With Confidence

Optimizing the workplace is a priority for many facility managers – balancing the needs of upper management to save costs, while simultaneously providing a more suitable workplace for employees to complete their work. This is truer now as an increasing number of organizations shift to new diverse workplace models. It presents a fantastic opportunity for FMs to rethink the kingdom over which they rule. However, the overarching objective of this optimization can quickly become a polarizing topic for FMs, particularly without solid data to back up the decision-making process.

The question is:

It is certainly possible to make educated guesses, but as with any argument, hard facts win over gut feeling. In this case, data removes much of the guesswork for FMs, providing a reliable and objective source of information on which to base decision making. It is also indispensable proof to present before committing to actions when sharing plans with other stakeholders.

Getting started

Before any FM rolls up their sleeves to deal with data, there are several things they ought to heed:

Pure-software workplace systems

Pure software-based systems often promise a lot for little investment with no need to deploy hardware. While software-based systems are a critical component of room reservations and other space management activities, having a hardware component can provide added value in the form of real-time tracking of actual behavior.

Take, for example, a room booking system. An employee books a meeting room in a prime location: it is near all the commonly used amenities, has several ergonomic features and access to wired high-speed internet. What if the employee changes their mind about coming into the office that day and no longer needs the space, while also not bothering to cancel their reservation? Without something as simple as a meeting room panel for checking in to the space, there is no way of knowing that the booker has not shown up for their booking and will remain reserved within the software. On paper this looks good, space is being well utilized; however, there is prime desk space going unused for half the day.

The right hardware to support FMs

This naturally leads to the topic of necessary hardware and sensors. Within any modern workplace, there is an ecosystem of hardware and other IoT (Internet of Things) devices communicating and working together to paint a digital picture of the workplace composed of data. Hardware such as room-booking panels or desk-booking devices help gather data regarding space utilization and occupancy.

Meanwhile, measuring any aspect of the physical world, sensors are meticulously tailored for a variety of application-specific functions. This can include functions such as detecting human presence or other data points such as current capacity, total footfall, environmental temperature, natural lighting and so on. Every piece of hardware or sensor is an invaluable data collection point, gathering vital data that by itself is not so meaningful, but when placed alongside other data can offer something vastly more significant and relevant.

Therefore, it is apt to think of there being both “good data” and “bad data.” So, what is bad data? Simply put, data from a single source which is not combined with data from a separate independent source to identify trends and correlations. It gives an overview, but only at a shallow level, and does not give anything that can be acted upon.

Good data, on other hand, is that which is combined with a large amount of other varied data from different sources. For example, space reservation data, capacity, occupancy, temperature and lighting data can be compiled together to form an insightful and accurate overview of the workplace that is highly diverse and rich in information.

Pre-deployment checklist

Here are some steps to prepare before rolling out IoT and adopting a data-driven approach to decision making in the workplace:

• Map out goals and what insights the team wants to capture. Make sure there is a clear understanding of business outcomes. This will help ensure the team has the right tools, can prioritize projects and focus on the needed data points.

• Explain to employees in advance what the team is doing. While intentions may be good, they can easily be misinterpreted. Employees may ask: “Are these devices being installed to spy on me every time I check in for a meeting room?” or “Why am I being tracked?” leaving a sense of uneasiness and distrust. It is important to explain why it benefits them and how it works (i.e., is data anonymized, who it is shared with, etc.)

• Get IT involved. Even the best laid plans can still fail without taking basic considerations, such as will it be possible to provide power to these IoT devices, and if so, what new infrastructure will be necessary to support all these devices that utilize Power over Ethernet (PoE). IT is the best bet for logistical problems. Ensure any new integrations will be successful and fit into the bigger strategic plan laid out by the organization in terms of their technology roadmap and needed support for rollouts.

• Enterprise over consumer grade. Enterprise-grade hardware should always be advocated for over consumer grade. It is simply better built for the task at hand and can offer lower total cost of ownership.

• Avoid disparate systems. Choose an IWMS (Integrated Workplace Management System) that can reduce organizational siloes and capture all data in one integrated system. All this captured data needs somewhere to live so it can be analyzed and used to improve decision making. Having one system across the FM organization will save everyone time, effort, and money.

• Decide who is in charge. As ever, choosing a good leader to drive the project, as well as be held accountable for both successes and failures, is key to any initiative. They also need to believe in it and be willing to throw their full weight behind it.

Typical key metrics to look out for in the workplace

Reservation data

By far the simplest thing to measure is booking data. This data shows who, when and how often spaces are being booked by employees, as well as cancellations and no shows, and can be easily gathered through room booking displays.

Actual usage vs. reservation data

A simple metric for evaluating how long people are using the space they booked against the time for which they reserved it. This can be achieved by comparing bookings against the actual time a meeting room was used before users checked out of the space.

Occupancy data vs. location

This is the data that shows the actual time your workplace resources are being utilized. How long was the meeting in Room 203, how much time employees spend away from their desk during their booking, and so on.

Percentage usage of full capacity

How often and when facilities are at full capacity, if it all.

Utilization data of different space types

This simple metric clearly shows to which level spaces are being utilized, which is particularly useful when there are a variety of spaces, including meeting rooms, huddle rooms, conference rooms, silent booths, and lounges for example. This can be evaluated with room check-in data.

Historical vs. current occupancy data

Essential for identifying trends over time, and how employees’ habits are changing over time in response to actions by the FM or from external factors.

Meetings vs. desk versus other types of spaces

When adjusting floorplans and increasing or reducing certain types of space, this metric can be referenced against other data such as over-utilization to evaluate efficacy.

You’ve got your multifaceted data, now what?

The question now is what should be done with this fresh-from-the-oven data. What trends are being looked for? What needs improving about the workspace, and how can it be adjusted to meet the needs of employees? Where can costs be saved? Or, returning to face the dilemma of deciding between reducing the space the organization is renting, or maximizing the utilization of the space currently held, or a fine balance between the two.

Data itself is the raw ingredient. Now it is time to produce insights that can enable better decisions around spaces. FMs do not want to have to go to many disparate systems to get those insights. With an IWMS infused with data from a variety of sources and analyzed with the help of Artificial Intelligence (AI), FMs can bring together critical utilization and occupancy metrics into a modern dashboard to deliver easy-to-understand data visualization on space usage — all in one place. They can then use these insights to make decisions for lease renewals, determine if expansion or consolidation of space is needed, and provide the types of spaces occupants need when they need them.

Take, for example, the problem mentioned earlier of a hot desking system. Employees make reservations, then either do not show up or cancel it, blocking it from use by other employees. Upon checking live reservation data, it displays more than 90 percent of desk space is utilized; however, employees have complained in the past about being unable to make bookings, despite plenty of desks being unmanned. That is a problem. Upper management may also see a host of empty desks and incorrectly believe that there is too much space and begin to ask questions regarding the necessity for such vast office space. Issues can quickly become exacerbated.

This highlights how important it is to centralize and compare data from different sources — the booking system and occupancy sensor data — in a single platform to pinpoint the root cause of issues and to evaluate whether shrinking the organization’s footprint, or making better use of the space, is the right decision in this situation.

A success story

IBM Global Real Estate (GRE) consistently uses data and insights to be an AI-driven real estate organization. Prior to the COVID-19 pandemic, it dramatically improved space and lease management and reduced costs using insights generated through IWMS. When the pandemic hit, they needed an even better understanding of real-time occupancy and utilization to understand how their spaces were being used.

They were able to provide real-time occupancy status overlaid with workspace data. The organization is enhancing the solution with IoT building sensors, Wi-Fi access points and heat-mapping technologies that can deliver critical information on space usage, including overcrowded areas.

As for the results, the GRE team reduced the time to complete space utilization analysis for a location by 99 percent, from 10 days to 10 minutes. In addition, with highly accurate space utilization data, GRE leaders can optimize usage and expenses across the global portfolio.

Conclusion

Right-size facilities, maximize what one currently has, or meet in the middle? There is no single answer for each individual organization. However, driven by the wealth of data and insights now under their belt, FMs can make the right decision. The data confirms what they knew from the start, or the outcome is a new revelation. Either way, it facilitates a new level of confidence in decision making, based on hard facts over gut feeling.