Every organization has data. Enterprise architecture requires gathering, storing, and sharing large amounts of data. When data repositories are cleanly managed and easily accessible, they provide valuable information to guide an organization.
Enterprise architects know a lot about managing data, but they may not always know the best ways to share data with decision makers who need them. They may speak in highly technical or arcane ways.
When those decision makers cannot easily draw meaningful conclusions from their data, they miss opportunities to leverage their enterprise architecture to make better decisions. This makes it challenging to justify allocating significant resources to enterprise architecture programs.
Costs of Poor Sharing of Enterprise Architecture Data
In many organizations, when someone needs data from the enterprise architecture, they request it either through e-mail or in person. A member of the enterprise architecture team takes time to generate a one-time report that will immediately be out-of-date. Pulling reports is not only time consuming for highly-specialized employees, it is a barrier to providing timely information.
Building a Bridge between Enterprise Architects and Decision Makers
One way to connect these two worlds is through data visualization. New tools streamline efforts to share data,
but it is not as simple as plugging data into a tool. Data visualization experts analyze business requirements and decide on the most effective way to represent data before choosing the right tool for the job. Some decision makers like to explore data in-depth, some like a clean summary. Designing data visualization that serves both types of thinkers requires tools that are both flexible and simple.
When an enterprise architecture team wants to make a case for a data visualization investment, it should consider how much time is spent pulling reports. Many of these teams already have ticket systems, such as JIRA, so calculating costs may be a simple process.
Another way to get buy-in is to show how data visualization can provide insight or guidance into addressing a business problem. The complexity of the problem determines the visualization:
- How does our budget support our strategic goals and objectives? Simple bar, line, or pie charts.
- When I make a change to data in one application, how does that impact other applications? More complex and interactive visualization methods, such as interactive chord diagrams and force-directed graphs.