An Example of Information Design

Let's say we're designing an attrition (attrition is when a customer leaves a company) system. When a customer call customer care, we give the representative a recommendation. We have a lot of options:

1. We can't ever know exactly who is going to leave so let's not address the problem.
2. Have an overall policy that treats all customers exactly the same.
3. Present an attrition score to the customer representative.
4. Present an attrition threat flag to the customer representative.
5. Give a graded response with reasons and some specific recommendations to the representative.

Depending on the company any one of the solutions may be appropriate.

If a company is going through a period of low attrition, ignoring attrition may be the best response. There can easily be more important problems for an organization to worry about. I have seen this happen in companies where attrition has been a critical focus of the company: the incremental effect of a new attrition-focused system is small. However, if attrition is a problem in the company (1) can be a foolish approach. It is usually impossible to tell who exactly is going to leave but good analytic design can tell you how to make bets and get a good return on your efforts.

Solution (2) is what companies usually do, and if the policy is well thought out this can be sufficient.

Solutions (3) and (4), while apparently more sophisticated that solutions (1) and (2) are asking for trouble, How are service representatives supposed to interpret the data they are given? If we give customer service representatives a raw score without guidance, then good representatives will worry about their interpretations and the attrition score will become a source of stress. If we give an “Attrition Threat: Yes / No” flag, then we've lost the ability to distinguish between a slight risk and a substantial risk. we'll be giving the representatives clear guidance but that guidance probably not be appropriate and the company will be worse off than if they had no policy.

What we want to do is solution (5): break the base down into segments with guidance and insight in each segment, making sure that our intervention is appropriate and effective in every case.

Still, there are lots of right and wrong ways of doing this -- more tomorrow.