The Marketing Technologies Transforming Commercial Brokerage | ACCESS THE REPORT→
ESI Design Inc. - Design
ESI Design Inc. - Design

The Underlying Paths That Lead to Successful Data Architecture

Last updated:

Have you ever watched an ant colony being built? Yeah, neither have I. One day, you’re walking in your backyard, and small mounds of dirt seem to have magically appeared. But really, there’s nothing magic about it—those mounds of dirt equate to thousands of ants diligently working countless hours to create vast networks made of intricate structures. Every ant has a role in the system and is supported by the rest of the ants to do it. The infrastructure needed to support this amazing amount of choreographed work is incredible and was designed with every member of the colony in mind. 

From an outside perspective, this is how an efficient data architecture system may appear. New protocols, efficacious systems, and useful analytics “magically” materialize, making information readily available and easy to use. Good data architecture seamlessly blends in with the rest of an organization’s landscape, barely noticeable except to those who use it regularly and know its paths well. To a new employee, it might seem as though these structures have always existed, but that can’t be true. The technology didn’t always exist. It took many people many hours to figure out the best ways to implement that technology. Creating an efficient data architecture requires a lot of “underground” work being done before the surface even begins to change. For most companies, this process can be challenging. It requires resources and people who know where all of these “underground” paths lead and how to navigate them. 

Many commercial real estate firms have outgrown their capabilities to efficiently process the information they’ve been generating. WashREIT recognized this challenge early and has taken steps to transform their data strategy and capabilities in order to maintain their competitive edge in a rapidly evolving marketplace. WashREIT was founded in 1960 and encompasses multifamily and commercial properties in the Washington D.C. metro area. The company has changed dramatically over the last seven years and continues to do so. Technology has played (and continues to play) a key role in that transformation. 

Susan Lilly Gerock was hired as WashREIT’s Chief Information Officer to ensure the company was making the best use of its current technologies and implementing new ones to support the company’s growth. Part of her role was to oversee the company’s data strategy. Gerock’s goal was to democratize information and make it readily available to those who needed it, when they needed it. She knew this process would require buy-in across the company, and she also valued having the expertise from a fresh set of eyes outside of WashREIT.

WashREIT enlisted help from CohnReznick, a global advisory firm that offers an array of services including information management and analytics. This division specializes in implementing data strategies and enabling seamless transitions in creating data-driven organizational mindsets through managing change. With Gerock’s goal of democratizing data as their guiding force, the team examined WashREIT’s data landscape side by side with CohnReznick’s advisors. They looked at everything—what data were they collecting and what was the source of truth, were they duplicating data, were different teams using different methods for analyzing data, and what questions did they want to easily answer that they could not answer today. Gerock wanted to “create more agility in solving future needs, not just problems of the moment.”  

Through this thorough examination of WashREIT’s current data architecture, they realized their data warehouse was not serving their data needs efficiently. In addition, certain leasing information was being kept in a separate database, making it cumbersome to produce new reports and analysis. Gerock and Cohnreznick’s team also found opportunities for improving the use of their current ERP software, JD Edwards, including the implementation of the JD Edwards Job Cost and Procurement systems to support the company’s Development and Construction cost and project management.

Gerock knew they needed data that was up to the minute and a system that everyone could access easily. WashREIT added a new reporting system as part of the transformation project, eliminating the data warehouse and other auxiliary databases.  Choosing the right tool for interrogating data eliminated the need for complex integrations and a greater understanding throughout the organization of the sources and uses of data.

With so many changes in the company’s processes and systems, a substantial education rollout with significant change management efforts was warranted.  Over 50 people throughout the organization had a say in design and testing. Gerock’s team listened to stakeholders at every level, from the trenches to leadership, to find out what they wanted. She says, “By giving everyone a voice, it allowed us to have everybody speaking the same language and understand where that data originates.”

After the first phase of the data strategy had been implemented, WashREIT entered the flexible office space market. Leaders within the company wanted to measure success and develop innovative strategies for approaching this new line of business. Because of their streamlined reporting system, Gerock says, “We took advantage of all possibilities for tracking data to be able to answer questions quickly and efficiently. Flexible office is a completely different animal than the traditional commercial office business, and we needed that reporting to be able to support this venture.” 

The underlying paths that form the vast networks of data architecture may be painstaking to build (at least, correctly). But once the foundation has been laid, these paths blend seamlessly into the organizational landscape as if they had always been there, creating easy access to valuable data and its many insights. 

As with a colony of ants, or any other sophisticated ecosystem, data architecture is built to support the members of an organization, so that they may thrive and be as productive as possible in their environments. A profitable business is built on top of well-structured data architecture. When you have a complicated business, with many moving parts and teams doing a huge variety of things, it can seem a bit like the frenzy of an ant colony. The most important thing an organization can do is design the systems by which the work gets done, and in today’s business environment, that means taking the time to customize data architecture to support your colony.

Have Another
Sorry, Boss: 72% of Workers Don’t Want to Return to Offices Full-Time