Monday, January 26, 2015

The simplest solution...

Often people from different parts of the business come to me when they're in trouble.  This trouble generally stems from some program not working like they expected, or a revenue shortfall.

A couple of things define these requests:

  1. They're looking for some "data magic"... essentially some large scale statistical model to figure out the problem, define a path to solution, implement some kind of decisioning, or at the very least, explain why they shouldn't be fired. 
  2. By the time they come to me the situation is really bad.

The second point here is interesting, because of a correlation I've observed:

The worse a data problem seems, the simpler and more fundamental the likely problem.

This means that I field quite a few requests, where the solution is quite simple, and generally, quite upsetting to the business.  Here are a few examples of data science requests, matched with their solutions:

Q: Can you put a model together to determine why our paid search campaign isn't working?
A: The "apply now" button has been broke for six months.

Q: Why is our web conversion rate low?
A: Because your website looks most like a spam site.

Q: Why are final revenue numbers 20% lower than initial, is accounting wrong?
A: Because you have a 20% cancellation rate.

Q: Why aren't sales people doing what we want?
A: Because your incentive plan creates a perverse incentive not to work hard.

I realize that these type of problems will likely continue to come my way, but they form the basis for an important lesson learned:
When analyzing seemingly horrible and counter-intuitive business results, start from the beginning, and look for the simplest solutions.

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