Page 409 - Using MIS

we have a stream of bad luck and none of them buys. and missing. There was no way we could know ahead of
This bad result doesn’t mean the model is wrong. But time that it would happen, but it did.
what does the salesperson think? He thinks the model is “When the time came to present the results to senior
worthless, and he can do better on his own. He tells his management, what could we do? How could we say we took
manager who tells her associate, who tells everyone in the 6 months of our time and substantial computer resources to
Northeast Region, and sure enough, the model has a bad create a bad model? We had a model, but I just didn’t think
reputation all across the company. it would make accurate predictions. I was a junior member
“Another problem is seasonality. Say all your training of the team, and it wasn’t for me to decide. I kept my mouth
data are from the summer. Will your model be valid for the shut, but I never felt good about it. Fortunately, the project
winter? Maybe, but maybe not. You might even know that was cancelled later for other reasons.
it won’t be valid for predicting winter sales, but if you don’t “However, I’m only talking about my bad experiences.
have winter data, what do you do? Some of my projects have been excellent. On many, we
“When you start a data mining project, you never know found interesting and important patterns and information,
how it will turn out. I worked on one project for 6 months, and a few times I’ve created very accurate predictive mod-
and when we finished, I didn’t think our model was any els. It’s not easy, though, and you have to be very careful.
good. We had too many problems with data: wrong, dirty, Also, lucky!”

DisCussion Questions

1. Summarize the concerns expressed by this data analyst. was ineffective, maybe even wrong, what would you do?
2. Do you think the concerns raised here are sufficient to If your boss disagrees with your beliefs, would you go
avoid data mining projects altogether? higher in the organization? What are the risks of doing
3. If you were a junior member of a data mining team and so? What else might you do?
you thought that the model that had been developed

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