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IT Complexity Metrics – How Do You Measure Up?

Journal 34: Cass-Capco Institute Paper Series on Risk

Peter Leukert, Andreas Vollmer, Bart Alliet, Mark Reeves

Commerzbank and Capco have worked out a practical solution, by creating an IT complexity model and management decision tool. The tool is based on a number of specific and measurable IT complexity indicators, organized in a structured IT complexity analysis framework.

IT complexity is so important that “learning through failing” is no longer satisfactory given that this form of complexity so clearly and harshly impacts the cost, delivery quality, and flexibility of the IT landscape.

We now need a robust and functioning model for complexity measurement and mitigation. This paper describes how Commerzbank, in partnership with Capco, is deriving such a model. We also examine how it can be developed over time to provide a cross-industry standard. Specifically, we will be looking at:

  • The shape of the model – how Commerzbank, with Capco’s input, models complexity at the moment.
  • The key components – a deconstruction of the key components of a rigorous under-standing of complexity – the indicators – covering applications, interfaces, data, and infrastructure.
  • A pathway to live implementation – over-view of the key steps required for an organization to start using rigorous, predictive complexity insight as a management lever.

IT complexity can and should become a leading indicator for IT performance management
Typically, the CIO scorecard contains the following key performance indicators: costs, flexibility, and quality. Sadly, these are “lagging” indicators whose current values typically result from choices made many years previously. Most experts agree that IT complexity is a key hidden variable. As such, it is a “leading” indicator supporting the prediction of costs, flexibility, and quality that should (must) be used in today’s IT management decisions. IT complexity is, however, very difficult to master, since it creeps up, growing incrementally (but can only be reduced by a substantial management intervention), is not purely local (it occurs locally in many different applications and inter-faces, but the impact is only perceptible on the aggregate level), and cannot – until now with our model – be measured (a valid measure for IT complexity does not exist elsewhere, either in academia or in business).

And, as we all know: “what cannot be measured, cannot be managed.”

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