Budget variances explained

How can variances between budget and actuals be turned into a clear, verifiable commentary that is useful to the finance manager?

1250 € per session, excl. VAT

In short

This half-day session of 3 hours explores how generative AI can help explain budget variances without inventing their causes. Using a fictitious case, participants check the figures, distinguish facts from hypotheses, then produce a concise commentary accompanied by a checklist.

Why this training?

A budget commentary must do more than simply rephrase a table: it prioritises variances, explains their significance and indicates what warrants investigation. However, a numerical change alone is not enough to establish its cause. AI can suggest a structure and simplify wording, but it can also produce a plausible explanation without evidence. The training teaches participants to set boundaries for this writing support and retain human financial validation before any circulation. Running case study: The fictitious organisation « Dorseline Conditionnement » is preparing its monthly review for June. Its cost budget totals 200 000 €, compared with actual costs of 218 000 €. The file provides details of purchasing, transport and staffing, with notes on an exceptional delivery and overtime. Some causes are deliberately left undocumented. Transfer to the workplace: At a future budget review, reuse the framework within a limited, authorised scope. Compare the draft with the commentary reviewed by a qualified finance professional, then record corrections to figures, causal links and wording.

Objectives of this training

  • Identify significant variances between budget and actuals.
  • Calculate a variance in value and percentage terms using an explicit convention.
  • Distinguish between a numerical finding, a documented cause and a hypothesis.
  • Formulate a request to AI limited to the available information.
  • Write and check a commentary intended for a finance manager.

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Management assistants and accounting staff contributing to monthly reporting.
  • Operational managers required to explain expenditure within their area of responsibility.

Prior skills

  • No prior knowledge of AI required.
  • Ability to read a simple cost table and understand the distinction between budget and actuals.

What you will work on

  1. Read the variances before commenting

    Objective: Establish a reliable numerical baseline. Variance calculated as actuals minus budget; percentage relative to the budget; distinction between the arithmetic sign and whether a cost is favourable or unfavourable.

  2. Separate evidence from assumptions

    Objective: Recognise the limitations of a generated explanation. Simple introduction to generative AI; risk of invented causes; distinction between a fact, a documented explanation and missing information.

  3. Guide an initial draft

    Objective: Obtain a draft that is faithful to the file. Instruction specifying recipient, period, units, length and sources; structure covering findings, explanations and points requiring attention; prohibition on filling in missing data.

  4. Review before sending

    Objective: Assess the quality of the commentary produced. Checking figures, traceability of causes, readability and cautious wording; the role of human financial validation.

What you take away

  • Table of verified and prioritised variances.
  • Writing instruction for AI prohibiting invented causes.
  • Budget commentary of 150 to 200 words.
  • Completed review checklist and questions still to be investigated.

Method and assessment

  • Short inputs followed by immediate practice using the running 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: Arrange access to a generative AI assistant authorised by the organisation; no confidential data will be needed. Provide the fictitious table, explanatory notes and a calculator or spreadsheet to verify the variances.

Observable criteria: Amounts and percentages match the table; the denominator and sign convention are explicit. ; The main variances are presented in a justified order. ; Each asserted cause is linked to a note in the file; hypotheses are flagged. ; The commentary distinguishes between findings, available explanations and points to check. ; The checklist identifies the corrections needed before validation by a qualified professional..

Frequently asked questions

Do you need prior knowledge of AI to participate?

No. First-time use is guided using the budget table provided.

Can real figures be used?

The exercises use fictitious or anonymised cases, exclusively within tools authorised by the organisation.

What should you do if a cause is missing?

Flag the missing information and formulate a question; do not turn a hypothesis into a definitive explanation.

Can the commentary trigger a decision?

No sensitive decisions are automated. The text must be validated by a qualified finance professional before circulation.

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