ChatGPT for business Excel analysis: from file to report

ChatGPT can help combine system exports, identify discrepancies and prepare a spreadsheet report. A manager benefits when they can check changes in sales or order fulfilment sooner. The report needs to preserve metric definitions and make the source of each figure traceable.

Start with one recurring report, such as weekly sales by branch. This guide covers files used in ChatGPT and ChatGPT Work. An add-in operating directly inside Excel is a separate product choice whose availability and billing should be checked before purchase.

Prepare the inputs and definitions

Collect the transaction export, a product or branch lookup table and a description of the required result. Decide whether sales means orders, issued invoices or received payments. Specify how returns are handled, the date range and the currency. Without those decisions, two correctly totalled spreadsheets can answer different questions.

ChatGPT Work can analyze attached CSV files and Excel workbooks and create reports for review. OpenAI describes the workflow in its data analysis guide. File analysis does not establish compatibility with every macro, external connection or workbook calculation behaviour. Test the elements your report depends on.

Limit the input to information needed for the analysis. Sales by branch usually does not require customer addresses or phone numbers. The data must be approved for the chosen environment under the company's rules.

Check the join before drawing conclusions

Suppose an export contains 1,000 transaction lines and the product lookup has two rows with the same identifier. Joining on that identifier can duplicate transactions and overstate sales. A chart alone will not reveal why.

Request row counts and totals before and after the join. Define what happens to products without a match. Do not ask to remove duplicates without defining a unique record: two lines on the same invoice can be separate items that must remain.

OpenAI's spreadsheet consolidation guide also covers join rules and checking the next refresh.

Instructions for a first report

The following example needs your file names and business definitions. It sets the order of work; the resulting workbook still needs review.

Prepare a sales-by-branch report from the attached files. First list the columns and check the identifiers used for joining. Show duplicate keys, unmatched records and control totals. Preserve the source files. Use the sales definition in the attached instructions. Return a separate workbook containing the result, an exceptions sheet and refresh instructions. If a definition is incomplete, identify the decision needed.

Open the generated workbook in the application your team uses. Check formulas and selected rows against the source. Figures shown in a preview are insufficient evidence that the whole workbook works correctly.

Test next week's files

Use an export that was not involved in preparing the instructions. Include a new product and a missing branch code. The report should identify the required decision instead of dropping the row or inventing a category.

Assign responsibility for lookup tables and metric definitions. If the process should run automatically when a file arrives, agree how scheduling, failures and retries will work. You can assess available Work features or scope an API integration. A manually generated report does not refresh itself in the next reporting period.

Cost and the value of released time

Illustrative scenario: eight monthly reports currently take three hours each. If the target is one hour per report including checks, released capacity is 8 × (3 − 1) = 16 hours a month. At an assumed fully loaded labour cost of €25 an hour, that represents €400 of staff time. Additional administration and running costs reduce the benefit; the pilot establishes the actual result.

Three Business Standard seats billed monthly cost $75 a month, before taxes and additional usage. The rate was checked on 30 September 2026 in OpenAI pricing. Work and Codex share usage limits, so demanding analysis can affect the allowance available for other tasks.

Syntalith training starts at €600 per day excluding VAT. Report preparation, source cleanup and automated refresh need an agreed scope. Our pricing page and ChatGPT implementation budget explain the separate cost items.

Bring a sample export without confidential data and the report your team currently creates to an implementation discussion. We can establish whether cleaning, calculation or checking accounts for most of the work.