March 9, 2016 by Dr. Jian Huang

More than ever before, architecture and design firms are hungry for client-centric data to gain a better understanding about a client’s needs and priorities. Firms that have a competitive edge are those that can demonstrate the capacity to better collect, decipher and validate a client’s complex project requirements.

As with all transformative changes, there is often resistance to employing new tools or processes. Feedback collection and analysis in the field of design isn’t immune to this barrier, but A+D firms are becoming more aware of the positive results when using concrete data to help their clients define and appreciate the business case behind their workplace design decisions. The pace of this shift in the A+D industry is accelerating month over month.

It is indeed a tricky process to determine what a client and their employees really need or what they prioritize in their workplace, particularly when a client has a large number of employees with varying ages, responsibilities and tasks. Traditional surveys are often employed in this scenario but are problematic due to their lengthy, fatiguing experience which causes users to carelessly respond. In the end, how can you trust that kind data?

A feedback platform like Survature is in a whole new class of online survey tools that has been developed to address these issues. Survature’s AnswerCloud question collects responses from survey participants while assessing their behavior—which responses are chosen first, changed, or even ignored. In essence, it listens and records what participants said AND how they said it. By capturing and analyzing respondent behavior, Survature can determine the workplace parameters that matter most to employees in a much shorter amount of time while capturing 9 times the data insight compared to traditional online feedback tools.

The picture above shows Survature’s AnswerCloud question which allows for the use of “draggable” images as responses. This example shows how an interior design firm captured feedback after their client and employees demoed various office seating options.

The Survature team also discovered that not everyone has the resources or time to hire data analysts to interpret and present the insights found when collecting feedback data. The Survature platform was built to do this analysis automatically, in real-time, as feedback is captured. The results dashboard delivers this real-time analysis in interactive sharable visual analytics, as well as downloadable charts and graphs that can be used in presentations.

The hallmark of Survature’s results is the priority matrix (pictured above)—a powerful, two-dimensional view of both a question’s response ratings and their relative priority. This unique data view makes it easy to pinpoint what matters most among similarly rated items, or crucial differences between targeted segments of the responders. The results above reveal the stark difference in the impression and priority of a particular office chair between departments. This is unique, easy to interpret visual insight that isn’t available with traditional platforms.

Architects, designers and human resource directors have had great success when using the Survature feedback platform to engage employees on how the workplace can best support their wellness and productivity. Revealing both the ratings for pertinent workplace issues and their priority offers clear evidence that cuts through debate about where to focus attention to insure a successful solution to a design project.

Check out Survature’s field tested template library of workplace assessment surveys that are easy to set up and get running “as is” or can be edited or modified to better fit the particular needs of any organization. Using these can really set the stage for a design strategy that minimizes inefficiencies while maximizing the appeal of the workspace.

Jian Huang is the Chief Executive Officer at Survature providing the vision for reinventing the way the world experiences surveys. He is a professor of computer science at the University of Tennessee (UT) researching data analysis, visualization, and human-computer interaction. His research has received funding from the National Science Foundation, the US Department of Energy, the US Department of Interior, Intel, NASA, and UT-Battelle. Jian received his PhD from the Ohio State University.