Sorry to be repeating myself with the emphasis on “People”. But I feel compelled because over the weekend I ran across two pieces from a couple of my favorite old media friends — The Wall Street Journal and The New York Times — that highlight again the art versus science aspect of how important the “people aspect” is to the success of any organization.
First up is the Sunday NY Times article “Secrets of the Talent Scouts” by George Anders, highlighting the short list of ways professions ranging from venture capitalists to country music A/R guys go about making their bets on what they hope will be their next hits. One general theme highlighted in Anders’ piece is the focus on putting your money on young, passionate people. I agree on this one, especially if we are talking true early stage investing or finding the next sports, music or acting star. When was the last time you saw a 50-year old starting a semantic Web search start-up or launching a music career?
Now, in the spirit of full disclosure, I have met with George. In fact, we chatted just a few weeks ago about the angle of talent scouting in the context of sports scouting — specifically baseball scouting, something I did on a part-time basis for a couple seasons in the mid 90’s for the Chicago White Sox. It’s too bad George didn’t track down a sports scout for the story — it would have added another valuable dimension to a fascinating, yet amorphous topic.
From my perspective, evaluating talent is largely about pattern recognition. As with sports, the more repetitions you get, the better you get. There is predictive power in being able to say “this guy reminds me of that other guy from 10 years ago who flamed out in AAA” or “this team reminds me of those other guys who zigged and zagged before they locked in on their idea that they sold to Cisco for $500 million.”
Yet unlike sports, even with a long history of pattern recognition, you can still fall prey to false positives and false negatives. Cleary the former can be quite costly which is perhaps why the story didn’t talk too much about such examples.
Another story that I found interesting this weekend was the WSJ’s piece about evaluating the value of college basketball coaches, Matthew Futterman’s “College Basketball’s Bargains and Busts”. What’s great about this story is the very simple calculation that Futterman does to rank college coaches — at least the guys who make at least $1 million a year in salary.
By dividing each coach’s annual salary by their average Ratings Percentage Index (or RPI, the stat that measures a team’s winning percentage against the difficulty of it’s schedule), The Journal arrives at a simple number that basically calculates what a school pays in dollars for each RPI point. There you have it — a quick way to figure out is it worth keeping your coach or not!
Now, to be fair, this doesn’t take in to account other factors such as NCAA Tournament performance (e.g. Billy Donovan ranks pretty low on the list, but he has won a couple NCAA Tourney’s in the past 5 years) or how much revenue the coach’s program generates via gate receipts, merchandise and TV revenue (e.g. how many times a year does CBS put Jim Calhoun’s Connecticut Huskies on national television?).
But think for a minute how an approach like this could be applied to CEOs given today’s economic maladies. What if The Journal published a similar list of S&P 500 CEOs that tabulated their total compensation divided by the company’s EBITDA. From this simple ratio we could get a snapshot of how much a company is paying their CEO for each dollar of profit. Sounds simple, eloquent and down right unveiling doesn’t it? Maybe that’s why the Journal hasn’t done it?
I would love to see companies in today’s environment talk more about “pay for performance” in a credible way. Maybe a simple calculation a la what The WSJ has done to rank college basketball coaches doesn’t quite cut it, but something along these lines would be a welcome change to the divergent path between these two numbers that we see all to much these days.
Originally published on Medium on March 16, 2009. This Substack version is maintained as the canonical archive.