The “Beer and Diapers” story is a famous big data legend.

As with many legends, the story has become more spectacular and fabricated over time. Also like many legends, the story does have some basis in fact.

For those who haven’t heard it, here is a common version:

Back in the 90s, Osco Drug ran an affinity analysis and discovered that young males often purchase beer and diapers in the same trip. Osco used that information to reposition the beer and diapers and greatly increased its revenue and profits.

And, now the truth (maybe – there is still some disagreement)

Back in the 90s, Osco drug (actually Teradata) ran an analysis of 1.2 million shopping carts. They discovered, among other things, that between 5-7pm there was an increase in sales of beer and diapers together (although no correlations with gender or age were analyzed). Osco did not do anything specific with that information. (http://www.dssresources.com/newsletters/66.php).

Despite the actual story being somewhat less exciting, it still provides an important take-away: insight comes from context, not data.

The finding that people purchase beer and diapers together is an interesting fact. However, it’s not an insight…yet. For it to gain meaning, it must be put into the context of the business.

The insight is the way that the company should exploit this fact.

So, the first question in turning a fact into an insight is what should be done as a result of this new piece of information. In the case of the beer and diapers, the specific question is, “Where should we put them relative to one another?”

Ironically, while the data will tell you that people purchase these items together, it won’t tell you where to put them. For that, you need context.

If you are a traditional retailer who makes very little on any one product, you’d want to put them far apart. This would encourage people to wander the store and hopefully fill their cart with other products along the way.

However, if you are a retailer who is able to charge a premium for a fast, simple, and convenient customer experience, you’d probably put them close together.

There are several possible actions. Each one equally “right” within its given context. Turning the fact into an action specific to your business increases its value and insight.

However, knowing the correct placement still doesn’t provide the insight. You need additional context.

Suppose that you conclude that the beer and diapers should be far apart.

The next contextual question is, “Where are they now?”

If they are already far apart, the insight isn’t to put them far apart. That’s redundant. The insight is to keep them far apart. In other words, the insight is that they are in the right place and you should keep doing what you are doing.

If they weren’t far apart, then the insight would be to move them.

In this simple example, the same finding, that people buy beer and diapers together, could lead to four possible “insights” (in reality there would be more but I am simplifying for the example).

Move them far apart

Keep them far apart

Put them together

Keep them together

Focusing simply on the relationship between beer and diapers starts the conversation at least two steps from the decision. That wastes time and slows down decision-making.

Here is a simple formula for transforming facts into insightful statements of action. The key is to look beyond the data that are in front of you and add additional context:

State the action (what does the data tell us to do)

–“Put the beer and diapers far apart”

2. Add one or two contextual words reflecting what you need to do regarding the action

–“Move the beer and diapers far apart” (because they aren’t in the right place)

3. Add one or two contextual words reflecting how urgently you need to take the action

–“Move the beer and diapers far apart now!” (because you are losing an opportunity to increase profit)

Instead of reporting a single finding, you’ve pulled four disparate data sets into a simple, powerful statement of action:

• what and how are people purchasing? (customer data)
• what should we do about that? (company business model data)
• are we doing it right? (company performance data)
• how urgently do we need to take action? (company and/or competitor data)

That’s how you create insight!

If you want to close the gap between analysis and action, you must stop reporting facts. Instead focus transforming facts into decisions and actions.

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Brad Kolar is an executive consultant, speaker, and author with Avail Advisors. Avail’s Rethinking Data workshop teaches leaders how to close the gap between analysis and action.