Benefits of EA Metrics

Posted May 6, 2015 | Technology |

At a strategic level, EA metrics establish quantifiable parameters that enable practitioners to assess and evaluate the EA program, the IT assets employed, and their relevance to delivering business value for the enterprise. At a tactical level, EA metrics include parameters that impact EA and its effectiveness across the organization -- both directly and indirectly. By leveraging EA metrics, practitioners and business stakeholders can evaluate:

  • The benefits delivered as a result of applying architecture processes, models, frameworks, and technology standards
  • The alignment (or lack of alignment) between projects and programs and the business strategies they support
  • The ability of each individual project to overcome architecturally significant risks, constraints, and challenges
  • The common architectural risks inherent in the overall architecture planning for business transformation, application rationalization, or legacy modernization initiatives
  • The use of EA information, such as patterns, standards, and registries

Our recent Executive Report ("Methods for Defining and Analyzing Key EA Performance Metrics" addresses common pitfalls in selecting EA value metrics, discusses the attributes of effective metrics, and elaborates on the following key areas:

  • IT metrics
  • Customer metrics
  • Business/strategy metrics
  • Compliance metrics

Of the approaches used to measure EA value, one of the most important is return on investment (ROI), a performance measure used to evaluate the efficiency of EA investment, typically over the span of up to five years. ROI employs the benefit-to-cost ratio (B/CR), the ratio of EA benefits to EA costs. One significant challenge in calculating metrics is aggregating metrics that combine quantitative and qualitative data. The report discusses effective methods to quantify qualitative data, such as survey responses or other textual forms by analyzing and coding it. Qualitative data can provide in-depth insights into some of the biggest impacts made by EA, but since they are hard to quantify, they are not used often.

Aligning EA Metrics to Business Value Drivers

The challenge in measuring EA value is not a lack of metrics; it is knowing which ones make sense for an organization and provide the most "value" for the effort. The key to a successful value measurement program is to identify metrics that correlate to business key performance indicators (KPIs). The report describes the following process for deriving long-term EA value metrics that are aligned with the value drivers of the organization:

  • Stakeholder analysis/value mapping. This determines what value measures are the most important and most frequently cited.
  • Business capability analysis/value mapping. This helps in the understanding, categorizing, and prioritizing of business capabilities and then determining what value measures are needed for identified high-value business capabilities.
  • Stakeholder and business capability value measures mapping and analysis. This determines how much of an intersection exists between identified stakeholder value measures and core business capability value measures.
  • Metrics selection. This helps select those metrics that are of importance to key stakeholders and core business capabilities.
  • Performance improvement considerations. These ensure that the EA value measurement set continually aligns with changes in the composition and value sets of the key stakeholders and core business capabilities.
  • Communications considerations. These ensure that effective EA value communications plans are developed for different key stakeholder groups.

EA value metrics should align with the value measures utilized by the core capabilities of the organization as well as those measures utilized by key stakeholders. This process allows the EA team to directly show how it positively impacts measures that matter to the rest of the organization. Once accomplishing this task, the value of EA to the enterprise will not only be understood but assured.

I welcome your comments about this Advisor and encourage you to send your insights to me at

[For the complete discussion from the author on this topic, see "Methods for Defining and Analyzing Key EA Performance Metrics."]


About The Author
Brian H. Cameron is a Senior Consultant with Cutter Consortium and a member of Arthur D. Little's AMP open consulting network. He is the Associate Dean for Professional Graduate Programs and Clinical Professor of Information Systems in the Smeal College of Business at the Pennsylvania State University. Dr. Cameron is also Founding Director of the Center for Enterprise Architecture in the College of Information Sciences and Technology at Penn… Read More