Test budget assumptions

Which assumptions really tip the balance of your budgeted result, and how can you verify their impact using AI?

1960 € per session, excl. VAT

In short

In one 7-hour day, excluding breaks, build a verifiable budget sensitivity analysis. You will prepare the assumptions, calculate their individual and combined effects, then rank the risks. Generative AI will assist with formulating tests and producing the synthesis, without replacing calculations or financial validation.

Why this training?

A budget that is balanced in the base scenario can move into deficit after a limited change in volumes or purchasing costs. Without an explicit model, teams often confuse the impact on revenue, the effect on margin and the consequences for profit. Generative AI makes it easier to critique assumptions and draft commentary, but may suggest incorrect calculations or inconsistent scenarios. The course separates suggestions, reproducible calculations and financial judgement to make every conclusion traceable. Running case study: The fictitious company Torvane Agencement is preparing its annual budget: 12 000 units sold at 150 euros, a variable unit cost of 90 euros and 540 000 euros in fixed costs. Management wants to compare the effects of a fall in volumes, a sales discount and an increase in purchasing costs. Application at work: Apply the matrix to an authorised budget in your area of work, have the variation ranges validated by those responsible for them and arrange a financial review before making any trade-off decisions. Then update the sensitivities when sales or purchasing assumptions change.

Objectives of this training

  • Map the variables and relationships in a budget model
  • Justify the variation ranges for the selected assumptions
  • Calculate individual sensitivities and combined effects
  • Rank factors according to their impact on profit
  • Draft a decision paper distinguishing findings, assumptions and limitations

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Management accountants and financial analysts responsible for budgeting exercises
  • Operational managers preparing a budget with their finance department

Prior skills

  • Have a sound understanding of revenue, contribution margin and fixed costs
  • Be able to build formulae and references in a spreadsheet
  • Have already used a generative AI assistant for a professional task

What you will work on

  1. Define the scope of the economic model

    Objective: Link the assumptions to the profit measure being monitored. Scope, annual time horizon, units; distinction between profit and cash flow.

  2. Assess uncertain assumptions

    Objective: Select plausible, documented variations. Controllable factors, external uncertainties, asymmetric ranges and economic dependencies.

  3. Measure individual effects

    Objective: Calculate the individual effect of each factor. Varying one parameter at a time, absolute and relative differences, bases for comparison.

  4. Combine without double counting

    Objective: Test economically coherent scenarios. Combining price and volume, multiplicative interactions; distinguishing an adverse scenario from a forecast.

  5. Prioritise vulnerabilities

    Objective: Identify the factors and thresholds to monitor. Ranking of impacts, influence of the selected ranges, zero-profit threshold.

  6. Present findings to support trade-off decisions

    Objective: Produce a traceable financial synthesis. Cell references, model limitations and validation process.

What you take away

  • Assumptions register with ranges, justifications and owners
  • Parameterised budget model and checks log
  • Sensitivity matrix and ranking of factors
  • Decision paper with scenarios, alert thresholds and limitations

Method and assessment

  • Short teaching inputs followed immediately by practical work on the running case study.
  • Individual work followed by work in pairs, with peer review of outputs.
  • Guided group discussion: what works, what needs correcting and what remains a human decision.
  • Preparation: Arrange a spreadsheet and access to an AI assistant authorised by the organisation Identify three budget assumptions being discussed in your area of work; use only fictitious or anonymised data during the exercises

Observable criteria: The base scenario produces a profit of 180 000 euros; Each variation has a unit, a justified range and an assumption that other factors remain unchanged; Key impacts are recalculated in the spreadsheet and reconciled with the commentary; Combined scenarios make interactions explicit without mechanically adding individual impacts; The paper distinguishes facts, assumptions and recommendations subject to financial validation.

Frequently asked questions

Does AI perform the reference calculations?

No. Reference calculations remain in the spreadsheet; every proposed formula is tested.

Can you use a confidential budget?

The exercises use fictitious or anonymised cases, only in tools authorised by the organisation.

Do the scenarios indicate a probability of loss?

No. They measure conditional consequences without assigning unjustified probabilities.

Does the paper enable automated trade-off decisions?

No. No sensitive decisions are automated; the conclusions require validation by a qualified finance professional.

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