Reasoned financial decision appraisals

How can you compare three operating assumptions without confusing profitability, cash position and uncertainty?

1250 € per session, excl. VAT

In short

In a half-day session lasting 3 hours you use generative AI to clarify assumptions, analyse their financial effects and prepare a conditional recommendation. Working from a fictional case file, you produce a checked numerical comparison in a spreadsheet, a sensitivity test and a briefing note submitted for professional validation.

Why this training?

A financial comparison becomes misleading when scenarios use different periods, units or conventions. Distinguishing between commercial assumptions, cost mechanisms and payment timing differences makes the variances interpretable. AI can help rephrase assumptions and challenge a conclusion, but a plausible explanation does not prove that a calculation is correct. The training separates assisted preparation, verifiable calculation and professional judgement, without automating any sensitive decisions. Case study used throughout: The fictional company « Talvène Conditionnement » is considering expanding production. Over twelve months, participants examine three operating scenarios incorporating volumes, prices, variable costs, fixed costs, initial investment and collection periods. They must explain why the most profitable scenario may also create the greatest cash requirement. Transfer to the workplace: At your next budget review, reuse the framework within an authorised, anonymised scope, update the assumptions and have the calculations checked by a qualified financial professional before using them to inform any decisions. Record corrections to improve the requests addressed to AI.

Objectives of this training

  • Define an identical scope and conventions for three scenarios.
  • Structure the assumptions and document their sources.
  • Calculate variances in operating profit and cash position.
  • Test sensitivity to a change in volume or customer payment period.
  • Write a conditional recommendation distinguishing between facts, assumptions and limitations.

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Management accountants and financial analysts preparing budget reviews.
  • Business managers accustomed to commenting on a budget and a cash flow forecast.

Prior skills

  • Have already used a generative AI assistant for a simple task.
  • Understand revenue, margin, fixed costs and cash flows.
  • Be able to edit formulae and check references in a spreadsheet.

What you will work on

  1. Establishing comparison conventions

    Objective: Establish a consistent and traceable basis. Monthly time horizon, units, opening balance, distinction between profit and cash receipts; identification of missing data.

  2. Building and verifying the comparison

    Objective: Produce indicators calculated on a common basis. Revenue, contribution margin, operating profit, monthly cash flows and lowest cash balance.

  3. Testing the decisive assumptions

    Objective: Identify what could reverse the preference. Sensitivity to a single variable, consistency between assumptions and distinction between an adverse scenario and a certain forecast.

  4. Formulating a verifiable decision appraisal

    Objective: Present a substantiated conclusion without concealing uncertainty. Preference criteria, liquidity risks, caveats and human validation process.

What you take away

  • Register of assumptions and financial conventions.
  • Comparison table of the three scenarios with verified formulae.
  • Documented sensitivity matrix.
  • Conditional decision appraisal note and completed checklist.

Method and assessment

  • Short teaching inputs followed by immediate practice using the ongoing case study.
  • Individual work followed by work in pairs, with peer review of the outputs.
  • Guided group discussion: what works, what needs correcting and what remains a human decision.
  • Preparation: Have spreadsheet software and access to generative AI authorised by the organisation. Read the fictional case file provided; any additional examples must be anonymised and authorised for sharing.

Observable criteria: The three scenarios share the same period, units and calculation conventions. ; Each modified assumption is identified and linked to the case file or flagged as a supposition. ; Key indicators are recalculated independently of the generated text; any variance is explained. ; The sensitivity test isolates one variable and quantifies its effect. ; The recommendation distinguishes between profitability, liquidity, limitations and validation conditions..

Frequently asked questions

Does AI perform the final calculations?

No. The reference calculations remain in the spreadsheet and are checked independently.

Can we use our actual budgets?

The exercises use fictional or anonymised cases, exclusively in tools authorised by your organisation.

Does the comparison prescribe a winning scenario?

No. It clarifies the trade-offs and the conditions that could change the preference.

Who validates the recommendation before use?

A qualified financial professional checks the assumptions, calculations and interpretation before any decision is made.

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