Implementing Data in Practice: A Profit Opportunity

Initial client meetings often set the stage for the remainder of a project. What are the client’s vision, mission, and goals? What do they hope to accomplish with this project? More importantly, how did they develop the initial program that they are not excited about but hope that you, as the design professional, can transform into something amazing? Using data to rationalize such questions gives designers an opportunity to gain additional trust within a client relationship, but implementing data within practice should not be considered a research endeavor. Data in practice is an opportunity to increase services and provide the firm with additional revenue.

What type of client data should I seek?

In my experience at MKThink, our strategy practice typically seeks out three different types of data: building, economic, and client information.

Building data is anything relative to the existing and future site conditions—essentially it is data that can be found in a building environmental management system, feasibility study, or data measured onsite relative to climate, traffic, etcetera. Electric bills and building maintenance records can also be compiled as building data.

Economic data is usually external but relevant to the project and ultimately affects the client’s facility needs. These data sets could include census data as well as market and industry specific data not limited to forecasts and annual industry ranking surveys.

Client data is any data collected by the client on a regular basis that shows overall use of their facilities. This includes schedules, meeting room reservations, security card keys, and point-of-sale information, for example.

I have a lot of data, now what?

One of the easiest—albeit most tedious—tasks is organizing the data in a way in which you can begin to make correlations across data sets. To do this successfully, the data needs to be organized and compiled within the same file or using the same system. For those starting out in the data world, Microsoft Excel is an incredibly useful and powerful tool. At MKThink, we continue to use it at a variety of different scales.

Recently, we used Excel to model the utilization and occupancy of a high school and understand to what extent the addition of professional learning communities would change the required frequency of use and class size for the school’s classroom inventory. Those interested in more savvy applications of data can learn how to develop a database. FileMaker software is easy to learn with many online tutorials. A number of free database tools have their own supportive community of developers.  

Once the data is organized, the second task is to visualize the data to begin making comparisons across data sets. Excel and most database software have an accompanying visualization capability but, in some cases, a third-party data visualization tool is recommended. I tend to use a combination of DataGraph and the free version of Tableau, and finalize graphs in Illustrator for client presentations.

In the process of collecting, organizing, and visualizing data, patterns begin to emerge. In many cases, data provides quantitative support for assumptions designers have made through intuition. For our work on the San Francisco headquarters of the Nature Conservancy, we used security entrance data to show that, on average, a little more than half of the office occupants were present on a daily basis. That data ultimately convinced the leadership team to decide that no individual would have their own designated office space.

Taking on the responsibility to keep and organize a client’s data relative to capital spending and facilities enables the design professional to earn back the role of trusted advisor. Providing these services often comes at a greater upfront cost to the client, but ultimately drives better design in ways that are quantifiable to the client. On an annual basis, the profit margin for strategy projects at MKThink is consistently higher than architecture projects and that, in turn, supports much of the firm’s research endeavors.

Remember that the act of initiating data in and of itself is not a research undertaking—rather, it is an added service that leads to greater revenue potential.

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This article was originally published in Contract Magazine.