Enterprise Architecture (EA) has been around for longer than we might think. The foundations were laid in the 1960s, with the field coming into its own in the 1980s after the emergence of computers in the workplace.
Companies needed a plan to keep up as technology evolved and, just like that, a new discipline was born. This culminated with pioneer Enterprise Architect (EA) John Zachman’s paper, “A Framework for Information Systems Architecture” being published in 1987.
In very basic terms, EA was (and still is, mostly) a "blueprint" that defines and describes how to manage the structure and operations within an enterprise. This rings true today even though Enterprise Architecture has evolved since the early days of static models, graphs, and charts.
Enterprise Architecture: Evolution via Democratization of Data
Traditionally, authority in the outputs of EA is granted by seniority that tends to be found outside of the Enterprise Architecture team. Subsequently, the old-school “true” EA data plays a supporting role at best. EA teams often have one stakeholder they are desperate to target and influence: the CIO (Chief Information Officer). They spend time and resources manually creating diagrams and visualizations in the hope that it cuts through and makes their argument for them. The data behind their point gets lost in presentation aesthetics.
Keeping pace with changing customer preferences and the emergence of new technologies requires companies to evolve accordingly. Digital transformation, i.e. the integration of digital technologies across a business to help them optimize their operations, becomes unavoidable. This digitalization helps companies to meet customer demands, enhances their employees’ experiences, and delivers operational optimization.
Enterprise Architecture becomes critical for delivering these successful digital transformation projects. It can, for example, create a roadmap of how to implement these new technologies, while improving how the business operates, and helping to align business and IT strategic goals.
However, to keep up with this digitalization, EA also needs to evolve to stay relevant and appeal to all of the decision-makers across a business. This need to open up to everyone within a business has helped propel businesses into new Enterprise Architecture. Democratizing EA outputs alongside inputs from across the organization gives EA data a new sense of authority. It impacts at a scale that the more traditional EA approach could only dream of.
"New EA” includes improvements in platform functionality and visualizations in terms of rendering, layouts, configurability, and out-of-the-box AI-facilitated iconography.
An evolution of the EA “success story” can be seen in the launch of Ardoq’s Discover module. Discover gives easy access to real-time, contextual insights with a user-friendly and intuitive interface for everyone across a business, not just Enterprise Architects. It means that anyone in a company can access and contribute to data without the need to fully understand EA and how it works. This democratization of data shows just how much EA has evolved from its 1980s iteration.
Enterprise Architecture: Evolution Into New EA
As businesses become more reliant on digital technology and scale and enter new markets, they naturally become more complex in structure and operations. This complexity creates tricky business questions related to the growing, web-like ecosystem of people, business processes, applications, data, and security. All of which, by the way, need to be presented in real-time or near real-time. The new era of EA focuses on delivering contextually relevant and bespoke decision-making input for answering these complex business questions.
New EA can be likened to “ecosystem architecture”. It involves real-time, augmented intelligence around the enterprise and the ecosystems in which it operates. It delivers contextually enriched machine-to-machine and crowdsourced data. The results mean decision-support intelligence in a language that both business and IT executives can understand.
New Enterprise Architecture increases operational efficiency and strategic agility. Backed by accurate data, it delivers real-time contextual intelligence and faster decision-making, not framework-constrained rigid architecture.
Evolution From Static to Dynamic Data-Driven Visualizations
Being data-driven no longer means endless spreadsheets manually filled with data, but an automated system that pulls the right data at the right time and that displays it in an easy-to-digest format.
Coping with the demands of today’s businesses means that EA data needs to be business-friendly, accessible, and provide an informative analysis instantly. It’s helpful to consider this from the consumer perspective.
Take the executive management team or whoever in a company is responsible for making the “big” business decisions. They are unlikely to understand EA's ins and outs, in terms of the metamodels, frameworks, and architecture. Instead, they want to be able to instantly, or nearly instantly, see the information that matters most in a context that is relevant to the business decision they’re trying to make.
Meaningful insights presented in an accessible format are one of the most useful things for management to make informed decisions with. The approaches offered by Ardoq, such as crowdsourced data collection via Surveys, can gather data from the business side without these stakeholders needing to learn how to use an EA tool.
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Staying in Control as Businesses Evolve
While Enterprise Architecture has helped businesses to adapt and grow with the introduction of digital technologies and changing customer expectations, it’s also evolved into a necessary tool for monitoring and combating external risk factors.
The “top 5” disruptive external forces, according to a report by Gartner, are as follows:
The Business Ecosystem
Before the digital era, businesses could be managed as single, stand-alone entities within their industry. The advent of digital means that value creation has shifted to the entire ecosystem that surrounds and supports an organization. It’s affected by all of the interactions of a company, such as customers, partners, suppliers, organizations, and “things” (via the “Internet of Things”). The relationships here are constantly evolving. They are complex and dynamic. To manage this complexity, organizations need to adapt and evolve to survive the unpredictability of the digital business ecosystem.
Organizational Complexity
Digital businesses rely on digital platforms that allow them to connect and exchange information with the plethora of partners, providers, and customers that comprise their wider ecosystem. As this ecosystem evolves, so do the digital platforms. As a result, the technological foundations of the platform can quickly become very complicated, while the business models are in a constant state of change.
Rate of Change
In the pre-digital age, enterprise-sized businesses could take a leisurely 3-5 years to react to changing technology cycles. In some industries, it could take about 10 years before change became critical. This has now shortened to around 2 years, thanks to the speed at which new technologies adapt and competitors enter the market and cause disruption. It’s also much harder to predict the future.
As 2020-2022 has taught us, global pandemics, interest rate rises, and energy costs can take us by surprise and cause dramatic and unforeseen impacts on our businesses. In such an environment, enterprises have to develop capabilities for rapid analysis and change quickly so that they can pivot with the market.
Digital Threats
A consequence of all the people, data, and businesses connected via digital platforms is that the threat to cybersecurity is both a constant and yet hard to control. Cybercriminals are more sophisticated. As Cybersecurityventures.com reported, cybercrime-inflicted damages totaled $6 trillion USD globally in 2021. Businesses must be able to continuously identify and plug gaps in their digital defenses, with real-time security capabilities.
As CIO.com explains, if an enterprise doesn’t have the proper level of cyber resilience built into its storage and data infrastructure, the result is a huge gap. This is why, on average, it takes an organization nearly 300 days to figure out if they have even been infiltrated by a cybercriminal.
Businesses need to recognize that robust digital security is not only essential but can lead to a competitive advantage.
AI and Machine Learning
It would be virtually impossible for one individual to understand and react to a digital business ecosystem in real time - they’re far too complex. So, businesses consider the possibilities offered by Artificial Intelligence (AI) and machine learning. However, these technologies are new and require enormous investment, take longer to implement, and also require extensive configuration. They’re also far from being able to make the same decisions as a human would.
These factors are all important for business performance, but they are difficult to control. EA is one approach that can help businesses to solve these problems and maintain control.
Ardoq: Enterprise Architecture Evolving to Meet Business Challenges
Like businesses, Enterprise Architecture has also evolved to keep up with changing needs. The result seen in digitally-native SaaS (software as a service) platforms like Ardoq, is a much less rigid form of EA that helps business and IT leaders to navigate the digital business ecosystem.
Enterprise Architecture’s evolution has turned a discipline that was understood by very few into something that can help many people across a business understand the impact and alignment of their business strategy. EA tools like Ardoq can also help businesses to do everything from target people across the organization using Broadcasts, to create a high-level view of all data using Dashboards.
EA has evolved massively since its inception. Like businesses, it’s gone through its own evolution process in order to stay relevant and add value. Who knows what the next 40-50 years will bring?
See how EA can help your company’s evolution and book an Ardoq demo today.
