AI Will Eat The Fat Out Of Facilities Management if We Learn How To Feed it Quality Data

There are a lot of moving pieces when it comes to constructing and maintaining the ideal workspace—now so more than ever. People want their offices to function like the Facebook headquarters or the Google spaceship or, dare I say, a WeWork. To do this, offices have to be well designed, flexible and digitally integrated. They need to be comfortable, productive places that learn overtime from the people using them. 

At the same time, managing a building has gotten more demanding. Even the most well-run buildings are feeling pressure from rising energy costs, aggressive sustainability goals and shorter lease terms. A lot of technology has empowered facilities managers but since there are so many systems needed to keep a building functioning, understanding each piece of a very complicated tech stack is crucial. Staying ahead of an increasingly sophisticated competitive field, facilities and property managers will require collecting, tracking and visualizing facilities and employee needs to make smart, quick decisions. Newly accessible advanced computing techniques like machine learning and artificial intelligence can help. They can gather and analyze important data in a way never before possible. But, they can only do so if you can get them the kind of rich, real-time data that they need.

Integrated Workplace Management Systems (or IWMS) are a good first step. They can lighten the burden of feeding data-hungry learning algorithms by recording and monitoring a plethora of vital metrics across a real estate portfolio. IWMSs have been a staple in commercial real estate facility management for some time. But it has been the introduction of more recent advancements in artificial intelligence and machine learning that is allowing us to greatly augment the capabilities of these platforms. It is important to design IWMS systems with the end goal of using them to drive real time data to programs that will help inform decision making.  

Another area that can greatly benefit from AI and ML processes is the initial planning phase of a renovation or new workplace design. Drafting and constructing the floor layout is particularly arduous for our customers at Tango. It takes skilled technicians hours to draft polylines, creating costs and consuming bandwidth. That time can be cut drastically with auto polylining technology. With the aid of machine learning algorithms, software is capable of quickly producing a first draft of fine detail drawings. It’s much faster to alter the computer-generated models than it is to create the entire floor plan from scratch, allowing the technicians to move on to more important tasks. 

Spatial recognition software can also be a big time-saver for the facility managers we work with in the planning phase. Using pattern recognition software, the technology can analyze CAD drawings to classify space and determine usage. This allows managers to quickly visualize how well their space will be utilized to make sure they’re getting the most out of their expensive real estate assets. 

Optimizing the space a company works in can be just as important as filling it with the right people. But figuring out where to position people and departments to improve productivity, team cohesion, ease of movement and aesthetics can be a tricky task. That is unless we allow machine learning to take the wheel. Machine learning algorithms can generate space layout options that maximize utilization while adhering to the criteria we set. The software provides several different ranked options that fit the needs we detail. For example, say a company is rolling out a new product line and wants the sales and marketing teams to be in concert for the product launch. A solution equipped with ML capabilities would be able to create different floor layouts aimed at fostering communication and collaboration between the two departments. It could even add additional parameters to reduce the impact of the redesign for other departments. That way, as one team ramps up for a new project, business continues as usual elsewhere. But this instantaneous reiteration can only happen if you have a design team that is able to work within cloud-based, intelligent design platforms that integrate with state-of-the-art modeling software.

Leasing is another area being changed by AI and ML. Lease management software solutions can help track and manage a company’s entire lease portfolio, addressing the day-to-day operational requirements while helping to ensure compliance to the new lease accounting standards. With the new FASB lease accounting compliance deadline on the way for private companies, there’s never been a better time to be on top of leasing contracts.

But what makes AI-infused lease management software attractive for the facility managers, especially those with a large portfolio of locations and other leased assets, is the ability to quickly visualize the state of each renewal via different metrics. Managers who can get all their data in the right place can drive lease decisions based on individual asset performance, ROI, landlord analytics, trade area quality or market rents. This enables facility managers to come to the table and know whether it’s best to look to renew, renegotiate or exit the lease contract. 

While still in its relative infancy, there is exciting potential with AI-enhanced facility management technology. What once took weeks or even months for acquiring and analyzing data to drive decisions can now be achieved in a fraction of the time. At this point, it may sound like AI is the cure-all to our facility and office management needs, but there are notable caveats. While machine learning offers powerful solutions that can span from conception to maintenance to disposition of the real estate assets, this approach requires an understanding and commitment to the technology to ensure the correct algorithms and data are used in the model for clear results. AI can streamline workflows, but we must take the time to implement it correctly. Having the right infrastructure in place is paramount; learning algorithms are only as good as the data you’re feeding into them. 

For those willing to invest to build that critical infrastructure, AI and ML brings an unprecedented level of speed and security to your decision making, producing faster and far more accurate results than traditional means. We’re entering an age where the office is becoming leaner and smarter than ever before. In the future, I believe it will be crucial for managers to have these tools at their disposal so that they can make timely, accurate decisions to best reflect the needs of their fellow employees and company. AI will serve not only to help automate the office, but to drive insights that would be impossible to glean otherwise. These toolsets are far more powerful, accurate and fast. For facility managers to get the most out of these solutions, we will feed in quality data as much and as fast as we can. AI has a massive appetite for data, and the property industry is going to have to learn how to set the table for it. 

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