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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 Cloud computing is so big these days that I’m even getting emails from more or less reputable organizations imploring me to jump on the bandwagon and get rich off this latest fad. Clearly we’re well on our way if not already in the trough of disillusionment. As we pull out of the trough, we will have to deal with some very challenging issues – both technical and economic. On the technical side, I’ve been dealing with an interesting aspect of Speech recognition is like the fusion reactor of computer science. Fusion research is always “just 20 years away from practical applications”. This was the case in 1960, 1980, 1990 and 2000. All along we learned a lot of useful and interesting stuff, but we still don’thave access to clean, virtually limitless electricity. At one point in the early days of nuclear energy people actually talked about electricity being so plentiful that it would be “too cheap to meter”. And they I’ve often wondered why user interfaces always seem to be always constrained to the two dimensions on your computer screen. Certainly in the business information world this is the case. On my way home today I heard an interview on NPR with Michael Sweet from the Berklee College of Music in Boston that got me thinking. Sweet was talking about composing music for video games, which rely heavily on sound feedback to set the mood for the player. When the My ISP decided to stop delivering services to me this weekend. I suppose they got tired of taking my money and would prefer to see how things would work out if I didn’t pay them any more. Anyway, I get itchy when I don’t write for a few days so I took my lunch hour to finish this draft… When you are developing a product of any kind, you need to keep track of the requirements that dictate what goes in The decision of whether to add data to the database – in effect, denormalizing it to some extent – is partly informed by the need to reduce the overall complexity. As with the internet and the Charles proxy, the ability to see the raw data is always I’m currently reading Steven Pinker’s recent book “The Stuff of Thought”[1] in which he discusses how the structure of language provides insights to how the brain works. It’s one of three books I have on the go at any given time. Never have enough uninterrupted time to just sit down and read the whole thing – I guess that’s a lesson right there in how the modern brain works. I’ll give you one example of the kind of gem I’ve |
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