Read the website of almost any business promising to make sense of data and you’ll probably come across the words ‘analysis’ and ‘insight’.
They’re often used interchangeably, but they don’t mean quite the same thing. And when you’re using data to make business decisions, the distinction matters. Put simply, analysis is the process of examining data to understand what is happening. Insight is what you learn from that analysis that helps you understand why it matters.
What is analysis?
Analysis is the process of examining information in detail, looking for patterns, differences and relationships that can help answer a particular question.
For example, a retailer might analyse sales performance across its store network and discover that several locations consistently outperform others. That’s useful information. But on its own, it doesn’t necessarily tell the retailer why those stores perform better or what it should do as a result.
That requires going further.
What is insight?
Insight is the understanding you gain from examining and interpreting the evidence.
It can reveal something that wasn’t immediately obvious, explain why something is happening or challenge an assumption you previously held.
In our retail example, further analysis might reveal that the best-performing stores aren’t necessarily those in the busiest locations. Instead, they may be in areas with a stronger concentration of the retailer’s target customers, less direct competition or different patterns of footfall.
That’s the insight.
And it could change the way the retailer evaluates future locations.
How are analysis and insight connected?
Analysis and insight are closely related because analysis is one of the ways we uncover insight.
Take Willy Wonka’s chocolate factory. We can see that the factory produces a lot of chocolate. That’s an observation. Analyse what happens inside and we discover that the entire production process is being carried out by Oompa Loompas.
The insight comes from understanding what that discovery tells us about how the factory manages to produce so much chocolate. There is, however, another important part of the process, knowing what you are trying to find out in the first place.
If our objective is to understand how Willy Wonka produces so much chocolate, we can decide what evidence to examine and which questions to ask. Without that objective, we could analyse enormous amounts of information without discovering anything particularly useful.
Data doesn’t automatically produce insight
Having more data doesn’t necessarily mean having more insight. Businesses can collect and analyse huge quantities of information, but unless the analysis is connected to a clear question or decision, the result can simply be more information.
A useful insight should help you understand something that matters. It might reveal an opportunity, identify a risk, explain unexpected performance or show that an assumption you were relying on isn’t supported by the evidence.
Most importantly, it should help you decide what to do next.
From analysis to better decisions
This distinction is particularly important when working with location data.
Knowing that one area has higher footfall than another is analysis. Understanding that the people creating that footfall don’t match your target audience could be the insight that changes your decision.
Similarly, knowing where your customers live is useful. Understanding that you have strong customer penetration in some catchments but significant untapped potential in others gives you something you can act on.
The value isn’t simply in having the data or analysing it. It’s in using what you discover to make a better-informed decision. That’s ultimately the difference between analysis and insight.
See how Periscope® helps turn location data into clearer business insight. [add link to Location Intelligence page?]
