October 25, 2016
Interesting Takes on Determining ROI
How do you determine the success of a wearable pilot? This is a key challenge faced by enterprises today in the still-early days of the technology, for it’s not always a simple matter of numbers and percents. At EWTS 2016, real end users shared first-hand experiences of and outside-the-box thinking about gauging the ROI of wearables in your business.
When we talk about ROI, we usually talk in terms of concrete numbers. But what we heard from a number of enterprise users is that it’s often not easy to pin down numbers with wearable technology; sometimes it’s more practical – even necessary – to qualify than to quantify the success of these devices in your organization.
Peter Godino, Hershey Company: “There is always an ROI when you’re improving the way you do something [but] there are some things I don’t like to put KPIs to. I know there’s an enhancement. Sometimes it’s improving the quality of life for your engineering team or the people on the floor. A lot of metrics cannot be expressed as a dollar return, but we’ve seen a lot of benefits from wearable technology. Line uptime will be one of the big outcomes, though we cannot claim to have seen a reduction in downtime at this time; but we’re pretty sure we’ll have that information in the future.”
While you might view that as sort of a gamble – banking on the hope that one day there will be numerical data to support the adoption of wearables in enterprise – improving employees’ quality of life is no minor benefit:
Kristi Montgomery, Kenco Logistics: “Improving the quality of life for those end users (warehouse workers) is hard to quantify from a dollar perspective…Employee satisfaction and engagement–if we can improve that [then] we feel like we’ve accomplished something even if there’s no hard dollar amount we can account for.”
Peter also spoke to the idea that sometimes you just know there’s an enhancement: Dawn Bridges, Jacobs Engineering: “A wearable that recognizes a barcode is an efficiency.” Replacing hand-held barcode scanners with something wearable that frees up workers’ hands is a clear efficiency, supported by sheer logic if not by a percentage.
George Bowser of DHL gave two sides to the ROI coin: There’s measuring the impact of wearables on productivity and accuracy; and then there are less calculable, even emotional, indicators like ergonomics, impact on workers themselves, and user acceptance. And sometimes it might be necessary to weigh some metrics against others: If it’s not possible to (accurately) calculate an increase in productivity over the short lifespan of a pilot program; talking with users – even handing out questionnaires as DHL does – might reveal other, more immediately observable improvements such as less physical strain or awkwardness for workers using smart glasses to scan items instead of a handheld scanner.
How do you, for instance, determine if new employees learn faster or retain knowledge better when wearable tech is integrated into their training? It’s rather subjective. Maybe we shouldn’t rely on percentages right now or look to numbers to “make or break” this technology in the enterprise. Perhaps, for now, we do have to take that risk based largely upon logical reasoning and user testimonials.
Sgt. Dan Gomez of the LAPD talked about the importance of accounting for user acceptance and including user (and customer) feedback in determining ROI:
“Among law enforcement, measuring success is very different than in private industry. There’s no bottom line; it’s what you feel when you walk into a community. Do you feel safe? [That’s] much harder to measure. Adoption among officers is also important…ultimately it comes down to ‘Can we save an officer’s life?’ ‘Can we prevent the loss of life?'”
In the public sector, ROI often goes beyond a numerical increase in efficiency; it’s about well-being: The doctor’s or the officer’s, the patient’s or an entire community.
In addition, a few speakers shared some very “doable” methods for determining ROI: Joakim Elvander of Sony mentioned focusing on travel time in remote support cases. It is possible to pin this down to a number–ex. 9 trips saved per month for one expert, which reduces the organization’s T&L costs by X amount of dollars as compared to the preceding month (and also improves the expert’s quality of life.) In the same manner you could potentially calculate the impact – in hours – of the wearable solution on machine downtime, by comparing a parallel case in which the expert had to travel or even setting up a kind of scientific experiment with controls and variables (the wearable being the variable.)
Peggy Gulick‘s team at AGCO did just that: “We’re trying to figure out how well the [wearable] has helped us by doing time studies. Part of the way we’re testing it…is by recording someone who has never performed a particular assembly before, using Glass to walk through the steps.” Presumably, the training time of the worker using the wearable would be compared to that of someone utilizing the old tools. This method of setting up a controlled situation for comparison might seem a little time-consuming or even elementary, but it works and can yield real numbers and concepts.
*All quotes are transcribed from the sessions and presentations given at EWTS, June 16-17, 2016 in Atlanta, GA, and therefore may not be exact.
