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# Reporting vs. Analytics
- URL: https://www.philsimon.com/reporting-vs-analytics/
- Published: 2013-03-13T15:47:25.000Z
- Updated: 2025-08-09T01:39:56.000Z
- Description: Thoughts on a critical and oft-overlooked distinction.
- Author: Phil Simon
- Tags: Analytics, Big Data, ATAW, Data Management, The Visual Organization, Too Big to Ignore

We are hearing more and more about analytics these days. To be sure, the term is hardly new. [Key performance indicators](https://en.wikipedia.org/wiki/Performance%5Findicator?ref=philsimon.com) (KPIs) have been gathering momentum for fifteen years. As is often the case, though, terms get misused, if not bastardized. In this post, I'll provide some clarity about a key distinction: reporting vs. analytics.

Let me be unequivocally clear: Reporting is not the same as analytics.

Am I the only one who feels this way? Hardly. For starters, in [*Taming The Big Data Tidal Wave*](https://www.amazon.com/gp/product/1118208781/ref=as%5Fli%5Ftl?ie=UTF8&camp=1789&creative=9325&creativeASIN=1118208781&linkCode=as2&tag=phisim-20&linkId=2YLKHHM6C2VOHSWQ&ref=philsimon.com) (affiliate link), Bill Franks differentiates between reporting and analytics. From the book:

| Reporting                  | Analysis                |
| -------------------------- | ----------------------- |
| Provides data              | Provides answers        |
| Provides what is asked for | Provides what is needed |
| Typically standardized     | Typically customized    |
| Does not involve a person  | Involves a person       |
| Fairly inflexible          | Extremely flexible      |

In my consulting career, I spent a great deal of time on reporting. In my time, I created:

- Several thousand Crystal Reports
- More Microsoft Access databases, [SQL](https://en.wikipedia.org/wiki/SQL?ref=philsimon.com) statements, and *ad hoc* queries than I could count
- Many, many dashboards

Still, I rarely believed that even my most complicated reports (and trust me, some were doozies) really explained *why* something was happening—or had already happened. To me, that's the very essence of analytics: they go beyond the mere what and where. Ideally, they explain *why* and suggest a potentially measurable course of action.

> Foolish is the soul who conflates reporting with analytics and data discovery.

## An Example

For instance, how many customers visited our site and never made a purchase? Let's say that that number is 60 percent. That's great, but *why* did they not make a purchase? Potential answers include:

- The product's price was too high.
- The site's navigation was confusing
- They became distracted.
- Their computers crashed.
- A combination of a few different things.

I could go on, but you get my drift. A simple standard report or statistic isn't entirely unhelpful, but it begs the question, Why? This is critical point in [*The Visual Organization*](https://tinyurl.com/6philtvo?ref=philsimon.com)and something that I also address in the new book [*Analytics: The Agile Way*](https://www.philsimon.com/books/analytics-the-agile-way/).

## Simon Says: The distinction between reporting and analytics is critical.

In an era of Big Data, organizations of all sizes can theoretically explain more of the unknown and, dare I say, even potentially predict a few things. To truly realize the value of data—be it Big, Small, whatever—people need to rid themselves of the notion that a standard report is the same as meaningful analytics, let true alone data discovery.

I'll have plenty more to say on this over the coming months.