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The Unfair Advantages Known to and Ignored by (Almost) Everyone




The TrackMan is a Doppler radar device that is able to track many critical data, including ball speed, spin rate, club speed and path, face and attack angles, and more. It was first introduced to the world of golf around 2007, and some of its early adopters include the who’s who of golf, such as Tiger Woods and Michelle Wie.


The TrackMan revolutionized the business of performance improvement by focusing on a data-driven approach, then a novelty. On hindsight, one might consider this a no-brainer, considering the wave of digital transformation that has swept across many sports from baseball (remember Moneyball?) to basketball.


Yet, despite its obvious advantages, initial adoption was surprisingly slow. As late as in 2013, 5 years after launch, only approximately 30% of the players on the professional tour were using a TrackMan to finetune their game. And not for a lack of awareness – the Trackman’s benefits were well known and widely publicized.


Low adoption of good solutions is not new


Turns out such adoption patterns are nothing new. The sobering fact is that we Homo Sapiens are creatures of habits with an innate resistance to change, even in the face of overwhelming evidence.


This also brings to mind Rogers’ Diffusion of Innovation theory where the process of adoption over time follows the classical normal distribution with 5 distinct adopter categories – innovators, early adopters, early majority, late majority and laggards.


Today’s conservative ideas were once controversial, cutting-edge, and innovative.

As observed by author Ryan Holiday, “today’s conservative ideas were once controversial, cutting-edge, and innovative.” In other words, it does require a leap of faith for the innovators and early adopters to embrace change, even if they make a lot of sense.


Case in point: In 1943, Thomas Watson, chairman of IBM, remarked, “I think there is a world market for maybe five computers.” Today, it is estimated that there are over 2 billion computers in the world.


Might the trick be to “identify the future that has already happened,” to quote the late management guru Peter Drucker?


An example staring us in the face right now


Surveying today’s technology landscape, what do we see? According to Gartner, "the RPA software market grew 38.9% in 2020 to $1.9 billion and held its position as the fastest-growing segment in the enterprise software market." This for the 3rd year in a row!



This makes perfect sense, one would think. After all, there are plenty of motivations for shifting to a digital workforce, including:

  1. the strategic imperatives of digital transformation (one reinforced by the Covid-19 pandemic);

  2. an acute shortage of manpower in many markets, especially developed ones;

  3. unfulfilled customer expectations, e.g. real-time and tailored services, as a result of operational constrains (read manual and tedious processes); and

  4. loss of productivity due to a mostly disengaged, overworked and over-stressed workforce.

Yet, it appears that most organizations have not embraced an automation-first mindset on a scalable and sustainable basis. For example, Forrester research indicates that "more than half of all RPA programs worldwide employ fewer than 10 bots. Furthermore, less than 19% of RPA installations are at an advanced stage of maturity."


Could this be yet another example of slow adoption of soon-to-be mainstream technological innovation? More importantly, are you up for it? 😉

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