Workforce and workplace data is as critical to successful facilities management (FM) as wrenches and screwdrivers are to successful vehicle maintenance.
And just as the most expensive, high-quality wrenches and screwdrivers are pretty much useless in the hands of a mechanic who doesn’t know how to use them, the most comprehensive, accurate workforce and workplace data doesn’t mean much to the workplace leader who doesn’t fully understand how to analyze it and make it actionable.
That’s why innovative workplace leaders use predictive analytics. They know the power of the approach and how much of an impact it can make on an enterprise when employed correctly.
Read on to learn the basics of predictive analytics and why modern workplace leaders use it in facilities management.
Defining Predictive Analytics (aka Predictive Intelligence)
Before we can define predictive analytics, we must first discuss descriptive analytics as it is the foundation upon which prescriptive analytics is built.
Descriptive analytics is the act of collecting historical information via business intelligence and data mining with the goal of answering the question, “What has happened?” This technique provides workplace leaders with insight into various data points, including event frequency, operational costs and causes of equipment failures, which they can use to guide their short-term and long-term decisions.
With predictive analytics, workplace leaders leverage the data acquired during the descriptive analytics process to hypothesize possible scenarios and develop plans of action. Whereas descriptive analytics is reactive, predictive analytics is a proactive process in which facilities leaders use algorithms, machine learning and modeling to…
- Identify potential risks and opportunities
- Predict potential infrastructure or asset failures
- Forecast future operational needs, including spatial demands
- Test hypotheses
- Validate assumptions
- Make more informed decisions
It’s important to keep in mind that predictive analytics does not provide recommended actions for workplace leaders. Rather, it offers the FM team additional context and insight which they can use when evaluating the next steps in the facilities optimization process.
The Benefits of Predictive Analytics
Predictive analytics empowers workplace leaders to determine the best course of action for their enterprise and can be applied to various types of decisions with an organization — from day-to-day operations to long-term business actions. Here are a few examples of the benefits of using predictive analytics:
- Enable facilities leaders to focus on fixing smaller problems. While the resolution of major issues which arise periodically can undoubtedly improve operations, predictive analytics helps workplace leaders focus on the smaller decisions that are made repeatedly throughout the day, month or year. Addressing these issues may yield smaller gains, but due to their high frequency, their total impact over time can be substantial.
- Help workplace leaders get rid of the unknown. A lack of confidence in their decisions and doubts about the efficacy of the intended results can prevent workplace leaders from following through on their plans. However, predictive analytics allow facilities leaders to make decisions based on insight, not hindsight, thus helping to reduce uncertainty. Workplace leaders are empowered to make swift, confident decisions and take action faster.
- Improve operations. Predictive analytics provides facilities leaders visibility into both granular aspects of the enterprise’s operations as well as insight into the big picture. Using these datasets in tandem, workplace leaders can identify and reduce inefficiencies, increase profitability and boost productivity across the organization. For example, predictive analytics allows facilities leaders to see if building assets such as the lighting system or HVAC units are in use during times of zero occupancy.
- Helps facilities leaders avoid unexpected asset failure. With predictive analytics, workplace leaders can develop benchmarks to compare device performance and create alerts to inform them when equipment is not performing as anticipated and is likely in need of immediate maintenance. This helps the organization save money by preventing abrupt failure of assets.
- Empowers workplace leaders to utilize space and assets more effectively. Leveraging the historical data acquired during the descriptive analytics process, workplace leaders can use predictive analytics to identify traffic patterns as well as asset utilization in each area of the facility. With these insights, they can determine how to ensure space and assets are utilized as efficiently as possible. This could mean consolidating under-utilized areas, upgrading existing equipment, changing building layouts, updating inventory levels, removing unused assets or redesigning work areas.
- Boost employee morale and decrease turnover. Predictive analytics enables facilities leaders to recognize which employees have become less engaged over time, as well as which have demonstrated behavior which indicates they may be considering leaving. By identifying flight risks, organizations can develop intervention strategies to improve employee morale and increase workforce retention.
As you can see, using predictive analytics can have a positive impact across the entire enterprise. While data analytics can be challenging (particularly in facilities management where there is a high volume of data), predictive analytics ensure workplace leaders are making the most of the available data and continuously improving operations.
For even more ways to increase the efficiency of your organization, check out our free SlideShare, 11 Ways Enterprises Leak Money, and see how to avoid common profitability pitfalls.