Can I have AI analyse my spreadsheet?
I have a spreadsheet but cannot work out what it says. AI is very useful here — and this is also where it makes its most dangerous error: stating a wrong number confidently. 📊
The distinction is clear: calculation is the machine’s job, interpretation is yours. When the two blur, the spreadsheet stops being a decision tool.
Short answer: have numerical work done with formulas and language work with text. Do not trust a figure produced inside a conversation. 🧮
What does it do well?
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- Explaining the sheet
- Writing formulas
- Cleaning instructions
- Explaining the results
Four jobs, all without generating numbers. ✅
Explaining the sheet
Answering “what is in this table?” structurally: what the columns are, the units, the period. Valuable as a starting point. 🗂️
Writing formulas
Turning the calculation you want into a formula. You run the formula; the number comes from the sheet. 🧮
Cleaning instructions
A step list for fixing messy data: remove duplicates, unify date formats, close gaps. 🧹
Explaining the results
Once the calculation is done, translating the resulting table into management language. This is the biggest time saver. ✍️
What does it not do well?
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- Arithmetic inside text
- Filling missing data
- Establishing causation
All three concern numbers. ⚠️
Arithmetic inside text
The figure produced when you say “add these up” is not used without verification. It is like adding by eye. 🔢
Filling missing data
It can fill empty cells with “reasonable” values. That means invented data. 🕳️
Establishing causation
Two lines moving together is not cause and effect, yet the tool may narrate it as if it were. ⚖️
The safe flow
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- Step 1: write the question
- Step 2: take the formula
- Step 3: share the result
- Step 4: check
Four steps, the same every time. ⚙️
Step 1: write the question
Is it “which month fell” or “why did it fall”? Without a clear question the analysis scatters. ❓
Step 2: take the formula
Ask for the calculation as a formula, not as text, and run it in the sheet. 🧮
Step 3: share the result
Give the resulting figure back to the tool for interpretation. Now you are talking with real data. 📊
Step 4: check
Figure, period and unit; the method sits in the verification guide. 👁️
Which data can be given?
The boundary follows the content. 🔐
Can be given
Aggregated sales, traffic and stock data; tables with name and contact columns removed. ✅
Never given
Customer names and contact details, payroll, identity numbers; the frame sits in the data security guide. 🚫
How do you get good interpretation?
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- Give context
- Ask for alternatives
- Ask for action
- Ask for the doubt
A good question brings a good answer. 💬
Give context
Sector, season, campaigns and price changes. Interpretation without context stays generic. 🧭
Ask for alternatives
“What are three possible causes of this drop?” A single explanation misleads. 🔀
Ask for action
Not interpretation but decision: what should be done, in what order? That is how a sheet turns into work. 📋
Ask for the doubt
“What cannot be said with this data?” This question breaks over-confident readings. ⚖️
What should I do today?
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- Step 1: pick one question
- Step 2: work with formulas
- Step 3: check the interpretation
- If you want help
Three steps, one spreadsheet. 🪜
Step 1: pick one question
The single thing you most want to know. Analysis begins with one question. ❓
Step 2: work with formulas
Do the calculation in the sheet, not in the chat. This one habit ends the wrong-number risk. 🧮
Step 3: check the interpretation
Add an alternative explanation and the doubt question. You make the decision. 👤
If you want help
Let us set up your analysis flow: use the consult your expert form. For your current usage see the business AI usage audit; the whole sits on the AI consultancy page. 🎯
Related reading from the archive: which jobs can use AI · measuring the return on AI.
📝 Notes From the Field
A team pasted the monthly sales table into the tool and asked it to summarise. The total in the summary was well below the real one — and nobody had checked. The method changed: the calculation is done in the sheet with formulas, and the tool only explains the result. The error never recurred.
📖 Short Glossary
Arithmetic in text: adding figures inside a conversation; never used unverified. Aggregated data: a table summarised above the individual level. Alternative explanation: other causes that could explain the same data. Doubt question: the “what cannot be said with this data?” check.
⚡ Quick Summary
Calculation is the machine’s job, interpretation is yours. 📊 The tool explains the sheet, writes formulas, gives cleaning steps and translates results into management language. Figures produced inside text are not trusted. Analysis runs in four steps with personal data removed.
🎯 Next Step
Let us set up your analysis flow: use the consult your expert form. Working with your data sits in the own data guide; for your current usage see the usage audit.
Frequently Asked Questions
Sık Sorulan Sorular
Numbers from the sheet, interpretation from a person. That sentence sums up the whole section. ✅
Delete identity columns and use codes if needed. Names are almost never required for analysis. 🧼
In the company account with the data setting off; the structure sits in the company account guide. 🏢
Usually safer, because the tool can run code to calculate. Even so, a few of the resulting figures should be verified in the sheet; the method changes but the check does not disappear.
You can, and it is practical for presentations. Axis and period labels must be checked; the most frequent error is in the labelling rather than the data.
The rules are few and reduce to one sentence: calculations happen in the sheet. That single habit removes the biggest risk at any scale.