Good informants help beat cops find crime—sometimes before it happens. On the corporate real estate beat, data analytics tools act like cops sniffing out inefficiencies before they can impact the business. But they have another, more profitable role: uncovering business productivity opportunities. It’s all about having the right informants—and for today’s corporate real estate cop, your informants can be anything from building equipment sensors to portfolio dashboards.
Corporate occupiers are now using sophisticated statistics and data analytics to fight inefficiency and find opportunity. But there is more to be done.
“Informants” are more plentiful and resourceful than ever, with our ever-expanding volume of structured and unstructured data, some generated internally, some gathered from external sources that even include Twitter and Facebook. As depicted in JLL research, data and analytics are on the frontlines for “aha!” moments—spotting building equipment approaching malfunction, offices that are underutilized, buildings with above-average energy consumption and more.
Analytics reveal both hidden operational weaknesses and opportunities to add value, fighting inefficiency while improving productivity. Here’s how:
By day: The inefficiency cop using data as informant
Predictive analytics tools enable corporate real estate and facility management analysts to process hundreds of millions of data points and pinpoint efficiencies across their corporate real estate portfolios, from power usage to capital spending. Google, for example, used analytics models to map five years’ worth of energy demands and load patterns in its global data center servers, enabling it to predict power usage with 99.6 percent accuracy—and ultimately detect areas where energy consumption could be slashed.
Wireless sensors can generate millions of data points from automated building systems across a global portfolio of facilities, and human analysts can use this data to optimize system and facility performance. Predictive analytics can be used to forecast asset failures and create risk-adjusted models, allowing managers to replace aging equipment before its fails. Benefits can be vast, including reduced operations downtime, more efficient building performance, environmental sustainability improvements and lower operating costs.
By night: The scout using analytics to reveal productivity opportunities
Those at the leading edge of data-centric corporate real estate are going deep into their data, leveraging multiple layers of information and analyses to identify strategic opportunities in portfolio and location strategy. Some are tapping the retailer playbook for data-driven site selection strategies, integrating data sets such as commuting times, availability of amenities, proximity to transportation and other employee satisfaction factors into site selection algorithms. Armed with these insights, a corporate occupier could determine how particular sites would affect talent recruitment and retention, innovation success and other key factors. These talent attraction and retention factors can be as critical to business performance as real estate costs, taxes and local regulations, particularly in talent-driven information economy industries such as technology and life sciences.
Companies adopting today’s new innovative workplace strategies can use data and analysis to support these strategies and optimize outcomes. Rather than relying on the outdated measures of cost-per-square-foot or benchmarking data as indicators of success, corporate real estate teams are creating analyses incorporating myriad data streams, correlating new workplace initiatives with employee and business productivity.
Moving ahead on both fronts
We are just beginning to understand how analytics can unlock opportunities for corporate real estate to boost business productivity. However, some companies are better positioned than others to gain competitive advantage from data-centric corporate real estate management. Assuming a leading position requires training or recruiting data analytics experts and investing in the data-gathering and analytics technologies required to transform data into actionable insights.
Data analytics is enabling new business models; encouraging data sharing across silos for collective benefits; promoting increased partnership across support functions and with the core business; and pushing the limits of technology. For a solid foundation, start with the most high-impact questions and data sets, identifying the most appropriate analytics techniques to address them and building the technical and organizational capabilities required to support the process.
David W. Kollmorgen is international director, business intelligence, with JLL.