Pattern Recognition

Pattern Recognition

““Mathematics is the science of patterns, and nature exploits just about every pattern that there is.”~ Ian Stewart

pattern recognition

Make better decisions. Seeing that on a to-do list will ruin anyone’s day. Every leader from Moses to Musk has wished they could better prognosticate an outcome or choose the correct path. We’ll do everything from putting on six different hats to meticulously analyzing costs/benefits to creating elaborate decision trees in order to ferret out the best course of action, but do those approaches really enable us to make better decisions? Evaluating and improving decision-making is highly subjective, but methods by which we marry pattern recognition with making judgment calls is gaining traction within the business community.

Pattern recognition is a term usually used within computer science where a program identifies input data, like images or numerical data sets, and calculates relationships that exist between the data points. Facial recognition evaluates the unique distance ratios of facial features to a biometric database to produce an identification. There are similar programs that assess stock trends or blood tests to make recommendations based on trend data. Here’s the slick part, your brain puts any computer to shame when it comes to pattern recognition. You’ve probably met a financial analyst who can look at a few spreadsheets and quickly tell you the health of a company. Tat person learned to see the interconnectivity of cash flow, inventory, accounts receivable, and other factors to form a rapid assessment.

Pattern recognition can be learned, and it even forms the basis of capitalism. Supply and demand; boom and bust; consumption and production all form patterns. The topics and techniques of pattern recognition go beyond this text, but the first step is to look for connections in daily causes and effects. A simple example might be tracking why the last ten deliveries were late to a customer. Does the pattern connect with weather conditions, roadwork, supply chain glitches, loading dock callouts, or any other discernable factor? If you see that pattern, you have the beginnings of a data-driven crystal ball that will improve your decision-making process.

Consider this …

1. What business challenges are you experiencing right now, for which you have some data that you can review?

2. What potential patterns do you see in the data that might give you a glimpse into the root cause of the challenges?

3. How might you “test” those root causes so you can ultimately get to a workable solution?

For more, check out The Top Performer’s Field Guide, The Innovator’s Field Guide, or visit www.JeffStandridge.com.

(Originally published in The Top Performer’s Field Guide.)

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