Enterprise Architecture and Its Importance in Digital Transformation


The ever-changing landscape of technology services has led some to wonder if traditional enterprise architecture (EA) practices are any longer relevant.

In a world where IT decision-making has been devolved from the enterprise to the business unit, driven by digital trends such as SaaS, cloud, and mobile apps, the role of traditional enterprise IT can seem to be reduced to supervising legacy applications, traditional hosting services, and corporate services such as email. This appears to move corporate IT away from the business leaving some business users to question the value that enterprise IT brings to the organization?

The Problem

The playing out of this trend over the last few years has, however, uncovered issues that require an enterprise view, perhaps the most important being data quality and relevance. But security, performance, and accountability for coordinating business goal metrics and ensuring that IT spend brings value to the organization are also critical.

Many a time in my career, I have been asked to help a client with their “data problems”; what we often find on analyzing such organizations is that their “data issues” are actually a result of internal organizational silos, each with their own systems and data models, trying to manage complex business processes across these silos.

The failure to take an enterprise-wide view prior to buying or building technical solutions can lead not only to data problems as described above, but duplication of effort, complex, insecure, and difficult-to-maintain IT estate wherein too much time and effort is spent “keeping the lights on” and not enough in enabling business improvement.

In a world where edge computing, microservices, and DevOps are decentralizing IT architecture, we would argue for the need to have an enterprise-level understanding of the following:

  • Wherein the organizational capabilities should lie
  • What the data needs of the whole organization are and who should own and manage data
  • Managing security to a minimum standard across the whole enterprise, ensuring that applications perform sufficiently well to reflect their business criticality
  • Ensuring that IT budget supports business goals in a measurable way is vitally important

The Solution

This doesn’t imply that EA should micromanage what the business does, or claw back the recently acquired flexibility and responsiveness that these new trends give to the business.

Case Study: Impelsys has experience of working with a U.K.-based university consortium, seeking to transform their core business processes to take advantage of the opportunities offered by digital transformation.

Key areas prior to executing any significant change are:

  • An identification of the key business goals and the metrics for measuring success
  • An enterprise data model identifying the key attributes required to support the business goals
  • A high-level model of the main business processes
  • A capability model to ensure separation of concerns and avoid duplication of work and data within the business
  • A high-level technical architecture model to guide delivery
  • A set of security and performance standards and a method of ensuring compliance
  • A mechanism to assure delivery activities comply with the EA, including regular architecture review meetings and a RAID log for each delivery program

Deciding on the required amount of EA work required to meet an organization’s needs is vital. Many organizations, such as the above-mentioned client, are not large enough to maintain a full-time architecture team. They have never fully established a central EA function and much of the knowledge required to assure alignment of business with technology is scattered among different parts of the business.

The Benefits

In our experience, following this approach significantly impacts risk to delivery projects by identifying and mitigating risks early in the design process. The focus on business goal metrics decreases the time to business value and allows for an accurate measure of return on investment for IT spend. Productivity is improved by focusing on the elimination of duplication and the tuning of business process to remove bottlenecks and improve organizational cohesion and visibility of the state of key business processes. The considerable reputational and financial risks posed to business by personal data breach, denial of service, and ransomware attacks can be considerably reduced through the standardization of security and the proper management of data integrity through the enterprise data model.


Now, more than ever, the need for an appropriate enterprise architecture approach is vital for the success of any business attempting to make any significant changes. This need not be a long or onerous task but should be tied into the needs and the objectives of your organization. The additional effort required upfront will pay dividends in terms of business value, risk reduction, and ease of implementation.

For a more detailed discussion of how we can help your business through this approach, please feel free to contact us for an initial discussion.

Authored by – Maurice Leahy