Imagine you oversee operations for a portfolio of office and residential high-rise buildings. Your boilers have increasingly required emergency repairs and you’re convinced that the systems could be run effectively if your team had access to the right technology. After a lengthy due diligence process, you find a solution with an online dashboard that displays real-time data about your boilers. You sign a contract and deploy the technology, only to find that your operators almost never use the tool.
This situation is increasingly familiar for real estate executives. As with anything, simply making something available does not necessarily mean that it will be applied correctly, or even used in the first place. As the pace of technology deployment in commercial real estate quickens, the likelihood that tools adopted in the boardroom are not being used in the mechanical room is increasing in kind.
The answer is not to stop adopting technology as that would mean missing out on a major catalyst for growth. Instead, technology deployments can become more effective by avoiding the pitfalls that lead to poor internal adoption. Here are the common reasons that technology does not get utilized as intended.
The most powerful force that new technology is up against is inertia. There is a concept in psychology called the overconfidence effect. As the name suggests, humans reliably believe that their judgements are better than they objectively are. Because of this, it is natural for teams to resist a new tool because it isn’t seen as an improvement to their own knowledge and skills. Ironically, the more training and experience someone has, the more pronounced this effect tends to be.
The solution to this problem is to spend some time upfront to get everyone on the same page. Agree on the goals, whether those are improving the ratio of planned to unplanned maintenance, maximizing efficiency, or reducing the amount of tenant complaints. With an agreement in place, frame the technology as a tool to support their judgement as professionals. This will make it much more likely to get buy-in from the team.
While this may sound trivial, this process has been shown to work even for surgeons and pilots who have every reason to be overconfident in their abilities.
Getting buy-in for new technologies can get people in the door, but from there it is up to the technology. One common issue is that many tools are built by technology experts with little knowledge of what it’s like in the field.
Going back to the boiler example. There are a range of IoT-based solutions that could help collect real-time data about the system to inform better decision making. Unfortunately, too many solutions deliver raw units of measurement to operators, significantly reducing the likelihood of sustained adoption.
Imagine your team, being completely unfamiliar with kilowatts (kW) for energy tracking or hertz (Hz) to measure vibration, relying on a tool that displays absolute changes in those numbers. It doesn’t matter if it’s in real time, unfamiliarity a sure fire way to have your team stop using the solution.
The answer to this is to understand what your team already knows and ensure that any new technology speaks their language. Over time, the team may gain knowledge and unlock more sophisticated tools and analyses. This should be encouraged, but it can only work from the ground up, not the other way around.
While it’s crucial that your team is able to understand the data provide by new technologies, perhaps more important is how actionable those data are. Unfortunately, the word “actionable” has been used so frequently that it has lost much of its meaning, but it remains an essential piece to the puzzle.
For example, many traditional fault detection and diagnostics (FDD) solutions operate largely based on thresholds. Going back to our boiler example, an alert that there is some sort of anomaly in how a boiler is operating, such as a significant change in power draw or vibration, can be useful.
However, this is like a doctor simply telling you that you are sick. It's the "how" that's important. Pulling from a historical set of similar equipment data and mapping the nature of the anomaly to a specific fault, such as short cycling or pump failure, is the "how" that matters to your team.
Operators are in constant triage mode. If they do not know the nature of the issue, they cannot effectively prioritize, must find time to perform an investigation, and will become weary of the new technology. On the other hand, if they get notifications on the specific scenarios they are facing, they are much more likely to continue using a solution.
It can be difficult to cut through the noise to determine if a solution will be actionable. One good rule of thumb is to inquire which building verticals the company serves. If the solution can be applied to nearly any building type, there is a high likelihood that the solution is more generic and less actionable. This is because equipment operates very differently in different verticals and mapping anomalies to real-world faults is very difficult without focus on a certain set of predictable behavior.
Along the same lines, a major reason for poor internal adoption, especially among FDD solutions, is the number of false positives.
There is a significant opportunity cost associated with false positives; any time an operator spends investigating an anomaly that is not a real problem is time not better spent elsewhere. Especially early in the adoption period, there is limited tolerance for this type of scenario. One too many false positives and your team will stop using the solution entirely.
Again, it can be difficult to tell which technology will produce false positives before implementing it, but there are clues. Diagnosing real world conditions from a data set requires feedback from the real world. If there is no built-in feedback mechanism in the solution, it is highly likely that there will be false positives.
There is another issue that is probably familiar to every person in today’s world – being inundated with new information.
The constant triage that building operators are performing centers around physical building systems. Adding a tool that delivers an endless cascade of new information and thus requires digital triage is likely to go nowhere.
Even if all the new information is actionable and not a false positive, your team still cannot be everywhere at once. They also cannot be expected to remember every piece of information that has been sent their way.
To avoid this issues, ensure that new technologies for your building operators provide them the ability to “snooze” notifications for times where they are less busy and stores all notification in an easily accessible place.
Your team is in the field, not at desks. It should be obvious that a tool needs to be accessible on mobile devices to be adopted by on-site operators.
The trick here is to find the right balance between accessibility and detail. Mobile devices are great for working on the go, but the smaller screens make it difficult to communicate the level of detail that is required in building operations.
This ties back to finding a solution provider for your particular building type and business needs. Companies focused on the business requirements, rather than the technological requirements, are more likely to understand how to provide only what is needed in limited screen real estate.
Security is an issue on the mind of every person in charge of technology adoption in commercial real estate.
The balance here is to combine robust security with ease of use. If an operator in the field needs to login to a platform in order to view a notification, the likelihood the tool will be adopted in the long run is very small.
Data needs to be sent and stored securely, but this does not require constant user authentication. To avoid this issue, find out if and when a technology requires logging in while in the field.
The final pitfall that those adopting technology for teams in the field should avoid is cumbersome processes required to utilize them.
As mentioned, a built-in feedback mechanism from users in the field is essential to provide actionable insights and avoid false positives. However, if this feedback mechanism is not streamlined to its absolute bare essentials, you can expect poor utilization by your team.
When evaluating solutions, walk through the full process with the technology provider. If the process for those in the field takes more than a couple minutes, it is likely that they will not use it at all.
Have you seen any other reasons for poor adoption in the field? Comment below to share. If you'd like to judge whether your team would use Enertiv's solution, schedule a demo today.