As companies work to adapt to a fast-changing business environment and increasingly complex technology landscape, leaders are taking a closer look at their enterprise architecture strategy to ensure their IT portfolio supports strategic business objectives. Done well, a strong enterprise architecture provides the foundation that enables companies to be more agile, scale new innovations quickly and securely, and ultimately deliver greater value to customers.
Creating a solid enterprise architecture strategy can help take product development organizations to the next level by providing the technological runway they need to create seamless customer experiences and respond quickly to market needs. Inside many organizations, however, we often find that enterprise architecture has not reached the level of maturity needed to deliver on those promises. Often, employees rely on patches and workarounds to get data from one system to another, time that could be spent working on product and system enhancements. In other cases, existing technology architectures no longer align with strategic business objectives. One of the main problems stemming from this lack of alignment is that it limits the capacity to create efficiencies and synergies that support business goals. It can also hamper business agility by making it more difficult to create and share relevant data and insights across the organization.
To overcome these challenges, firms need an enterprise architecture strategy that can adapt to changing market demands. That requires making EA an ongoing and evolving part of any digital transformation initiative.
At its core, enterprise architecture refers to the configuration of IT resources in service of an organization’s business strategy. It creates alignment among a company’s strategic goals, its existing business processes, the data and information created, and the underlying infrastructure that supports it. It forms a blueprint of sorts, noting not only what technology the company currently has, but also how future technology investments will fit into or change what currently exists.
There are four main components of the EA:
We will explore each of these later in the article. These components cascade down from one another, each serving a different purpose (see image).
Having a clear EA does not magically solve business operations issues, nor does it enable a company to generate insights with a single tool. What it does is create vertical alignment of the business and functional objectives, foster collaboration between functions, and help create synergies based on data.
For many companies, the Enterprise Architecture is an afterthought, something only relevant to the architect who needs to give his or her sign-off during product feasibility meetings. But as mentioned above, the EA needs a seat at the table throughout the process to share guidelines and strategies with product development and IT teams that enable key growth levers. Among the reasons a clear EA is essential:
There are four key components of any enterprise architecture strategy:
The first step in creating an enterprise architecture strategy is understanding the overall business outcomes an organization wants to achieve. The Objectives, Goals, Tactics & Metrics (OGTM) framework provides a useful framework for aligning business goals to the mission and vision of the organization, then tying those goals to specific operational tactics. You can read more about the OGTM framework here.
Once there is clarity about the organization’s path and desired outcomes, it is important to partner with business functions to help each understand their role in the company’s strategy. Conversations with functional leaders should focus on objectives, roadmaps and blockers, the functional leader’s needs, and which technologies support and enable their goals.
Discussions with functional leaders should also include how they use data to influence their processes and decisions. This creates a bridge between business strategy and data strategy and leads to understanding about how data will flow across and within the organization. In the age of artificial intelligence, it is important to discuss and set a direction for the use of tools and structures that enable the use of algorithms, automation, machine learning and eventually AI.
With an understanding of the overall strategy and functional objectives, as well as the data needed to execute business processes, technology leaders can determine the tools and applications that will best help the organization achieve its goals.
These tools may be internal, such as an employee lifecycle management tool. At the center may be an application that includes an employee’s personal information and is connected to recruitment and onboarding tools. That data may also connect to a learning management system (LMS) to track training and employee growth paths. Connecting all of these applications can, for example, allow HR team can generate valuable insights used by the management teams.
Applications may also be external, directly related to customer-facing products or digital channels. Say a financial services firm sells an application to help bank branches process customer transactions. If the firm also offers related products, such as mobile or web banking or fraud detection products, it is important that the different products work seamlessly and appear as a single system to the end user. A single application architecture can help influence requirements for user experience, product development, and operations teams.
When creating an application architecture, it is also important to understand the role that Application Programming Interfaces, or APIs, play within the business. APIs are the building blocks that ensure all systems can communicate and share data effectively. This is one of the most important, yet often overlooked, aspects of the product development process that needs to be addressed by your EA strategy.
Organizations first should assess whether the company has all of the technological components necessary to support the business tools and applications. This includes hardware and software that will enable these tools to be deployed, such as on-premise servers or cloud storage, networking, and security. When thinking through technology architecture, it is critical to consider how infrastructure will affect the organization’s agility and ability to grow.
There are different risks and challenges associated with the creation of an enterprise architecture strategy. Due to how quickly technology changes, it is very easy for systems, applications, and even entire methodologies to become obsolete in a short period of time. Combined with an inclination to go after the latest trend, it is particularly easy for the EA model to become outdated or to have changed by the time a standard version is in place. In this scenario, enterprise architects constantly play catch up and the strategy fails to deliver its real value.
Similarly, business teams may perceive architects as people sitting in an ivory tower, not tied to the reality developers face. As a result, developers may not see the value in creating documentation. Technology leaders, then, must constantly communicate the strategic importance of enterprise architecture in achieving both short-term and long-term business goals, and drive operational accountability for documentation across the organization.
With a clear understanding of the business objectives, as well as the data, applications, and infrastructure that will help a company achieve its goals, technology leaders can create a roadmap for transforming the organization. That includes thinking through which frameworks and tools may be used to implement the new enterprise architecture. There are a number of EA management tools in the market that you can use to map all business capabilities to the strategy, as well as to the logical and physical infrastructure. Depending on an organization’s maturity, leaders may also opt to have more informal plans and architecture mapping, but it’s worth noting that this may inhibit the speed and effectiveness of implementation.
At the same time, it is important to frame EA as a light tool rather than an onerous process that only delivers documentation. When creating or improving an enterprise architecture, leaders should think through how EA teams will continue to add value by enabling new product development and creating new opportunities for innovation at scale.
Creating a comprehensive EA strategy is not a linear process, and it takes time and many conversations to go from an idea to full execution. The journey does not stop once the EA has been implemented, but rather is an iterative process that will change and mature over time as technology evolves and priorities shift.
This article was co-written with Chris Davis.
Summary: People, not technology, are the true center of any digital transformation initiative. The half-life of skills is rapidly shortening, necessitating a mindset that embraces change, an adaptable skill set, and a workforce plan that ensures an organization has the talent necessary to operate at speed and scale through hiring, automating, upskilling, and sourcing.
Putting talent at the center of digital transformation
The biggest challenge of any digital transformation is not revamping technology, but rather shifting the company’s mindset to embrace new ways of working. Just like you can lead a horse to water, but you cannot make it drink, little can be achieved by making the latest tools available to an organization that is anchored to traditional processes.
Transformation efforts should have people at their core, and leaders must be intentional about inspiring, listening, and investing in change management to bring everyone along on the journey. We find that organizations typically under-communicate by a factor of 5X, don’t clearly articulate a pathway for current employees to help be a part of the future, and take an imbalanced approach to closing skill gaps.
With that in mind, there are three steps to developing an effective talent strategy for transformation:
While not an exhaustive list of activities to drive a transformation, executives that do not prioritize the people component of change management will inevitably fail.
Start with why and communicate relentlessly
People do not change their beliefs, values, and attitudes without good reason. They are especially unlikely do so when the norms, practices, and measures of success are inherited from a company legacy that has historically been successful. Success forgives a lot of sins, and even when there is a collective recognition of a need to change, it feels safer to endure the predictable way of working rather than venture into the unknown. This is why author Simon Sinek, whose TED talk amassed 48 million views, encourages leaders to “start with why.” In practice, that means explaining why the team is undergoing the change, what the expected impact and outcome will be, and how the firm and its people will benefit as a result of the transformation.
Communication must be personal. We regularly find that a senior leadership team will spend roughly 50 hours agreeing on a transformation plan, but an individual contribute receives less than ten hours of cumulative explanation. As those individual contributors are most directly affected by the change, this ratio is dramatically disproportionate. In this scenario, by the time the message reaches individual contributors the rationale for change is unclear, which can prompt fear and resistance. Develop a communication plan that segments personas by seniority, functional domain, and project/product team. Establish a communication campaign cadence per persona that specifies varying levels of detail tailored to the channel of communication (group meetings, training workshops, webcasts, 1:1s, etc.)
To catalyze the change, focus on creating a compelling vision for the future and explain how the leadership team will work with individuals to ensure a smooth transition. Communication is bi-directional, so ensure there is an active feedback loop. Workshop role-specific examples of new work patterns. Even if people raise concerns, it is more valuable to identify active resistance and change “detractors” early on than to succumb to passive resistance that erodes momentum. However, to create an environment of trust, it is critical not to shame anyone that has a concern into submission. Be judicious about delineating whether a voiced concern is someone being obstructionist or whether it is sign that the leadership team is not being effective in its communication.
In addition to the qualitative feedback loop, it is important to define and track outcome-oriented metrics that drive desired behaviors. Monthly dashboards at different levels of the organization can help transformation teams promote a successful, sustainable digital transformation. Done well, they can highlight areas where the right talent and skills are missing, monitor the achievement of key transformation change management milestones, and gauge the sentiment of the team. The metrics should serve as a compass to enable leaders to make data-driven decisions on how to steer the transformation when waters get choppy.
Assess your skills, knowledge, and traits and identify gaps compared to future state needs
Digital transformation will require people across your company to learn new skills and adapt to new ways of working. These skills typically fall into one of three buckets:
First, functional leaders should partner with HR to conduct a skills assessment and identify gaps between existing and needed skills. When speaking with employees, it is critical to communicate that this is not a performance evaluation. Otherwise, you may run the risk of employees overselling their abilities and skewing the results of the assessment. Instead, think of this as a way to identify and prioritize where the organization will dedicate its training and development resources. Explain how the newly acquired skills will advance one’s career and personal brand so that there is motivation to be vulnerable rather than self-aggrandizing.
Identify the people whose work creates the benchmark for the skills, knowledge, and traits your transformation needs, and deputize those high-performing and high-potential individuals as change agents for new skill adoption. Some practical skills to measure include consultative and technical skills, product and project management, and self-development and adaptability traits.
Next, develop a plan to close existing skills gaps and align it with the firm’s overall goals. Create training plans, with clear goals by level and function, and turn this into a digital transformation workstream like those used to manage other process or organizational changes. Set realistic timelines for skills adoption so employees are not paralyzed by the enormity of the change. One large financial services company set a bold vision to move its entire infrastructure to the cloud but was clear with employees that it would do so over five years and offered an internal “university” to certify people in new technologies like AWS S3. As a leader, you cannot just tell people to improve. You need to show them how to improve and invest in their development.
Define a balanced workforce plan around hiring, automating, upskilling, and sourcing
As companies define and identify skill gaps, they also need to develop a strategic staffing strategy that will help them achieve their transformation goals through the HAUS model:
The HAUS model allows leaders to decide how to fulfill their talent needs across core, value-added and transactional activities. For example, a company may decide to hire its head of DevOps, automate its software delivery value chain through CI/CD, upskill its current developers to learn to use the new tools, and in the interim source talent that can “teach to fish” while implementing the first wave of the new approach.
Another example can be drawn from the first wave of mobile app development. In 2010, iOS development was a fairly rare skill, so any major non-tech company developing its own mobile app was likely hiring an agency. Fast forward a decade, and you’ll find that most companies with major mobile-powered commercial operations will have in-sourced that skill set to have more control over their own destiny. The next wave of skills following this pattern is artificial intelligence and machine learning; most companies are outsourcing this skill set now but will likely have more internal talent in 2030. In this way, the HAUS model becomes a living, adaptable framework, instead of a one-time solution.
People and behaviors lead digital processes and tools, not the other way around. Putting people at the heart of the transformation while tracking results and behaviors is key to ensuring a successful and sustainable talent strategy. Your talent strategy must be managed as an equally weighted workstream within the overall transformation portfolio in order to ensure that the company’s most important assets are not overlooked. Finally, be humble. No transformation is perfectly planned, so be prepared to communicate, listen, and transform yourself first, if you want others to follow you.