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PROJECT 16Advanced

Three-Scenario Financial Model

Business scenario

Orion is considering opening two new stores in 2026. The board wants to see the P&L impact under base, upside and downside assumptions.

Problem statement

Build a driver-based 2026 monthly P&L model with explicit assumptions and scenarios, and test sensitivity of net profit to key drivers.

Learning objectives

  • Design a driver-based model
  • Implement switchable scenarios
  • Run and present sensitivity analysis

Instructions

Drivers: revenue growth of existing business, new-store ramp-up curve, gross margin %, opex per store, capex and depreciation. All inputs on one assumptions sheet; scenario selector cell; no hard-coded numbers in calculation sheets.

Tasks

  1. Baseline from 2025 actuals.
  2. Assumptions sheet with three scenarios.
  3. Monthly 2026 P&L to net profit.
  4. Two-way sensitivity table (gross margin × growth).
  5. Tornado chart of ±10% driver changes.
  6. Board summary.

Deliverables

  • Excel model
  • Board summary

Evaluation rubric

CriterionWeightExcellentProficientDevelopingInsufficient
Model integrity30%Fully driver-based, auditable, no hard-codes, checks included.Correct and complete with minor gaps in rigour or presentation.Partly correct; important steps missing, unvalidated or unclear.Missing, incorrect, or not supported by the data.
Scenarios & sensitivity25%Correctly implemented and interpreted.Correct and complete with minor gaps in rigour or presentation.Partly correct; important steps missing, unvalidated or unclear.Missing, incorrect, or not supported by the data.
Assumption quality15%Assumptions justified from 2025 data.Correct and complete with minor gaps in rigour or presentation.Partly correct; important steps missing, unvalidated or unclear.Missing, incorrect, or not supported by the data.
Interpretation & recommendations15%Clear trade-offs for the board.Correct and complete with minor gaps in rigour or presentation.Partly correct; important steps missing, unvalidated or unclear.Missing, incorrect, or not supported by the data.
Presentation15%Concise, well-labelled outputs a manager can act on without explanation.Correct and complete with minor gaps in rigour or presentation.Partly correct; important steps missing, unvalidated or unclear.Missing, incorrect, or not supported by the data.