Historically, one critical function of enterprise architecture (EA) has been to identify and manage standards for the corporate technology ecosystem. However, in the digital age with increasing corporate complexity, how can an EA team keep up with the fast-moving changes in the technology landscape? Do standards even matter in a cloud-native world?
Yes, they still matter! However, perhaps the way we manage these standards needs a fresh look.
One of EA’s most critical responsibilities is to manage the long-term technical direction of the company to ensure the complexity remains in check. However, the traditional governance approach may no longer be effective. In many companies, there is a perception that EA’s technology governance is “prohibitive.” EA controls 100 percent of what technology teams can and cannot use. Invariably, the business often feels like they are being forced to use something that doesn’t quite fit their needs.
"Communication about technology decisions needs to be shared across business units and – a federated model will require more communication and collaboration across teams"
Moving toward a more “prescriptive,” federated model is likely to provide a win-win environment for all parties. A prescriptive model focuses more on what teams should do vs. what they cannot do. A federated model creates a hierarchy of architectural realms—think federal, state and local—where different levels of governance and control are applied.
At the federal, or enterprise level, EA will focus on core, foundational elements of the architecture, including security, information management and systems or record (to borrow from the Pace Layering view). These almost become architectural “policies”, which allow EA to focus on a much smaller set of standards and patterns, i.e., what matters most. Whereas at the state and local levels, EA governance may allow any technology that is best suited for the businesses’ needs, so long as no federal or state policies are violated. Sure, affordability, complexity, interoperability, etc. are still important measures, but perhaps, not the overarching focuses they once were.
The digital enterprise requires more speed and agility. Providing more prescriptive guidelines, instead of prohibitive rules, ensures a balance between business flexibility and enterprise compliance.
However, as governance shifts, visibility to the entire technology ecosystem becomes more critical. EA must have the tools and ability to see what is being used, where and by whom. Communication about technology decisions needs to be shared across business units and – a federated model will require more communication and collaboration across teams. At Cardinal Health, EA produces several dashboards to measure and monitor “complexity” for each business unit, such as application counts, health, total cost of ownership and a variety of other measures filtered by unit and business process. CIOs have incentives to drive annual improvements in their complexity scores, for example: reduce cost, lower app counts, improve health, etc. EA helps drive the improvements, but ultimately, the IT solution teams are accountable. In turn, EA focuses on the rules of the road and the architectural policies and leaves everything else up to them.
As cloud tools change every day, there is not enough time nor capacity to evaluate every single tool. Rather, EA should focus on the decision trees to provide guidance to the teams making the technology decisions. As an example, these decision trees could help determine when to use cloud-native vs. cloud-agnostic solutions – balancing operating costs with switching costs if cloud-portability is a requirement.
Adopting this type of model provides a nice balance of governance and control with flexibility and speed – shifting where and how decisions are made to where they matter most. This shift allows EA to focus less on reviewing and approving “all” technology decisions, and spending more time on the patterns and guidelines of how technology should work within the environment. That said, EA cannot not abdicate its role in helping select and recommend technologies. Decisions at the state and local levels are made with the business units or teams, and not for them. Ideally, EA provides teams more flexibility and control over their technology decisions, while also shifting accountability for the impact of these decisions to the teams making them.