Let's start with the customer usage profile. To start out with a project that's intended to give individual recommendations to customers and start that project by assuming that all customers act the same is amazingly dense. The Rate Plan Optimizer project manager explained that they had a study done several years ago saying that most customers were fit pretty well by their profile.
First off, a study done a few years ago doesn't mean that much in a constantly changing world, not when data can be updated easily. Second, even if most customers are pretty well fit by the profile that means that some customers are badly fit by the profile and will be negatively impacted by the system's recommendations.
The reason that the IT department went with using a one-size-fits all usage pattern was that the customer data warehouse did not actually have customer usage data in it, only how the customer was billed. The IT department should have taken this project as an excuse to get the usage data into the data warehouse. The customer recommendations could have been been done at an actual customer level.
The next major problem with the Rate Plan Optimization project was choosing the rate plan that was most profitable to the company and then suggesting the customer adopt that plan. In other words, the Rate Plan Optimizer had the goal of making the customer's bills as large as possible and making sure the customer got the worst possible plan from the customer's standpoint.
How to fix it? That's tomorrow.