Imagine that you are an HR director. One of your responsibilities is to ensure your department is up to date on its annual compliance training.

Recently, your company rolled out a new sexual harassment course. At the end of the course, participants are given a test. They must score 90% or higher to pass. If not, they retake the course.

You approach your analytics and reporting team to build a report for you. They ask you what you want to know. What would you tell them?

I pose this problem in my Rethinking Data workshop. Here are the most frequent responses that I receive:

·     How many people passed

·     How many people failed

·     What score each person received

·     Who passed and who failed

I sometimes get a few others but these (or some form of these) are the most typical. Were you thinking of something similar?

These questions represent an information-based approach to data. Many of us are stuck in that approach. We frame our questions around obtaining facts. Don’t get me wrong. Facts are important. You’d better not be making any statements or decisions without out them.

However, an information-based approach is slow and inefficient. You are often several steps removed from the decision. For example, knowing the number of people who failed doesn’t get you any closer to taking action. To take action, you have to go one more step and determine who those people were. Similarly, asking for each person’s score still puts you one or two steps from the decision. You have to compare that score against the target to determine if the person failed. You then need to remember who all of those people were. Even if you color code (which is another form of information), it’s still up to you to mentally collect all of the people whose are “red”.

The reality is that no one wants information. We aren’t just curious or looking to be enlightened. When we look at data, we are always trying to figure out whether something needs to be done. So, why not start there?

An alternative to asking information questions is to ask decision-driven questions. Decision-driven questions close the gap between analysis and action.

In the list above, the fourth question is closest to a decision-driven question. I don’t need the score or the number of people who passed or fail. I need to know who those people were so that I can do something about it. However, even this question is worded in terms of information.

The easiest way to create a decision-driven question is to think about the action you are looking to take. In this case, the question that I should be asking is, “Who needs to retake the training?” The result of asking this question is going to be a pretty simple “report” – a list of names.  Of course, the answer to this question better be based upon actual facts and data.

Not only does the question itself start you closer (or at the decision), the report is much simpler. You don’t have to wade through a lot of excess information. You don’t have to mentally separate those who passed from those who failed. You get the exact information that you need to act.

Too often, I sit in meetings that focus on providing information. While the goal of those meetings is to make decisions and drive action, most fall short. The reason is simple: when you ask about and present information, you talk about information. When you ask about and focus on decisions/actions, you talk about decisions and actions.

Change your questions. If you start with an information-based question, ask yourself, “What am I going to do with the answer?”. Then reframe the question around that.

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Brad Kolar is an executive consultant, speaker, and thinking coach with Avail Advisors. Avail’s Rethinking Data workshop will help you close the gap between analysis and action. Contact Brad at brad.kolar@availadvisors.com.