With most sports conversations in the U.S. swirling around which college teams deserve (or not) to be in the College Football Playoff Semi-Finals, I might be out of step to be thinking about baseball right now.
I have had several conversations recently – including conversations within my own organization – around what kind of analytical talent is needed and when as an organization’s data analytics strategy matures. Should we be hiring data engineers? Database managers? Statisticians? Undergrads? PhDs?
I see a parallel here with baseball. Depending on your spending cap, you may be tempted to hire a Cy Young Winner for your little league team – having a Ph.D. Computer Scientist on your analytics team would be a huge coup – think of all the wins! The trophies! The free ice cream!
Well…maybe. Hiring a world class pitcher for a little league team is probably a bad idea for three reasons:
- The MLB champion pitcher’s skills can never be fully appreciated by the little league team. A pitcher with a 90mph curveball with a 12inch break will not win any more little league games than a pitcher with a slower fastball who can get the ball consistently across the plate – not to mention the appreciation of the 10 year old catcher.
- The other kids won’t play with him. A superstar data scientist will likely have difficulty fitting in. User acceptance and adoption of technical solutions is the hardest part of any digital transformation – learning new technical skills can be challenging. And solutions that depend upon broad-based proficiency with the newest technology might be a hard sell to people who have been comfortably using Excel for 20 years.
- Simply put, hiring the champion pitcher is an inefficient use of resources (even if you don’t have a salary cap). According to the most recent Burch Works Salary Study data science professionals with over 10 years’ experience, average over $250-$300K per year depending on the industry. Alternatively, more junior people with less than 3 years’ experience average less than $100K per year. Many organizations would be better served with 2-3 junior data scientists than with an expensive superstar.
The analytics maturity curve – like the journey from Little League to the Major League – is a process without shortcuts. You may be better off hiring a little league player who can grow into a Cy Young winner.
For more information about Flock Specialty Finance, contact Jennifer Lewis Priestley, CDO (email@example.com)