Capco Blog

Measure and control IT complexity, before it controls you

What if IT complexity was a discrete, measurable metric rather than a discretionary, ambiguous term? Could a complexity metric reshape the decisions and activities of a chief information officer? Germany-based Commerzbank and consulting firm Capco have developed a model for measuring IT complexity in the financial services industry.

Complex systems and our limitations in managing them have been the subject of academic attention for some time. Sargut and Gunther McGrath (2011) point out in their recent article in Harvard Business Review that “collectively we know a good deal about how to navigate complexity, but that knowledge hasn’t permeated the thinking of most of today’s executives or the business schools that teach tomorrow’s managers.”

In a commercial environment, decision-making often requires an understanding of entire business and IT infrastructures, something that may be beyond the cognitive limits of an individual. In an interview with HBR in September of 2011, Michael Mauboussin, the chief investment strategist at Legg Mason Capital Management, suggested that “people seek to improve complex …systems, sometimes with disastrous consequences.” Complex systems behave and interact in ways that are difficult to predict, and our instinctual response is to reduce, rather than manage, the layers of complexity.

Without a doubt, an appropriate level of complexity is necessary for a business to provide a cost-effective infrastructure and maximize returns, while allowing for differentiation, greater flexibility, and growth. However, today’s multi-layered and interconnected IT environments cannot be managed with traditional financial analyses or experience-based approaches. In a vicious circle, it is those largely experience- and intuition-led CIO’s (chief information officer) decisions that influence IT complexity. Complexity in turn drives up cost, makes quality harder to achieve, and reduces flexibility.

A complexity metric will help CIOs articulate short and long-term implications of initiatives, costs over time, impacts on existing operations and the business as a whole, strategic implications, and justifications of high-risk projects. It is not a substitute for the hard-earned CIOs’ experience, but a reliable instrument to complement their expertise and intuition.

How do you measure complexity?
In its current state, the Commerzbank/Capco complexity model applies to the IT application and infrastructure landscape. The model consists of several indicators mapped across the relevant dimensions of application complexity – functions, interface, data, and technology. These indicators cover the various aspects of IT complexity and have been statistically validated through quantitative research, using Commerzbank data on approximately 1,000 applications over three years. A distinction is made between business-driven IT complexity and that caused by design and implementation decisions, to determine reducible levels.

Our research found a statistically significant correlation between key complexity indicators and cost indicators (such as running costs) as well as quality indicators (such as the number of production incidents occurring). A tacit inverse correlation exists between complexity and flexibility which is difficult to quantify, as there is no zero-base standard for future time to market. As the model evolves, we envisage extending it to a broader IT landscape as well as business processes and operating models.

While the body of academic work on IT complexity matures, Capco and Commerzbank demonstrate a practical application of IT complexity measurement within a leading financial institution. Our metric-based approach to complexity is designed to drive up understanding, insight and ability to predict the impact of potential decisions about the future IT state of a business. We are confident that this on-going project will be a step towards bridging the gap between academic knowledge and commercial employment of IT complexity management.

View the full IT Complexity: Model, Measure and Master paper.

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