The smart data discussion and strategy place greater emphasis on having the ability to predict, prevent, and mitigate problems before they happen; this is called predictive management. Foreseeing the future with a higher degree of certainty requires:

  • Knowledge about history
  • Knowledge about the present situation
  • Knowledge about developing new technologies
  • Knowledge about evolving future needs and trends
  • Knowledge about competitive threats
  • Knowledge about capacity for change and improvement

All of these things are addressed by data that describe how things get done and their associated metrics. In anticipating the future, data is needed that addresses possible scenarios for which probabilities are determined about their possible occurrence.

Data is made useful through applying various analytical techniques, methods, and algorithms. The smart data paradigm encourages executives to press for better data and best methods and algorithms to support their requirements.

Information technologists employ a host of techniques to design and develop complex systems and software. UML is a popular family. For executives, we return to IDEF because it is the simplest way to address critical elements that includes accounting for enterprise data in context of process performance. By applying IDEF process modeling and other data modeling techniques, executives can visualize an operating enterprise at various degrees of aggregation or decomposition (detail).

Other modeling techniques ...

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