Does Proptech Have a Place in Submetering?

The Problem With Proptech

Proptech, or property technology, is a broad term encompassing any use of digital technology (i.e., software) in the real estate industry. And of course, software has provided many a useful tool in various professional settings. But that doesn’t mean it’s always the right tool for the job. After all, a Cuisinart is a fabulous kitchen tool. Unless you’re cooking a steak. You may have had some mouthwatering NY strip in mind, but what you’re going to end up with is uncooked mush.

Why isn’t proptech a good solution for submetering? Because submetering isn’t a software problem, any more than cooking a meal is. Even if you could somehow program a food processor to cook a steak, it’s not going to be able to handle every detail that goes into making a proper meal. It won't do the shopping for you, bring the groceries home, put everything away (properly!), and then make not only the steak but also the sides (because you’re a grown-up and you eat your vegetables, mostly). And it won't clean up either. Yet someone has to put leftovers away, wash the dishes, and wipe down the counters or tomorrow's a mess. Making a meal from start to finish is a lot more than cooking one item, just as submetering is a lot more than running data through an algorithm. That is, if you’re planning to actually do something with it. If you’re submetering for show, well, it’s your money. You can stimulate the economy any way you choose.

Proptech companies will talk about submetering commercial and campus properties as though the job were simple: you install meters to measure utility consumption and then use that data to bill tenants and track load on your equipment. They’ll make it sound like it’s just math –
time-consuming for humans, easy for computers.

Here’s what the proptech bros aren't talking about:

• what kinds of meters to use for your goals and your specifics,
• where the meters need to go in the building to meet those parameters,
• how their proprietary protocols allow them to cut you off from your own data whenever they choose,
• why it’s not fine to capture the majority of consumption in the common area costs,
• how much of your existing systems and network can be leveraged to keep your costs down,
• how to verify the system so that everyone agrees about its accuracy,
• how difficult it is to retrobill when you find out the billing has been wrong, how much it’ll cost you to fix everything,
• how much liability you’re opening yourself up to,
• that they can’t answer questions about the meters, the data, or the billing because they’re a software company, and
• that their company is equity-funded and unlikely to be around in 5–7 years.

And that’s the short list. We could go on.

Think we’re exaggerating? Here’s a real-life example of what happens when you hire software to reason and problem-solve instead of experienced humans.

Downtown Debacle

A facilities director for a large company knew her utility recovery was too low and the failure rates for various components throughout the submetering system were high. Also, because of the high failure rates and a poor submetering design, utility costs had to be recouped mostly through common area charges. This overreliance on CAM, she knew, opened up the risk of tenant disputes over lease terms and accurate ESG data, which was important to a major tenant.

The proptech company that the director started with (let’s call them “Jerques.com”) was unresponsive to her concerns. In fact, they went one step further. When the director finally cancelled the contract, Jerques refused to turn over both the building’s submetering data and the meter nomenclature, citing the “proprietary” nature of their services.

utiliVisor was brought in to help the onsite team get back on track. What did we find? Submeters that had failed, submeters that were installed incorrectly, and communications systems that didn’t communicate.

Our conclusion about how this situation came about: Jerques either:

a) lied about having commissioned the submetering system or

b) somehow thought that they did commission it. If so, they clearly didn’t know how to do it. Just because a system spits out numbers doesn’t mean those numbers are accurate.

A HUMAN SOLUTION FOR A HUMAN DILEMMA

For a problem this comprehensive, it’s essential to be sure of your foundation. We began by identifying what each meter was measuring and reference-testing them, to determine what was good and what needed to be fixed.

This entailed:

• Documenting all meter locations, electric panel service info, one-line electrical diagrams, and meter-to-remote-point maps.
• Reference-testing all meters and replacing if faulty. Incorrectly installed meters were correctly reinstalled and all meters were programmed to correctly capture all of the power being consumed at each measurement point.
• Tracing loads for high-visibility clients and reviewing all billing to make sure tenant bills and consumption data were accurate.
• Reprogramming all data collectors to use open protocols to ensure compatible, interoperable communications long-term.
• Validating the entire system so it now meets code, local law requirements, and utility allocation needs. We compared our own manual readings with the system’s remote readings for a full billing cycle to ensure that field readings and remote readings actually synced up.