Data Analytics – Helping to focus learning, set L&D direction and most importantly…win the Masters!

16:15:00 Learning Boffins 0 Comments

It is no secret that I am a golfing nut!  My wife is understanding enough to let me play at least once but often twice a weekend and when not on the course I am often practicing, watching or learning more about the game.  Last weekend was an exceptionally special time for UK golfers due to the fact that Danny Willett won the masters.  He is the first UK golfer to do this since Sir Nick Faldo won in 1996 thus ending a 20 year drought.  Obviously this took a tremendous amount of skill and perseverance but it also required an understanding of what he was good at and perhaps more importantly not good at.  This is a lesson we could all benefit from.

The pro golfer and data

Professional golfers and by extension their caddies are known for their meticulous preparation before any event.  Preparation revolves around training, technique, nutrition but also about how the player is performing on any given week and what a player’s tendencies are.  They gain this knowledge by looking at data or past evidence of performance.  They track all manner of data points but some examples are in the table below.  Within this table I have included the stats for Danny Willett as well as the previous winner of the Masters, Jordan Spieth.  It is worth mentioning that Spieth is the current world number 2 and was favoured to win the competition even half way into his final round on the Sunday.

As mentioned previously the above stats are just the tip of the iceberg.  Nether the less there are data points that point to areas where both Danny and Jordan may focus their practice and learn from their numbers.  For example both players see a significant drop off in putts they make from 6’ or more.  They may choose to improve putting at this range or they may decide that they want to improve their chipping or irons so that they are more often within 5’.  The strategy of improvement will be player dependant and again more data on the success of either approach will govern their eventual strategy for practice.

I also previously mentioned that a pro golfer will also understand their tendencies.  Again, in the table above you can see that Jordan Spieth misses the fairway to the left (left rough tendency) more often than he does to the right.  This might prompt him to start aiming slightly further up the right when he tees off, or alternatively change the shape of his shot to ensure he hits more fairways.

Data in-the-moment is just as important as averages across a large period of time

Understanding data across a season or even a career is important to a golfer but during the Masters it became apparent that in-the-moment data was equally important.  During the final round on Sunday Jordan Spieth was leading by 5 strokes but in just three holes he would drop 7 shots and loose his leading position at the Masters for the first time in two consecutive competitions.  This ‘meltdown’ as some have called this is best summed up on the 12^th hole where Jordan took 7 shots on a hole that should only take 3.  The cause…he wasn’t paying attention to his tendencies that week.  In a post round interview Jordan admitted that all week he had been hitting this weak shot to the right off the tee and on the 12^th hole that is precisely what he did.  Unfortunately for him that meant his ball found a river.  What is interesting about this is that fact that Jordan and his caddy knew that he was tending to hit it right.  What they didn’t do is listen to the data and then learn or make adjustments accordingly.  In stark comparison Willett made no errors on his final 21 holes of the competition.  Perhaps he was listening to what his data was telling him of his play across the four days of the competition

My Personal Learning

After realising the importance of data in performance I decided to track my own stats.  I started this process a little over a year ago using a relatively inexpensive piece of technology designed specifically for golf called Game Golf™.  Essentially it tracks my stats in a very similar way to the PGA tour albeit with less granularity.  On one of my first rounds I shot 14 over the par of the course.  At this time this was playing to my handicap.  My stats were as follows:

At the time I thought “not bad stats for an amateur golfer”.  However I knew things could be improved.  After drilling further into my data it became clear that I was losing a lot of my shots by missing the green or not being close enough to the hole when I was on the putting surface.  So for the next few months I focused heavily on my accuracy from around 125 yards and in, as well as on chipping and putting.  The results of a round in early May (4 months later) are below:

My experiment had worked.  I had more than doubled the number of greens I was hitting in regulation and there was a 66% increase in my ability to scramble (make par or better if you miss the green).  Now all I needed to do was improve that driving accuracy!

How does this apply to learning in business

The Individual Learner

At an individual level it shows how improvements in performance or knowledge can made in short spaces of time.  The key is to ensure that any time spent on improving one’s self is focused in the right way and at the right area.  It is all too easy for us to slip into our comfort zone and improve the things we find interesting and are often already good at.  Identifying our deficiencies and tendencies can open up the possibility that our performance can far exceed what we previously thought achievable.

As an L&D Function

The lessons for the individual hold true for the broader learning function.  The complexity of the data could increase, as may the number of data sources, but when you distil it down it is all about understanding gaps and also not forgetting to notice the strengths.  Where an individual is striving for increases in their own personal performance an L&D function is trying to improve performance in relation to business goals.  The magic happens when you can identify a potential gap that, once filled, will directly result in reaching that business goal.  It could be reducing L&D spend, upskilling a division of the workforce, making learning more accessible, etc.  The key is that there is evidence of a gap and the decision to improve an area or take decisive measures has not been reached based solely upon ‘gut feeling’.

The reality is whether you are trying to win The Masters, beat your best round of golf, or achieve a business result, good analysis of reliable and relevant data can often get you to your desired goal faster and more efficiently.