When “Data-Driven” Is Not Enough

Jun 26, 2019
Written by
Nick Reed
Nick Reed

When “Data-Driven” Is Not Enough

An enterprise architect friend of mine recently posed an interesting question: “I lead a relatively mature EA practice that delivers good value to our organization. We are digitally transforming the organization and adopting agile ways of working across the enterprise, which is improving our outcomes for individual initiatives. But I am worried these efforts are sometimes wasted on delivering capabilities managers tell us are important, rather than the ones that are truly game-changing. How do I get in front of this, and help lead us to the right strategic outcomes?”

This is a question many enterprise architects wrestle with on a daily basis. It goes beyond typical, well-established EA work into a more business-led strategic analysis of fundamental aspects of the enterprise, to understand which capabilities are truly strategic. To tackle the question, let’s approach it step-by-step.

When Data-Driven is Not Enough
When Data-Driven is Not Enough


The goal of EAs is to help their organizations make better decisions about how and what they transform, based on multi-dimensional analysis of factors such as business goals and strategy, business capabilities, processes, data and IT. By understanding the relationships and dependencies between these dimensions, EAs offer guidance to executives on the best courses of action to achieve faster delivery of desired business outcomes, with less waste and less risk. We describe this as enterprise architecture management. In other words, it involves maintaining an up-to-date, accurate enterprise architecture with “just enough” scope to deliver valuable analysis that drives better business outcomes.

This enterprise architecture uses data – in the form of a digital model of the enterprise – to enable advanced analytics providing deeper insights about the enterprise, in support of better decision-making. We call this data-driven model a Digital Twin of the Enterprise.

This data-driven architecture allows stakeholders to understand the current state of how technology and data support business activities in pursuit of strategic goals, and plan roadmaps for how the enterprise will deliver the future business capabilities and operating models for how it will operationalize them.

But the key question is: what determines the direction of this evolution?

The key goal of digital transformation is 1) innovation of existing business models, customer experiences, partner ecosystems and operating models, leveraging digital technology and data throughout the business to deliver new digital products and services; and 2) transformative increases in productivity and efficiency, based on automation and advanced analytics to deliver game-changing value.

These new business models and customer experiences require innovation, which may be generated in multiple ways: crowd-sourced across the enterprise, R&D-led by assessing emerging technologies, problem-led by focusing on customer needs/pains, or goal-led to achieve a specific objective. This innovation informs us which capabilities need to be created or improved; which are differentiating, “core” capabilities that provide strategic competitive advantage; and which are commodity capabilities to be operated at maximum efficiency.

Capability analysis also needs to inform what type of capability improvements are needed – are they investments in people and skills, cultural change, new technology or data services, or process improvements (or some combination of all of these). It will almost certainly involve an ecosystem of partners providing innovation and/or specific technology services and expertise as part of the overall approach.

The point here is these future business and operating models need to be designed – modeled – in order to inform and guide the evolution of the enterprise. This is what enterprise architecture is all about. A data-driven architecture is necessary as a basis for Digital Twin-based analysis of the enterprise. But it is not sufficient to describe the future business and operating models, and the new customer experiences and ecosystems, that drive the capability analysis to determine investments. Without this, your data-driven architecture is in danger of “flying blind.”

With Gartner saying 81% of organizations expect to compete primarily on the basis of customer experience, can my friend afford to not put this front and centre in his organization?

That’s what we think. We’re interested in what you think. Let me know at n.reed@bizzdesign.com.