Data Analytics 101: Descriptive, Predictive and Prescriptive
It’s no understatement to say data is integral to a facilities leader’s role. And though a facilities leader has access to a wealth of data about the workforce and workplace, if he or she doesn’t know how to effectively evaluate this information and build a strategy around it, all of that data is pretty much useless.
Data analytics can be challenging. But in facilities management (FM) where there is sometimes an overwhelming volume of data, it can be especially difficult. The best way to ensure facilities leaders have a comprehensive picture of operations and are taking full advantage of the data at their disposal is by using descriptive, predictive and prescriptive analytics.
Here is a breakdown of each of these types of data analytics.
Descriptive Analytics (Summarizing)
Facilities leaders engage in descriptive analytics every day. This technique is simply a matter of collecting raw data and organizing it into actionable insights. Descriptive analytics answers the question, “What has happened?” and allows facilities leaders to make short-term and long-term operational decisions based on historical data.
Without descriptive analytics, the facilities management team would have an abundance of data but would be unable to create a plan for how to leverage it. However, by using this practice, facilities leaders can objectively see the productivity of the workforce and know which parts of the organization are performing well and which are in need of a little TLC.
Descriptive analytics is also the foundation for predictive analytics.
Predictive Analytics (Forecasting)
With predictive analytics, facilities leaders employ the datasets from the descriptive analytics process to forecast future operational needs and determine the best course of action based on these needs. For example, this may mean redesigning workspaces, upgrading equipment or hiring more personnel.
Predictive analytics also utilizes algorithms, machine learning and modeling to help the FM team see patterns and relationships among different datasets to identify potential risks and opportunities. However, predictive analytics isn’t a Magic 8-Ball—instead, it lets facilities leaders use the data they do have to make more accurate estimates about the data they don’t have.
Prescriptive Analytics (Hypothesizing)
Prescriptive analytics is a more complex form of predictive analytics. It not only is focused on the “what” and the “when” but also the “why.” Using prescriptive analytics, facilities leaders can speculate how future actions of decision-makers will affect the business and make adjustments before those actions are actually taken, increasing the likelihood of success.
Whereas predictive analytics is focused on forecasting one specific outcome, prescriptive analytics helps facilities leaders determine the probability of several different outcomes and the best way to reach the desired outcome. One of the benefits of prescriptive analytics is it can improve efficiency by showing facilities leaders which decisions will lead to reduced waste and better space utilization.
It’s important to remember each approach should not be used independently—they are complementary practices that build on each other to help facilities leaders make the most informed decisions. With descriptive, predictive and prescriptive analytics, the FM team can use objective data to continuously streamline operations and build a more productive workforce.
Workplace technology helps make collecting and assessing data even easier. Check out our free eBook, The Workplace Leader’s Playbook for New Technology, to learn how to choose which workplace technology is best for your organization.