JUL 13, 2012 11:27am ET

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Philosophical About Perfect Data


Good thoughts and responses to last week’s column on Living With Imperfect Data, which postulated, “Sometimes it’s better to have everyone agreeing on numbers that aren’t entirely accurate than having everyone off doing their own numbers.”

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Comments (3)
Certainly, Sales, Operations, Product, and even the customer look at things in different ways simply because each different way of looking happens within a particular context of a particular process or function. But when multiple versions of the truth pop up within the same context, there is a problem. Additionally, problems arise when truth is asserted without context.

Still, a certain single truth remains: Underlying all the varying enterprise contexts, processes, and functions is but one foundational, holistic, naturally and fully integrated enterprise structure. Mess up that truth to a great extent with disparate "silo" data solutions, then the thinking that "as long as the data are good enough to make sound decisions ..." merely rings as a rationale for inaction to do better to improve data quality and to do it continually.

Posted by Ed J | Monday, July 16 2012 at 1:26PM ET
Jim's article shows quite well that new categories of data occur and that new rules need to be defined. Imperfect data required: Decisions are already taken when selecting the data we track, when selecting data and data structures for reports and not to forget when defining the decision fields itself. Just repeating the well-known following story: A drunk loses the keys to his house and is looking for them under a lamppost. A policeman comes over and asks what he's doing. "I'm looking for my keys" he says. The policeman states: "But there are definitely no keys here around". The drunk: "But searching with light is so much better". A free translation into Jim's topic: The more decisions extend into the future the less reports on structured 'accurate' data are really helpful. Two examples: To improve business processes it makes sense to check the free text communication of bookers, planners, dispatchers, invoice operators. To get a feeling of consumer markets the collection of customer pain points in blogs etc. is most useful. There are a lot of similar examples to get an idea about the health of suppliers or VIP customers. Rules for imperfect data required: The use of data has always a 'legal' dimension. As Jim said you cannot always wait for all data covering a decision. A decision has an optimal time window to be taken, too early or in our case too late the additional costs can be tremendous. But if based on existing structured data these data should be accurate. Other rules need to be defined to treat and use unstructured data, Big Data, or other by nature imperfect data.
Posted by Peter K | Monday, July 16 2012 at 2:30PM ET
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