Archive for March, 2006

Are All Jobs Commodities ?

Wednesday, March 29th, 2006

The other day an IT professional in charge of staffing for his company said to me, "All labor is a commodity, including the CEO".  "Including the labor of doing your job?", I asked.  "Absolutely, of course", he said.  A lot of IT jobs have become commodities and work is moving offshore.  It got me thinking, what is a commodity in the labor market?  How do you avoid competing in a commodity market ?

A job is a commodity when enough people can do it good enough that employers choose the lowest cost laborer.   The key here is good enough.  Performing a job better than the competition doesn’t matter when better means more than good enough.  Are all jobs commodities ?  No, take the CEO as an example.  CEO pay keeps going up.  The worse CEO’s do, the faster their pay goes up (as a group).  Instead of complaining about CEO pay, assume it is rational and ask why are compensation committees willing to pay.  It is because the job is getting harder, and fewer are capable or willing to do it.  The lesson is clear.  Try to work on the hardest most consequential problems you can find.

Run dog, run

Tuesday, March 28th, 2006

DSCN7724, originally uploaded by trekr.

I’ve seen some fast dogs, but nothing like this greyhound. It must be part cat. Light, graceful and blazingly fast. Matt took this photo and it turned out pretty cool. The dog’s name is Sadie and she’s from a foster family that rescue’s pure bred Italian greyhounds from pounds.

Spring Mallards

Monday, March 27th, 2006

DSCN7716, originally uploaded by trekr.

The change of seasons in Texas sometimes last only days, or so it seems. In the last few weeks we’ve had record high temperatures, overnight freezes and nine inches of rain. The return of the mallards is a sure sign that spring is near. I’m hoping for some ducklings this year. We’ll see …

The Royal Empress Blooms

Wednesday, March 22nd, 2006

DSCN7424, originally uploaded by trekr.

This is the first year the tree has bloomed ! I’m expecting tremendous growth this year … stay tuned !

Why Interviewing to find Talent is Difficult: A Demonstration using Bayes’ Theorem

Sunday, March 5th, 2006

Suppose you are a hiring manager with a goal to make sure that the person you hire has some special quality called IT. IT can be anything you like. You have developed an interview technique in which the chance of success for a candidate that has IT is 95% and the chance of success for a candidate who does not have IT is only 5%. Suppose that amongst the general population of qualified candidates, only 5% have IT. After all you only hire the top 5% like everyone else, right ? What is the probability that a candidate who does not have IT will be selected ? Surprisingly, 50%, the same chance as a candidate who has IT. For example, suppose it is possible for you to interview 100 candidates. Only 5 have it and you will correctly identify all 5 of them (I’m rounding up). Ninety-five do not have it, yet you will also identify 5 from this group as having IT.

Now suppose IT is really rare and only 1% of the qualified candidates have IT. However, you are better at testing for IT so you can identify those with IT 99% of the time and you can also identify those without IT 99% of the time. The end result is the same as the first example, the probability of selecting a candidate without IT is 50%, you pick 1 from each group. Put another way, the probability that any candidate has IT is 1% prior to the interview but the interpretation of the probability rises to 50% after the interview, regardless of whether they have IT or not.

In both cases, the probability of a false negative was high relative to the prior probability of having IT.  If however, we take the candidates identified as having IT from the first interviewer and a second interviewer with equal skill screens them, then the odds of correctly identifying a candidate with IT are greatly improved because we start with a 50% probability that the candidates have IT.

The next time you are tempted to brag about being a great interviewer capable of finding the very best, keep the thought at Bayes and employ a process of sequential, multiple interviews to improve your odds.