Jul 22, 2019 in Viewpoint
3 things facility managers need to know about data and machine learning
The role of facility managers has changed. You must collect data and do something with it. Taking a glance around the office to see how your building and employees work together just isn’t enough anymore. Data can tell you a different story. Using insights to redesign your office efficiently and applying machine learning to personalize the office to the needs of employees will give everyone a great day at work.
Combining it all together
The first step to collecting data is to collect data. You can do this by equipping your office with sensors in meeting rooms and workplaces. The data these sensors collect allow you to know if a room or workplace is occupied at a specific moment, but also gives an overview of a day, week or month. But there is so much more! Let’s dive into 3 things data and machine learning can help you with.
Alan Turing, 1947
What we want is a machine that can learn from experience.
Data can tell you at what time there are the most no-shows, machine learning can predict what meetings will turn out in one
You may find that meeting rooms are often empty, but the schedule says they are fully booked. Data can show you that there might be a lot of no-shows in the early morning. As a facility manager, you can choose to, for example, cancel all bookings if the meeting room is unoccupied fifteen minutes into the booking. This gives employees the chance to choose for ad hoc meetings. But machine learning can take it to the next level. Machine learning can point out which scheduled meetings are high potential no-shows. If needed, a facility manager can decide to appoint these meeting rooms to someone else.
Data can let you know which floor is popular, machine learning can show you why
In large office spaces, data can easily show you which floors are popular, in for example heatmaps. But why this floor is so popular? Insights from a machine learning model can point out which elements of a floor are appreciated by employees, so that these elements can be realized at other – less occupied – floors. Result: employees are more evenly distributed over the building and experience less bustle.
Data can help your employees find available workplaces, machine learning can recommend which available workplace fits best
Transitioning to activity-based working can be hard. Employees have to share everything and no longer have fixed desks. To make sure your employees don’t wonder the hallways for a free workplace, data can easily help employees find an available desk. Machine learning can improve employees’ experiences even more. By recommending workplaces they appreciated in the past, considering colleagues they prefer to sit next to and matching their activities of that specific day, the perfect workplace can be found within seconds.
While machine learning is a very useful tool, collaboration is the key to successful data collection and analysis. As a company, you have to create partnerships with companies willing to work together. Mapiq uses collaborative data analysis to help create a productive workday. We do this with integrations like PointGrab, Vecos, and Microsoft. We make one cloud-based office platform that helps you manage your office.
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Viewpoint / Aug 22, 2019 / Marc van de Wert
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