Accumulating And Analyzing Data From Commercial Cleaning

The final part of this four-part article looks at what BSCs can do with their cleaning data.

The data collected by these smart machines and dispensers is funneled into software platforms created by each individual manufacturer. But what happens from there is the next great, relatively unanswered question in the Internet of Things world.

Obviously, that data must be analyzed so that cleaning trends can be identified and actions can be taken. But who will do the analyzing?

Commercial cleaning equipment manufacturers have worked hard to ensure their data-management software platforms are user-friendly and intuitive. But most admit that BSCs may need to turn to outside help in order make the most of all this data.
 
Some manufacturers are looking into creating consulting departments to provide such services — at a cost. Others are providing that help as part of their IoT packages. One manufacturer even has the expectation that analyzing IoT data is probably beyond the capability of most BSCs, and thus the manufacturer doesn’t even share the raw data with the customer, unless the customer specifically requests access.
 
The approaches vary considerably. As a result, BSCs can probably expect independent cleaning industry consultants to begin offering data consulting services, as well. At the very least, a BSC may need to hire a part-time data analyst.

Then comes the question of a time line for return on investment. Remember, data is only useful if there is a lot of it. Small sample sizes could lead to faulty assumptions about cleaning practices, which could lead to faulty corrections to cleaning practices, which could prove costly.

Data takes time to accumulate — anywhere between several months and a year, depending on the size of the cleaning operation, says Baynum.

“If you have a healthcare facility, or a facility that’s running 24/7, we think within 90 days we can have a significant amount of data to highlight very immediate trends,” he says. “If it’s a slower facility, it could take 12 months. So it’s really going to depend on the frequency and number of visitors.”

But that, say manufacturers, is all the more reason to embrace IoT today — it’s imperative that BSCs begin collecting data right away.

What’s more, IoT — or more accurately, data collection — isn’t a passing fad.

“We all know technology comes and goes,” says Nissen. “But the need for data, leveraging that data and insight to drive action that helps anyone better manage business, I think, will always exist.”

Right now, says Baynum, IoT technology is still only used by the group known in tech circles as “early adopters,” which usually constitutes about 13.5 percent of users. Next will come the “early majority” with 34 percent of the user base, then the “late majority” with another 34 percent. But it might only be another five years before the late majority latches on, he says.

As far as end users go, many BSCs will likely be among the early adopters. The technology is a great fit for the BSC business model in some ways: Economies of scale come into effect with larger machine fleets, and early adopting contract cleaners can and will make use of IoT to stand out when writing bid proposals.

“Today, [IoT] is the order winner. … Down the road it will be the order qualifier,” says Boscher.

If BSCs want to take advantage of an opportunity to differentiate, the time to jump aboard the IoT bandwagon is now, say manufacturers. At the rate technology evolves, IoT will soon become ubiquitous in the cleaning industry — just as it did in the consumer market for the janitor with her Fitbit and her smart TV.