Enterprise Architecture (EA) has been crucial in helping businesses understand their internal infrastructure for decades. During that entire time, however, it has been somewhat resistant to change. The future of Enterprise Architecture needs to focus on transparency and enabling businesses to adapt to changes that will provide long-term financial benefits. While the digital landscape it oversees evolved dramatically around it, those practicing EA tended to remain steadfastly loyal to the discipline’s roots.
And, largely due to EA’s inability — or perhaps reluctance — to change, it has journeyed through plenty of turbulence. In 2007, Gartner predicted that ”by 2012, 40 percent of enterprise architecture programs will be stopped,” only to state in 2015 that “70 percent of organizations are starting or restarting an EA program.” As these two very disparate quotes suggest, EA has recently gone through a period of great transition and change, and it was sorely needed.
Important lessons have been learned over the last decade or so, but the primary takeaway is this: EA needed to change to remain relevant, and such change meant completely reevaluating EA to make it as beneficial to businesses as possible.
Entering the Era of New Enterprise Architecture
So what matters most in EA today, and what approaches should be utilized? Our market research has revealed that three things matter most to progressive enterprise architects and their CxOs who endorse new EA practices. Let's jump into it:
1. Ease and Automation of Input
For an Enterprise Architect to deliver ’quick wins’ in addition to laying the foundations for more long-term transformation, the EA platform’s design plays a critical role. This means enabling out-of-the-box integrations and eliminating the need to learn a specific UI just to interact with the product.
Putting this into practice means having pre-built data import integrations from Excel, AWS, or ServiceNow, for example, in addition to enabling user-friendly participation features. This allows diverse and broad stakeholder communities to participate in business process mapping, analysis, and validation feedback loops.
All EA programs are only as good as the data in the platform, hence why it is crucial this is highly automated and simple to operate manually.
2. Artificial Intelligence and Information Augmentation
AI is a complicated subject, and that is partly because its parameters are in a constant state of flux. As technology advances, and as computers become more capable of understanding and subsequently learning, AI is revealing itself to have more and more applications across any number of business functions.
In the context of EA, AI is showing particular promise across graph-based EA platforms, where data is, by default, in a structured format. AI allows enterprise architects to run automated — even self-learning — graph searches across many layers of different data sets, all interconnected on the same graph.
Given the complexity of EA tools, their ever-expanding functional realms, and the nature of their use for analysis based on syndication of large data sets across different business realms, this is an area where AI will drive real results, delivering maintenance simplification and intelligent insight directly to appropriate stakeholders, all in a personalized way.
However, most organizations may still be better served focusing on IA (information augmentation), instead of rushing to immature first-generation AI solutions. Putting IA ahead of AI in EA means ensuring data is structured, and that there are appropriate links (relationships) between different data sets.
3. Enabling Architects to Communicate Effectively
In the past, Enterprise Architecture visualizations have tended to be cluttered, rendering stakeholders stuck or at least very difficult to see what is relevant to them. EA tools are rarely designed for communication, so it is here that most EAs could use an additional helping hand.
The EA tools that deliver a more powerful and effective approach to EA are customizable and have easily digestible visualizations natively from the platform. Healthy engagement across an organization solidifies EA into a discipline at the forefront of digital transformation.Ardoq This article is written by Ardoq as it has multiple contributors, including subject matter experts.