Pattern recognition is the 4th step in excellent decision making. It is used to identify a trend or pattern from past events in order to predict future events. In Pattern Recognition, we want to be like the Roman god, Janus, who is depicted with two faces—one looking at the past, and the other looking to the future.

Look Back To Plan Ahead
We spend our entire lives learning and accumulating data. Beyond our own experience, the internet offers an endless supply of additional data points. Figuring out how all this data relates and how to use it to our advantage requires a strategic way of thinking.

Let’s say you need to hire a top salesperson. What criteria do you look for to ensure that you will pick the best candidate? Your gut instinct is that you want someone with at least a college degree and prior marketing experience.

Now you look at your current top performers and see that 85% had past sales experience when hired, but only 30% had college degrees. Clearly, the prior sales experience is a better indicator of future success than the level of formal education.

With this information at hand, reevaluate your criteria. Shouldn’t you place more importance on hiring someone with prior sales experience and less importance on the candidate having a college degree?

This is a simple example of using existing knowledge to predict the future. Will the candidate you choose turn out to be a top performer? We won’t know the answer for quite some time, but we still use basic predictive analytics to make the best choice.

Divide and Conquer
In Pattern Recognition, we aim to “connect the dots,” sorting large amounts of data into manageable silos and then analyzing the data. If we visualize each data point as a “dot,” connecting those dots will paint a picture that can be used to predict outcomes.

Correctly predicting an outcome is incredibly important to excellent decision making.

When we know what to expect, we can decide a course of action that provides the greatest chances for a successful result. Pattern Recognition ties in with Probabilities, one of the four key steps to successful decision making.

To spot predictive patterns and master Pattern Recognition in the decision-making process, we must:

  • Manage and simplify data
  • Differentiate between: Correlation, Relevance, and Causation

A word of caution:
Great decision making requires looking at facts objectively. If you begin Pattern Recognition with a mission to find a pattern that supports your hoped-for conclusion, you will inevitably seek out only data that supports your conclusion instead of objectively allowing the data to inform you. This is classic confirmation bias (and a big no-no).

In my next blog, I will detail the individual steps to practicing Pattern Recognition and guide you through the process to make it work for you