I read an interesting article about how the pendulum is swinging back to centralization of IT resources. Two of the most important results are an increased effectiveness in decision rights – the way technology investment decisions are made – and in information flows from IT to the rest of the business. This is related to, but not identical to some of the observations I’ve been making in this blog. With centralized data, everyone can see the same information as it
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In my previous post I discussed the challenges related to quality of predictions and inferences you can make from data you collect in a corporate repository. Fortunately, the data you collect are not all required for making inferences. Some of them are extremely useful no matter how much data you have. It all depends on what you intend to do with it. The following is a list of categories of metrics that can be used to shed light on your organization I can see in my mind a Hollywood movie where a junior employee (a junior actress in a cameo role) runs to the shop floor to her cigar-chomping boss (a well-known character actor in the latter part of his illustrious career), shows him a chart that clearly demonstrates a fatal flaw in the factory operations, he takes decisive actions to fix the situation, and together they take over the world of widget manufacturers. This, of course, never happens. Somehow Hollywood Ultimately, that is the lesson of metrics in a knowledge-based industry: No one metric is going to tell you the answer you are looking for. Metrics that work in some circumstances will not work in others. Even from one company to the next, in the same industry, following the same methodologies, you are going to find some unexplainable |
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