The Leader Magazine

SEP 2016

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60 SEPTEMBER 2016 said it another way: "Everything should be made as simple as possible, but not one bit simpler." Remember, analytics is just a way to discern "meaningful patterns in data." An almost inexhaustible array of patterns can be discerned within CRE data, but the operative word in the definition is "meaningful." Too often organiza- tions have developed extensive lists of metrics and performance indicators that add little or no value in the operations of the corporate portfolio. In fact, these lists have the exact opposite effect. Too many measures are as bad as too few. Recognizing the ideal analytics model for a specific operation is largely dependent on the specific mix of assets and services offered. A gen- eral rule of no more than a dozen core metrics and no more than two strategic key performance indicators (KPIs) is the appropriate mix. The hard part, of course, is discerning the right set of metrics and KPIs to help align portfolio decisions with the overall corporate mission. Remember, raw data have very little value until viewed in context, aggregated and observed in relationship to the value they can add. Principle #3: a nalytics is a way of think- ing, not a substitute for it It is easy to get enamored with the tools but developing a quality analytics capability is hard. Definition of a problem and fundamentally solving the problem will drive the success of the effort. Just think about all the political polls this year – same data set but radically different con- clusions. So, managers should always consider the following. • Work with those who will be affected by your analysis, both upstream and downstream of your immediate team, and determine what is truly important to them. Too often, analytics are deployed because they are clever or interesting to create. One way to mitigate this risk is to always look at data in the context of solving a particular problem. • Don't confuse association with causality. Pat- terns are easy to find in large data sets but it is more difficult to determine what actu- ally caused the pattern. Too often, people jump into running all kinds of analysis on their data simply because they can. • Assess what kind of analytics to run when addressing each problem. Descriptive ana- lytics are great for historical reporting, but predictive analytics are needed to predict what will be needed in the future. These are more difficult since they often require statistical models on past data to predict future performance. As your analytics prowess gets more refined, you might even need to add prescriptive analytics, allow- ing the tool to make recommendations about potential changes to how work is done or how the portfolio is deployed. Conclusion Although big data is not new, its exponential growth within CRE is. Today's challenge involves getting a handle on a workable platform, taking the right steps in assembling a CRE data re- pository, isolating meaningful data patterns, and understanding which opportunities that analytics is actually bringing to the table. Going beyond metrics, which are historical measures about such things as closing work orders, numbers of people moved and space utilization, true analytics will allow trusted data to be used for gaming and modeling. Data suddenly become actionable information for CRE executives to consistently make the best pos- sible decisions in aligning the portfolio with the overall corporate mission. Phil Wales, registered architect, is founder and CEO of Houston-based eBusiness Strategies, LLC, a real estate and workplace management consultancy firm. He holds a B.S., Bachelor of Environ- mental Design, and Master of Architecture from Texas A&M University. F E A T U R E A R T I C L E

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