Most leaders acknowledge the potential benefits of Digital Transformation. If they get it right, their enterprises will be more efficient, agile, and capable of delivering innovative products and services to customers and partners via multiple channels. Unfortunately, Digital Transformation takes a long time to produce value if done correctly. However, when done incorrectly, it can waste a lot of time, effort, and resources. This is where using Enterprise Architecture can help!
Enterprise Architecture (EA) leaders have numerous opportunities in today’s rapidly changing business environment. These practices that were once useful are now becoming obsolete. Enterprise Architects have an unprecedented opportunity to define a new vision for EA and their teams.
By 2023, 60% of organizations will depend on EA's role to lead the business approach to digital innovation.
Gartner
Gartner also states, “More than 90% of enterprises will have a multicloud infrastructure and platform by 2025, but less than 10% will have an effective multi-cloud complexity strategy.” This roadmap is intended to support the modularity, autonomy, and orchestration of distributed D&A workloads by focusing on the development of the appropriate strategy, architecture, and, most importantly, operationalization with hybrid and multi-cloud implementations. You might be wondering what this means for my business. Well first we must understand what digital transformation is to have a better understanding of why it matters to your business.
What is Digital Transformation?
Digital transformation helps an organization keep up with emerging customer demands and therefore survive in the future.
Digital transformation approaches all aspects of a business with a customer-driven, digital-first mindset. It leverages data to drive intelligent workflows, faster and smarter decision-making, and real-time response to market disruptions using AI, automation, hybrid cloud, and other digital technologies. Finally, it fulfils customer expectations and opens new business opportunities.
Its goal is to establish a technical and operational foundation that will allow it to evolve and respond to unpredictable and ever-changing customer expectations, market conditions, and local or global events in the best way possible.
Digital Transformation is better thought of as continual adaptation to a constantly changing environment.
MIT Sloan Management Review
What is Enterprise Architecture?
Enterprise Architecture is a discipline that identifies and analyzes the execution of change toward desired business vision and outcomes to lead enterprise responses to disruptive forces proactively and holistically. EA adds value by providing business and IT leaders with ready-to-sign recommendations for adjusting policies and projects to achieve specific business outcomes that capitalize on relevant business disruptions. So, how does using Enterprise Architecture help your business with Digital Transformation?
Importance of Enterprise Architecture in Digital Transformation
Enterprise architecture allows businesses to communicate their technology roadmap plans across the organization. Strategic planning has always been important in business, especially because of the complexity and urgency of digital transformation initiatives.
Enterprise Architecture (EA) assists businesses in documenting their current and desired states. Companies’ digital infrastructure, processes, and capabilities are critical to this process. EA is a strategy used to achieve specific business objectives, and firms must be agile, adaptable, provide high-quality services, and be customer-oriented to achieve their goals. EA is also regarded as a critical factor in business design. In other words, it documents the current and desired states of the companies’ strategic goals.
How Can a Digital Transformation be Successfully Implemented with Enterprise Architecture?
At the most basic level, thoroughly understanding the customer is the first major step toward a successful EA engagement. Without an understanding of the business model or industry, internal politics, and culture EA teams fall short of becoming trusted advisors to the C-suite.
As a result, EA teams must engage with the appropriate decision-makers early on to develop those key relationships and lay the groundwork for a long-term strategic value. Without those preliminary introductions, EA teams will struggle to lead any transformational initiative if they are only on the bench as backups.
Once the C-suite has agreed to the EA team’s digital transformation vision, the next step is to create an ideal customer journey map, or a potential roadmap to address their pain points and business challenges.
This strategy can be used in two ways. During the initial discovery phase, EA teams can mentor the C-suite and explore multiple options or ideas, then provide recommendations to address gaps in their current journey toward an ideal state. Based on their level of digital maturity, many customers are already nearing the finish line in terms of meeting their goals and objectives. Advising on best practices has become the preferred approach that EA teams can provide in such cases.
Getting Started
Data technologies are evolving quickly, making traditional efforts that define and build toward three-to-five-year target architectural states both risky and inefficient. Data and technology leaders will benefit most from instituting practices that allow them to rapidly evaluate and deploy new techniques to adapt quickly. Four practices are vital in this scenario:
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Apply a Test-and-Learn Mindset
Applying this technique builds architecture and experiments with different components and concepts. Agile practices have long been used in application development and have recently made their way into the data space. Now leaders can start with smaller budgets to create minimum viable products, or string together existing open-source tools to create an interim product.
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Establishing Data Tribes
Establishing data “tribes” refers to teams of data stewards, data engineers, and data modelers collaborating to build the data architecture from start to finish. These tribes work together to establish standard, repeatable data, and feature-engineering processes to support the creation of highly curated data sets that are ready for modeling. These agile data practices can help new data services reach the market faster.
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Enhanced DevOps
Invest in DataOps, which can aid in the faster design, development, and deployment of new components into the data architecture. This allows teams to quickly implement and frequently update solutions based on feedback.
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Promote Data Culture
Create a data culture in which employees are eager to try out new data services in their roles. One critical tool for accomplishing this is ensuring that data strategy is linked to business goals and reflected in C-suite messages to the organization.
Summary
With the increasing size and complexity of information system implementations, it is necessary to use some architecture for defining and controlling the interfaces and the integration of all system components. If institutions want to stay ahead of the curve, they will want to consider aligning with EA teams to scale their businesses to the next level.
