A manager says, Can you analyse why sales performance is getting worse? It sounds like an analytics question. It isn't. At least not yet.
A junior analyst might immediately open Power BI, SQL or Excel and start looking for a decline.
An experienced analyst pauses. The first task is to turn the vague request into something that can actually be tested.
Start by asking, What does “sales performance” mean?
- Revenue?
- Units?
- Conversion rate?
- Margin?
- New customers?
- Retention?
Then, What does “getting worse” mean?
- Compared with last month?
- Last year?
- Target?
- Budget?
- Another region?
And most importantly, What decision will this analysis support?
Suppose the manager explains that revenue is below target and wants to know whether the problem is customer demand or sales execution. Now the analysis has direction.
You can test:
- Whether customer demand has changed
- Whether conversion rates have declined
- Whether average order value has changed
- Whether the customer mix has shifted
- Whether performance differs across sales teams or regions
Notice what happened. The analyst didn't use another tool. They improved the question.
That is an important workplace skill because corporate requests are rarely delivered as perfectly defined analytical problems.
You may receive, The numbers don't look right. Can you find what's causing this?
We need to understand what's happening. Your job isn't to guess what management means. Your job is to convert ambiguity into a question that can be tested with evidence.
Analyst in Action, Before touching the data, ask:
- What exactly are we measuring?
- Compared with what?
- What could explain the change?
- What decision depends on the answer?
That's when tools become useful. Because the strongest analysts don't demonstrate their value by starting analysis quickly. They demonstrate it by making the problem clear enough to analyse correctly. You know the tools. Now use them to answer the right question.
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