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Next Generation Workplaces Using Predictive Analytics

As the data revolution transforms business, predictive analysis rises as one of the next generation methods for improving real estate and workplace services.
Image © IA Interior Architects.
Image © IA Interior Architects.

Big data, data analytics, data science: Call it what you’d like because, regardless, it’s changing the game of decision-making. We can no longer rely on established services or products to serve our clients’ needs. Instead, we must continually leverage methodologies, tools, and skills traditionally used outside of the corporate real estate (CRE) industry. Predictive analytics is an example of this and it will be one of the next great disruptors for managers of the workplace—real estate executives, workplace strategists, designers, facility managers, and organizational designers alike.

WHAT IS PREDICTIVE ANALYTICS?

Predictive analytics is best understood by considering where it falls within the business analytics spectrum. Business analytics typically involves a three-step process.

  1. gather data
  2. process the data into information, and
  3. translate the information into actionable insight.

The second step of processing data can involve two different types of analytics: descriptive and predictive. Often times both are used together, but descriptive analytics has been much more prevalent to-date. Descriptive analytics reports on the past. It uses statistical analysis to categorize past information, or data, and creates outputs such as reports, dashboards, and scorecards to communicate the discovered intelligence.

Predictive analytics provides insight into what the future will likely hold. It uses past data and algorithms to predict a target, embodying a proactive—versus reactive—approach to problem-solving. Put simply, descriptive analytics is hindsight of the past and predictive analytics is insight into the future. James Taylor, a leading expert in decision management, puts it in another light: “Predictive analytics turns uncertainty about the future into usable probability.”

PREDICTIVE ANALYTICS IN CORPORATE REAL ESTATE

In recent years, data and analytics have altered CRE services, and ultimately the space clients move into. Demands for faster and better-informed decisions, relentless growth and complex data, and technological advances at lighting speed converge to increase pressure for data-informed approaches. Descriptive analytics is customary to real estate and workplace design services, whereas predictive analytics is just beginning to appear in the toolboxes of CRE professionals.

According to TDWI research, predictive analytics is used to identify trends, understand customers, improve business performance, drive strategic decision-making, and predict behavior. Leaders like Colliers International are using prediction techniques to provide market insight, NIA Commercial Partners is hiring data scientists to identify future trends, and Google’s People Operations department is using social algorithms to predict behavior. It seems predictive analysis is here to stay.

“Clients don’t want just reflective data, they want proactive data,” says Monica Parker, founder of HATCH Analytics, a workplace consultancy using predictive analytics tools for workplace clients. “Despite its best intentions, traditional ‘workplace strategy’ tends to be a lot less about strategy and more about tactics. Predictive analytics helps support more strategic decision making.”

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KEEP CALM AND SEE YOU IN LONDON

With predictive analytics at its tipping point in CRE, IA has assembled a panel of industry experts with various backgrounds to discuss further the climate for predictive analysis, who else is leveraging it, and why it is important to model workplace behaviors and real estate markets. The panel session will be held at CoreNet Global’s EMEA Summit in London on September 18. IA’s Brian Szpakowski and Kelly Funk will join Derrick Bock, head of workplace design at eBay Inc., and HATCH’s Monica Parker to inform CRE professionals about the world of predictive analytics and what is yet to come.

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