For the end of 2011, many around the blogosphere are forecasting what will be on hype next year. I often read that big data and mobile BI are on the hype. In this article, I will discuss about those technologies. Don’t believe the ads, those technologies aren’t game changer at all.
When deploying a model, one very important thing is to monitor the results. Does it work like you’ve expected? I’m not talking about pre production tests but following the life of your model. I use two kind of reports to do that : preventive reports and corrective reports. As you expect the first one is created just after the prediction and the second is created after the consequence of the prediction is known.
Lately, I was thinking on the difference between machine learning and simulation (for prediction). Machine learning use historical inputs and outputs to find subsequent outputs. Simulation, on the other side, asses you get the knowledge, i.e. the underlying model so you don’t need historical data to learn it. Sometimes you can use both methods to know something, sometimes only one method is available. After thinking about it, I find than the distinction between them is thinner that I thought.
Predicting the number of sales representatives on a particular time on a particular store is harder than expected. If you instrument the whole process, you could know the activity of your representatives (number of customers, average time of a transaction, activity rate, …). We could then predict the number of required representatives. We know the cost of having set too much of them but what is the cost of having to few representatives? How to value a missed opportunity, a customer unsatisfaction of the quality of service, the behaviour of a too much stressed employee?
It’s a damn good question which should be tightly correlated to your salary in an utopic world. In other words, how do you justify your existence?
Supposed you are doing a new product version (a software, a website, a car, whatever). It can be used internally to your enterprise or sell to client. In the later case, you guess you can look at the sales to see if your work was valuable. You can think the difference in benefits (positive at minimum) is a direct consequence to your work. Considering your salary and other costs, you can compute your ROI. If you don’t sale it, people which will use your new products could be instrumented, i.e. you can see if they improved theirs sales or benefits. Not so easy.
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