NVTC is inviting members and industry leaders to serve as guest bloggers, sharing insights and information on trends or business issues relevant to other members. This week on the NVTC blog, Aaron Trionfi of LMI shares three business-friendly strategies to increase the value of enterprise architecture.
Enterprise architects have long promised significant benefits to their organizations. Using Enterprise Architecture (EA) practices, they can uncover operational and technical redundancies, pinpoint overspending, and identify technology gaps and other risks. Unfortunately, these promises are often unmet. Why? Lack of simplified, business-focused communications between EA teams and executives.
EAs define the business, as well as the information and technology needed to operate the business. Enterprise architects use frameworks to capture current and alternative future states of an organization broken down into related elements, such as business functions, data, and technologies. Too often, these frameworks don’t yield results that decision-makers can use to better understand the risks and opportunities facing their organizations.
As a result, many executives fail to recognize the potential value EA shops can deliver. To unlock this value, decision-makers must clearly communicate the business questions they want their EA shop to try and answer.
Similarly, enterprise architects must learn to speak the language of their stakeholders. Rather than developing EA outputs that only other architects can understand, they must present results in a form that decision-makers can more readily consume.
Implementing three key strategies will facilitate communication between enterprise architects and business leaders, and improve the success rate of EA efforts. To better support organizational-level decision-making, enterprise architects need to
- Create a simple model showing how organizational elements relate,
- Tailor communications for different audiences, and
- Provide business intelligence-based analyses.
1. Create a simple model showing how organizational elements relate
Most EA frameworks include an EA model describing the data elements. Unfortunately, these models routinely are based on a fixed set of EA products that fail to help answer pertinent business questions. Further, because EA data models are often developed using a Unified Modeling Language (UML) class diagram or entity-relationship diagram, enterprise architects struggle to convey to non-architects the importance of the EA data model for answering business questions.
Instead of enterprise architects focusing on a laundry list of EA products, they should develop an organization-specific conceptual EA data model with many of the complicated modeling elements removed. This simplified model describes organizational objects—such as goals, initiatives, projects, and investments—about which an EA program might collect data. Once the model is created, conversations can revolve around how linking the different data areas allows EA shops to answer business questions pertinent to stakeholders. Figure 1 shows a simplified model and how to tailor a discussion of the model around how it can be used to answer a specific business question.
Figure 1: A simplified EA metamodel describing the objects of the organization about which an EA program might collect data. The model clearly illustrates the data needs of the EA program and how the data can be integrated to answer business questions. This organizational-level example helped decision-makers manage strategic information technology (IT) investments.
2. Tailor communications for different audiences
Enterprise architects need to tailor communications to individual stakeholders. For instance, for financial executives, the communications might focus on how linking investment data to systems and applications can help determine how a reduction in specific investments will impact the maintenance of current business systems.
Conversely, for a functional office providing services, the communications could focus on understanding the impact on services if the staff executing a specific business function is reduced. The vocabulary and frameworks used to describe the architectures must have business relevance.
3. Provide business intelligence-based analyses
Senior executives are pressed for time. EA programs often fail to connect with leaders because they cannot effectively summarize information.
The growth of the business intelligence field gives EA programs powerful tools to analyze data and illustrate results in easy-to-understand formats. For example, the heat map in Figure 2 summarizes the number of applications that support specific business functions related to financial management.
Senior executives can quickly see that the red areas have more business applications supporting them and are, therefore, better candidates to examine for IT redundancies. Traditional EA approaches would yield a complex matrix and force the audience to summarize the data themselves. By presenting an audience with targeted business intelligence, the enterprise architect can deliver information that traditional EA formats cannot to audiences enterprise architects typically fail to reach.
Figure 2: A heat map showing financial management business functions—color-coded by the number of applications supporting those functions. Red represents more applications, yellow a moderate level,
and green a lower level.
Although a departure from traditional EA methods, employing these strategies will deliver significant organizational benefits, including:
- Information that is consumable by business leaders and architects alike,
- A simplified and less costly approach to EA
- Less need for personnel with advanced modeling skills, making EA programs easier to staff.
When business leaders and enterprise architects speak the same language, the success rate of EA efforts increases. Enterprise architects can position themselves as enablers of data-driven decision-making, and executives will finally realize the value of their EA investment.
Aaron Trionfi is a staff member of LMI’s Enterprise Architecture team. He has supported U.S. government agency EA programs for roughly 6 years. During that time, he has developed architectures using multiple frameworks and every layer of architecture. Dr. Trionfi earned a Ph.D. in physics from Rice University and uses this foundation to bring a strong analytic approach to EA.