top of page

Teeing Off with Data: A Golfer's Guide to Analytics

Ever considered that your approach to analytics could learn a thing or two from golf? Specifically, the ever-so-crucial approach shot? Well, buckle up (or should I say, lace up those golf shoes), as we embark on a whimsical journey down the fairway of data analytics, guided by our trusty 6-step process.

1. Problem Definition

Just as you survey the distance to the green and obstacles in your path (Is that a bunker or a very large, sand-colored rock?), defining your problem sets the stage. In analytics, as in golf, knowing what you're aiming for makes all the difference. Is the plan to get to the green in one shot or to lay up to a safer distance. Will it be the 7-iron of market analysis or the pitching wedge of customer segmentation?

2. Hypothesis Development

Now, close your eyes. Imagine the perfect arc your ball makes as it sails through the air, right before landing softly on the green. What would possibly impact this optimal trajectory

  • how or where the ball is sitting

  • The direction of the wind

  • Temperature and humidity of the air

  • The speed and hardness of the green

  • The consistency of your swing

  • The colour of sky etc.

These are your hypotheses - a comprehensive set of considerations that might impact/influence your outcomes. Will it glide gracefully towards increased sales, or are we looking at reducing operational costs in one clean swing?

3. Gathering Data

Peering down the fairway, you check the wind, adjust your stance, and maybe even chew on a blade of grass for effect. Gathering data is much the same. You're collecting all the variables that could affect your shot - or in our case, the analysis. Sales figures, customer feedback, and the ever-pesky market trends are your wind direction, strength, and humidity.

4. Analysis

With data in hand and a clear target, you adjust your grip, stance and aim based on the data gathered and you take your swing. This is where the magic happens in both golf and analytics. The swing is your analysis method - be it a regression analysis or a simple moving average. It’s the moment of truth where your preparation meets action.

5. Intepretation of results

Ah, the suspense as the ball arcs through the air. Will it find the green or take an unexpected detour into the woods? Interpreting your results is much the same. It's about seeing where your analysis lands and understanding what it means. Sometimes it’s an eagle, other times... well, let’s just say there’s a reason those pesky water hazards exist. But more importantly, understanding what went right or wrong in the analysis.

6. Communicating the results

Whether your golf ball is on the green or in the hazard (that's probably me), it is time to communicate to your golf buddy's about what went right or wrong in your analysis in setting up the golf shot. It if went right, you get bragging rights; if it went wrong, it is time to make your excuses; and also perhaps to offer some advice to the next person to step up to the tee.

From teeing off with problem definition to the final putt of communicating your recommendations, the parallels between golf and analytics are uncanny. Now, who said data couldn’t be fun? Here’s to making every analysis feel like a hole-in-one!

25 views1 comment

1 комментарий

Оценка: 0 из 5 звезд.
Еще нет оценок

Добавить рейтинг
Jeremy Poon
Jeremy Poon
06 апр.
Оценка: 5 из 5 звезд.

Now, who says Data Analytics is boring and golf is an old man's game?

Featured Posts
Recent Posts
bottom of page