A conversation brought up a topic which we called the 'Metadata of Expertise'. Data that relates directly to the description of expertise. A simplistic example might be a trend line extracted from sales data, which would be used to derive a prediction rule. Or a categorization of an anomaly that would lead to a selection of applicable rules. Like all metadata this needs to be managed in terms of lifecycle. Not unlike metadata of the usual kind.
'Metadata of Expertise'. At this point it is broadly described as a means of making sure you have, can deliver, and continue to update needed expertise. The expertise can be human resources, data, decision process or expertise than is embedded in systems.
Like Metadata in a database, it has a lifecycle that must be managed to keep it credible and current. In our enterprise experiments we found that the initial and continued credibility was one of the most difficult things to achieve. My particular interest now is how you use data analytics to make that happen.
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