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In the race towards digital transformation, many companies are pursuing tech investments touting promises of capabilities and business outcomes that don’t actually map to their organizational needs. As a result, those investments quickly become a loss as employees abandon them in pursuit of other solutions they expect to be more influential — faulting the technology itself rather than the implementation of it.
To avoid making investments that don’t yield organizational value (or ones whose complications and complexities outweigh the value they do offer), organizations need to take an informed approach, which they can achieve through enterprise architecture (EA). As the process of evaluating an organization’s business and IT capabilities in order to identify how they can then be improved to achieve defined business goals, EA is, truly by definition, a fitting approach to sidestepping common digital transformation dilemmas.
However, EA in and of itself isn’t a solution for identifying business shortcomings and increasing operational efficiencies. Rather, just like other digital transformation efforts, EA programs need to be launched thoughtfully in order to unlock their full potential. Gartner recently shared that many organizations are restarting their EA initiatives due to leadership losing sight of how to move their programs forward within their unique business models.
For the change they enact to be meaningful, business leaders need to take a holistic, data-forward approach. Here’s how organizations can establish an EA program that maps to their digital transformation goals in order to unlock enduring opportunity.
Start with a Holistic Survey of the Organization’s Needs and Resources
Smart business decisions aren’t made in a vacuum. Rather, they account for potential ripple effects once they’re put into action so that business leaders can more accurately predict whether those decisions will be worthwhile. Therefore, business leaders looking to transform digitally should start by capturing an overview of their business model, from people, processes, and products to data and apps. By looking holistically at an organization, companies gain perspective on which areas of the business should be their priority for improving, as well as better understand potential risks that can arise from their decisions.
This isn’t to say that executives need to devote all their time to secure a complete understanding of their assets. While a common misconception surrounding EA is that it’s a cumbersome undertaking, the reality is, when deployed pragmatically, organizations can quickly reap value from it. Business leaders need only to dedicate enough time for the project at hand to not be executed in a vacuum so that immediate risk can be mitigated.
Gauging the impact of one investment across multiple levels of an organization may still sound like a large endeavor to some, but that’s where enterprise architects can support. Working with employees, they can generate predictive models based on a company’s data that illustrate the likely implications of when business variables are altered and how those variables can contribute to (or detract from) defined outcomes. These maps help leaders clearly see the interdependencies of their organization instead of juggling guesses in their heads. With the ability to show executives which course of action will be the most productive before they embark on it, these models save organizations time and resources from pursuing dead-end initiatives.
Identify Areas for Quick Returns
In order to add value to an organization, digital investments should increase efficiencies across existing operations, not add on processes for employees to tend to on top of their usual responsibilities. With this criterion in mind, ripe candidates for digitization will be those that are highly manual and costly and would save workforces both time and resources were they to be automated. However, improvements may be as understated as finding new ways to utilize skilled employees or systems leaders had previously overlooked; with a holistic approach that assesses the assets already at executives’ disposal, they may see areas to transform already in front of them.
Having an encapsulating list enables business leaders to be as strategic as possible when identifying areas to transform. With the guidance of EAs, executives can assess how their technologies’ capabilities relate to business outputs and subsequently make judgments on which solutions will yield the greatest organizational impact. For example, whereas business leaders may feel like adopting a new trending technology will enable them to be more cost-effective, they may realize that the complexity in doing so outweighs the benefit, and they should instead consider enhancing a technology they already own. Then, once these quick returns are secured, architects can help business leaders scale up their programs to be increasingly complex and execute more strategic, nuanced responsibilities.
Be Strategic with Data Collection and Usage
To bolster the breadth and depth of organizational data architects have to work with — and thereby strengthen the accuracy of their predictive models — business leaders need to view EA as an organization-wide endeavor. Instead of establishing an ivory tower of specialists who understand how to engage with the program, executives should extend access to the program to employees across departments and seniority, creating a distributed system of contribution. The more workflows architects have insights into, the better leaders can predict the implications of their tech investments. Additionally, continuous employee input ensures that the data EA models are conceptualized from are always up to date and representative.
Once data is collected, organizations can also be strategic in how it’s maintained. Just like the digital investments they support, EA programs have the potential to evolve over time — and they should. Just because a data set may have been gathered to support a specific project doesn’t mean that that data is useless upon completion. Savvy business leaders will recognize that organizational data is reusable and cumulative, and with every digital transformation project, teams can get closer to achieving a complete data set for the company. For example, whereas it would be time-consuming for executives and architects to capture nearly all of their organization’s data for the first project, they can start with a fraction of that data — using what’s relevant to the project at hand — and keep building on it over time. Then, instead of recollecting data for every project that arises, teams can instead approach past data with a scoped perspective.
Armed with detailed insights into their variety of technologies and how employees interact with them at scale, organizations can become more agile in their digital transformation efforts. Whether business readers are looking to transform their technology reactionarily to market events or proactively to get ahead, with EA, they can assess courses of action before investing in any, effectively managing risks, conserving resources, and getting more in tune with their organizations in the process.