity boundary, the three plans, the recommendation with triggers and the limitations. The spreadsheet supports the memo but is not the message, and the bank's analyst receives the file separately to test the assumptions.

Conclusion

In the base case, twelve cafés fit within the chain's resources, but a plausible downside would breach its main covenant. A paced plan that opens four cafés a year only when same-café growth and coverage meet set triggers keeps the upside and avoids the breach. The model's value was in comparing futures, not predicting one.

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References

Benninga, S. (2014). Financial modeling (4th ed.). MIT Press.

Brigham, E. F., & Houston, J. F. (2022). Fundamentals of financial management (16th ed.). Cengage.

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

What the FIN 360 Week 5 instructions ask

FIN 360 Week 5 usually asks students to use their model for scenario and sensitivity analysis and to make a recommendation. Typical requirements include defining scenarios based on key uncertainties, running them through the model, presenting results such as net income, cash, borrowing and covenant ratios, performing sensitivity analysis on the most important drivers, comparing alternative plans and writing a recommendation for a decision maker. Some prompts ask for a presentation or memo to a specific audience, such as owners or lenders. Explain how the scenarios were built, summarize results in plain language, discuss risks and limitations and support the analysis with modeling and finance research referenced in APA form. Instructors often value a recommendation with explicit triggers.

How this FIN 360 Week 5 example is built

With the model complete and checked, the owners' question can finally be answered, and the paper does so in the form a decision maker needs. Scenarios are built from the two drivers flagged as least certain in the historical analysis, with a third for new-café ramp-up. Results are summarized in prose for the measures that matter: peak borrowing, the tightest covenant and profit. A two-way sensitivity table shows combinations of the two main drivers. Three expansion paths are compared under each scenario. The recommendation is a paced plan with explicit, measurable triggers, and the paper closes with the conditions that would shift the advice, the model's limitations and how it should be maintained.

FIN 360 Week 5 grading rubric: where the points go

Graders for this final week tend to reward scenarios grounded in the key drivers, clear presentation of results, sensitivity analysis on the right variables and a recommendation that follows from the evidence. Faculty check that scenarios change the uncertain drivers consistently, that results focus on decision-relevant measures such as cash, borrowing and covenants, that alternatives are compared and that limitations are acknowledged. A recommendation with conditions or triggers shows maturity. Communication matters: results should be understandable to the owners and lender without opening the spreadsheet. Clear writing and APA references to modeling and finance research complete the grade, along with a plan for keeping the model current.

FIN 360 Week 5 help: mistakes to avoid

Many FIN 360 Week 5 papers run scenarios that change every driver at once, making it impossible to tell what drives results. Base scenarios on the few uncertain drivers and change them consistently. Another is reporting only profit; lenders care about cash, peak borrowing and covenants. Students also present a recommendation with no conditions, as if the forecast were certain. Tie the plan to triggers. Include a sensitivity table for the two most important drivers. Compare alternatives rather than judging one plan alone. Acknowledge limitations and what the model leaves out. Finally, write for the decision maker, with numbers in plain language and the spreadsheet as support.

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FIN 360 Week 5 questions, answered

What does FIN 360 Week 5 usually cover?

It usually covers using a financial model for scenario and sensitivity analysis and presenting a recommendation to decision makers.

Where can I find a free FIN 360 Week 5 sample paper?

This page presents the coffee chain's scenarios, sensitivity table and paced expansion recommendation with margin notes, and reading it costs nothing. Send your own model's question for a free opening draft.

What is the difference between scenario and sensitivity analysis?

Scenario analysis changes several related assumptions together to describe a possible future; sensitivity analysis changes one or two assumptions to see how much results depend on them.

Which results should a scenario analysis report?

The measures that matter to the decision, often cash, peak borrowing, covenant ratios and profit, rather than every line of the statements.

What makes a model-based recommendation credible?

Clear assumptions, tested scenarios, a comparison of alternatives, stated limitations and conditions or triggers that would change the recommendation.

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