Next Gen. DSRs - Reporting is NOT analytics

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I've written a number of posts now on the next generation of Demand Signal Repositories. DSRs are the specialized database and reporting tools primarily used by CPGs for retail Point of Sale data.

So far, I've looked at the challenges (and big opportunities) around handling the large quantities of data involved: better database technologies, scale-out platforms, true multi-retailer environments, effective data blending and dramatic simplification of data structures.

Taken as a whole this get's the necessary data into one place where it is relatively simple to overlay it with the BI or analytic tools of your choice and still get good performance. This is the starting point.

Now, we can get to the fun stuff, Analytics. Let's start by addressing a widespread misunderstanding.  Reporting is NOT analytics.  I've blogged on this before , actually one of my very first blog posts, but it bears repeating and extending from the original.  Reporting is about "what happened"; Analytics is concerned with "why?""what if?" and "what's best?".

You need reports.  Hopefully they are well constructed, with appropriate metrics, good visualization and exception highlighting. Perhaps they are also interactive so you can drill-down, pivot and filter. These are useful tools for exploratory "what happened" work, but, almost exclusively, reports leave it up to the reader to construct the "why".

Great reporting can pull together facts that you think are related for visual inspection (e.g. weekly temperature and ice-cream sales by region). Perhaps you can see a pattern, sort of, but reports will not quantify or test the validity of the pattern that's up to you, the reader, to guess at.

Even great reports can't help you much with more complex relationships. In reality, ice-cream sales are also dependent on rainfall, pricing, promotions, competitor activity etc. Who knew? Well we all did of course, but there is no reasonable way to visualize this in a standard report. Want to predict sales next week given weather, price and promo data for all products in all regions? Your going to need some good analytics.

You need Analytics too.  In some cases, basic, high-school, math is all you need. In most, it doesn't even get you close to the 80% solution beloved of business managers.   "Winging it" in Excel, Access, PowerPivot etc. can give you very bad answers that are seriously dangerous to your success and/or employment.  

Want to understand and predict the impact to sales of promotions, pricing or weather events? You need Analytics for that.

Wan't to know where you can safely reduce inventory in your supply chain while increasing service level? You need Analytics.

Wan't to alert when sales of your product are abnormally low? Analytics!

Want to know how rationalizing products across retailers would impact your supply chain? Yep, Analytics.

Want to know which shopper demographics are most predictive of sales velocity? I think you get it...

If your business question is something other than "what happened" you need Analytics.