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MethodFinance & AccountingPlanning & modellingIntermediate

Build an annual operating budget

A departmental budget built from drivers, reconciled to targets, with phasing by month.

This is a practical, copy-paste process for annual planning season.. Use it when you want a clear structure, then add your own details and the linked evidence.

Published by Deepstory Research. Reviewed Sep 2026.

How to use this method

  1. 1. Copy or downloadCopy the prompt below, or download the method file and attach it to your chat.
  2. 2. Paste into any AIChatGPT, Claude, Gemini or Copilot. Replace each [PLACEHOLDER] with your details, or let the AI ask you.
  3. 3. Add evidenceAttach the evidence files listed on this page so the AI works from sourced numbers, not guesses.

The prompt

Paste it as-is. The AI will ask for anything still in [BRACKETS].

Download .md
# Build an annual operating budget
Method by Deepstory Research: deepstoryresearch.com/method/annual-budget

You are an FP&A lead running the annual budget cycle. Follow the method below step by step. Goal: A departmental budget built from drivers, reconciled to targets, with phasing by month.

## My inputs
- Last year’s actuals: [LAST_YEAR_S_ACTUALS]  (example: attach)
- Growth targets: [GROWTH_TARGETS]  (example: revenue +25%)
- Known changes: [KNOWN_CHANGES]  (example: new office, 6 hires)
- Inflation or price assumptions: [INFLATION_OR_PRICE_ASSUMPTIONS]  (example: 5% wage inflation)

Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source.

## Steps to follow
1. Set top-down targets.
2. Build bottom-up revenue and cost by department from drivers.
3. Reconcile gaps between top-down and bottom-up.
4. Phase monthly with seasonality.
5. Summarise P&L, capex and headcount.

## Deliver the output in this structure
- Assumptions
- Department budgets
- Monthly phasing
- Budget P&L
- Reconciliation notes

## Quality rules
- State inflation assumptions explicitly.
- Separate one-off from recurring items.
- Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION.
- If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED].
- End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.

What you need to give the AI

InputPlaceholderExample
Last year’s actuals[LAST_YEAR_S_ACTUALS]attach
Growth targets[GROWTH_TARGETS]revenue +25%
Known changes[KNOWN_CHANGES]new office, 6 hires
Inflation or price assumptions[INFLATION_OR_PRICE_ASSUMPTIONS]5% wage inflation

Use it when

  • Annual planning season.
  • A new business unit needs its first budget.

What you get

  • Assumptions
  • Department budgets
  • Monthly phasing
  • Budget P&L
  • Reconciliation notes

The procedure, step by step

Read this before you run it, so you can check the AI actually followed the method.

  1. 1

    Set top-down targets.

  2. 2

    Build bottom-up revenue and cost by department from drivers.

  3. 3

    Reconcile gaps between top-down and bottom-up.

  4. 4

    Phase monthly with seasonality.

  5. 5

    Summarise P&L, capex and headcount.

Quality checks built into the prompt

  • • State inflation assumptions explicitly.
  • • Separate one-off from recurring items.
  • • Every number labelled FACT, ESTIMATE or ASSUMPTION; claims outside attached evidence tagged [UNVERIFIED].

Evidence to use with this method

Methods tell the AI how to think. Evidence gives it sourced numbers to think with. Download a context file and attach it with the prompt.

EvidenceFinance

US Inflation & the Fed

The full 2026 inflation story on one page: the CPI path and category breakdown, the mid-year turn and the still-rising core PCE outlook, and the Fed’s rate response — fed funds, the 10-year Treasury, and the 30-year mortgage.

Open evidenceDownload context file

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Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment decisions need a qualified professional.