Measuring IT Value the Progression of How

Measuring IT Value

The progression of how enterprises measure information technologies' (IT) performance has been a progression from inward-centric metrics of performance to advanced analytics that capture contributions to strategic objectives. Chief Information Officers (CIOs) often measure their performance by cost reduction and system consolidation while Chief Executive Officers (CEOs) measure IT by the contribution to new business growth (Trkman, McCormack, de Oliveira, Ladeira, 2010). There are many strategic frameworks that enterprises use to map the contribution of IT, with the Porter value chain being the most prevalent (Porter, 1986). The intent of this analysis is to evaluate the most critical metrics that an enterprise can use to measure the effectiveness and efficiency of IT. These metrics also fuel the methods used to measure toe economic value of an IT department to a given enterprise as well. This aspect of measuring IT value will be defined in addition to evaluating the models used for measuring the economic vale of an IT department to a company. Finally there is a brief discussion of whether or not traditional financial ratios and measurements must be applied to measuring the value of IT or not. In reality these metrics are often only showing a part of the Return on Investment (ROI) of any IT investment. To get the complete picture of performance, enterprises needs to align their IT efficiency and effectiveness measures to specific strategy performance, and the Porter value chain is ideal for defining these interrelationships (Porter, 1986). Financial metrics only provide part of the insight into the ROI of IT needed.

Frameworks for Measuring IT Value

The frameworks that have been traditionally used to measure economic value of IT are no longer flexible enough to deal with the level of agility and complexity that enterprises are dealing with daily. These traditional frameworks including the Balanced Scorecard, Capability Maturity Framework, IT Costs vs. Benefits Analysis, and many others have been created primarily to measure IT's value in purely financial terms without looking at its strategic value (McShea, 2006). Each of these frameworks are also designed to take into account financial metrics that are easily defined and tracked, given the highly structured reporting systems supporting them. The metrics of IT efficiency, namely transaction accuracy, speed and scalability, along with inventory turns, managing of complex supply chain, sourcing and strategic systems performance, all quantified through relatively closed processes, miss the point (Columbus, 2008). The same holds true for those metrics that measure effectiveness, as the nature of these analytics is predicated on only those methodologies that can capture the most structured data. Measuring effectiveness with these limited methodologies that deal only with the most structured reporting processes only deliver 30% at best of all available performance data at best (McShea, 2006).

Given the constrained nature of analytics and metrics that are predicated only on the most measurable efficiency- and effectiveness-based methodologies in place in enterprises, it is not surprising their value is diminishing as uncertainty grows in the markets enterprises serve. CEOs are now demanding that the Balance Scorecard, IT costs vs. benefits analysis, and capability maturity frameworks have an element of customer-based data in them, at the very least, demand-driven insights and intelligence (Barrett, 2007).

The Transformation of IT Metrics

The traditional frameworks for measuring IT value including the Balanced Scorecard, IT costs vs. benefits, and capability maturing framework are today being modified to reflect IT's value to business strategies, not just cost reduction (McShea, 2006). This shift in how IT analytics and metrics are used is changing how enterprises organize and implement their communication and collaboration systems as well (Zhen, Jiang, Song, 2011).

Most significant is the change occurring in the cultures of organizations, with communication, collaboration and shared task ownership more prevalent than ever before. One of the best studies showing how the measurement of IT value can be used as a catalyst to create higher levels of communication and collaboration is that of the Toyota Production System (TPS) and the creation of a knowledge-sharing ecosystem (Dyer, Nobeoka, 2000). Toyota was able to take the traditional means of measuring IT and create a more efficient supply chain ecosystem by re-assigning the traditional, highly siloed IT metrics to specific line-of-business needs. This was accomplished through the use of a taxonomy of analytics and metrics that more closely aligned to their specific requirements. It then became not the primary focus, the success of the supply chain did. Through more effective use of communication and collaboration, the company was able to increase product introduction effectiveness and the pace of new auto development by 18% according to research completed in Toyota production centers throughout Japan (Dyer, Nobeoka, 2000). Another aspect of this approach to defining IT value by business strategy performance was the emergence of a hierarchy of supply chain metrics.

The measuring of IT value purely in terms of system and software consolidation had given way to the measurement of highly complex, highly orchestrated processes. Foremost among these is the Perfect Order (Novack, Thomas, 2004). Perfect order performance measures how effectively a given company manages its entire ordering, supplier coordination, sourcing, production and fulfillment processes, galvanizing all of them around the customers' expectations and requirements (Columbus, 2008). Perfect order performance is one of the more powerful metrics for evaluating if the IT systems in a manufacturing company are actually delivering value or not, as the orchestration of these processes would not be possible without high performance IT architecture (Novack, Thomas, 2004).