🧾 How GPT Turns Raw Exports Into FP&A-Ready Insights (In Minutes)

⚡ AI Hack: From Raw Exports to Ready-to-Use FP&A Insights

🧠 The Problem:

If you’re like most FP&A analysts, you often receive raw data exports — P&L lines, sales transactions, GL exports, export dumps from ERPs or CRMs — in CSV form. Before you can analyze, comment, or visualize: you have to:

• Clean the data (remove duplicates, fix formatting)

• Normalize categories (e.g. “Marketing Exp” vs “Mktg Expenses”)

• Calculate KPIs or key metrics

• Detect trends / outliers / anomalies

• Write summary commentary + possible action items

Doing that manually? Hours of work before you even start your analysis.

🧰 What You’ll Need:

• A CSV or Excel export (sales, GL, P&L, raw transactions, etc.)

• ChatGPT (or any GPT with data-upload capability)

• Google Sheets or Excel (to download / export CSV)

• Optionally: AI-powered spreadsheet tools (see below)

🔁 Step-by-Step:

✅ Step 1:

Export your raw data

From your ERP/CRM/financial system, pull the raw export as CSV. Keep the column headers clear (e.g. Date, Account, Amount, Category, Region, etc.).

Here’s an example of a raw CSV export you might upload:

Just download this kind of table as a CSV and drag it into ChatGPT.

✅ Step 2: Upload into ChatGPT (or Finance AI Assistant).

Open ChatGPT → start a new chat → upload the CSV file as input.

It should say:

✅ Step 3:

Use a prompt like this:

“Here is a raw data export from our finance system. Please:

1. Clean the data:

   • remove duplicates,

   • standardize category labels,

   • fix casing,

   • handle anomalies (flag negative or outlier values),

   • identify missing values or inconsistencies.

2. Calculate key metrics:

   • total revenue

   • total expense

   • profit margin

   • MoM changes (if applicable)

   • top 5 categories by spend

3. Provide an executive-ready summary:

   • 3–5 bullet points

   • 1 short paragraph of recommended next steps

4. Suggest the best chart types to visualize trends. Return:

   • cleaned table (CSV format)

   • summary

   • chart list”

✅ Step 4:

Review output

Here’s what GPT will generate:

Metrics (sample)

• Total Revenue: $56,000

• Total Expense: $17,000

• Net Profit: $39,000

• Profit Margin: 69.6%

• Anomalies Detected: 1

• Duplicated Entries Removed: 2

Executive Summary (sample)

Suggested Visuals

• Time-series revenue vs expense

• Stacked bar for category spend

• Scatterplot to highlight anomalies

• Region-level breakdown pie chart

 ✅ Step 5: Optional Follow-Up Prompts

Optional Export back to Excel / Sheets

A) “Export Cleaned Data Back to Excel” Prompt

Paste this into ChatGPT after reviewing the cleaned table:

GPT will return a downloadable CSV you can drop into Excel or Sheets.

B) Give Me a Dashboard Blueprint” Prompt

C) Explain It to My Manager” Prompt

✅ Step 6:

Deliver or export as PDF/report

Now you have a near-analysis-ready dataset, commentary, and chart plan — ready for your manager, presentation, or deeper dive.

🔥 Outcome Test:

Run the process on a small sample first. You’ll likely get:

• A cleaned dataset — no duplicates, standardized categories

• Calculated KPIs & metrics (margin, growth, anomalies, etc.)

• A crisp, executive-ready summary of findings + next steps

• Suggested visuals to illustrate trends

🔥 Why It’s Awesome:

Cut your data-prep time from hours to minutes. Get clean, analysis-ready data and a narrative before your lunch break.

🛠️ 3 Free AI Tools

1. ChatGPT (Structured Prompt + File Upload)

What it is: Upload raw CSV / Excel exports, ask for cleaning + insights

Why it helps: Works with Excel exports, easy to prompt — perfect “data janitor + analyst” combo

🔗 https://chat.openai.com

2. GPTExcel

What it is: AI-powered formula & data-cleaning + SQL/regex generation for Excel

Why it helps: Great if you want to automate cleanups or build repeatable data-prep scripts

🔗 https://GptExcel.uk

3. Rows AI

What it is: Spreadsheet-native AI: clean data, run analysis, generate summaries right inside sheet

Why it helps: Useful if you prefer to stay inside Sheets/Excel rather than switch between tools

🔗 https://rows.com

🧠 News Byte: AI — The New Data Janitor & Finance Sidekick

AI is no longer just an experimental add-on for finance teams — it’s becoming a core assistant. A new 2025 research report from EY shows how AI is reshaping the role of FP&A, not by eliminating it — but by upgrading it. Tasks like data consolidation, cleaning, and initial analysis are increasingly handled by AI, allowing analysts to elevate to strategic, insight-driving roles.

What does this mean for you? If you’re still spending your Sunday evenings manually wrangling exports and cleaning data, you’re doing the work of a “data janitor.” With GPT-powered workflows, that grunt work disappears — and you get to focus on what really matters: insights, narrative, strategy.

The shift is already underway: a 2025 survey found that 79% of FP&A teams now use some form of AI in their workflows.

If you treat AI as a copilot (not a threat), you’re positioned to become the go-to strategic analyst in your organization — not the person crunching numbers until midnight.

Meme Corner 😂

✅ That’s a wrap on this week’s The AI+.

• You just saw: a full, replicable GPT workflow to convert raw data exports into clean, insight-ready FP&A deliverables ✨

• Three free tools you can try today — no complicated setup required

• Solid evidence that AI is already transforming FP&A workloads — and if you’re not using it, you’re falling behind