The art of BI business user adoption - an illustrated Domo use case from Mayer Electric

Jon Reed Profile picture for user jreed June 30, 2021
When it comes to BI and analytics, user adoption is a huge hurdle. Few organizations have achieved the level of adoption Mayer Electric has. Scott Wagner shares the story of how he became the "BI guy" - and how his business users embraced a new approach to data and reporting.

Scott Wagner - Domo
(Scott Wagner sharing his Domo story)

After Domopalooza 2021, I gave Domo the use case challenge: if business users are so energized by Domo's approach to BI, then bring one forward.

Soon after, I was on a video call with Scott Wagner, Director of Business Intelligence Strategy with Mayer Electric. Wagner prominently lists his "MajorDomo" role on his profile, so what does that entail? (In the Domo world, a MajorDomo is a "dedicated internal Domo expert," with the job of supporting their company's changing business and data requirements).

Founded in 1930, Mayer Electric is a wholesale electrical distributor. As Wagner told me, Mayer Electric has entered a "transformative stage" where they are pursuing connected solutions and digital products. And yes, COVID-19 added impetus to those change efforts.

From Excel on-the-fly to BI guy

Five years ago, Wagner was a self-described "informal report nerd" with Excel skills; he supported users' reporting needs on the fly as best he could. Something needed to change. As Wagner told me:

I was one of the people in the company folks would call when they needed something, and the questions were getting increasingly difficult. So rather than just kind of faking it with Excel, I made the suggestion that we should get a real analytics tool.

Be careful what you ask for, joked Wagner. If you raise your hand, you might end up owning the project:

I made that suggestion to our president... I'm now the BI guy. It's been a great journey with Domo.

During the BI selection process, what made Domo stand out? Wagner:

The real 'aha' for me is that there was a difference between this product and the others we were looking at. Getting to an actionable level of information stood out. Also that user experience piece: that's really everything. If you don't have that, you don't have anything.

Conversations with other BI customers informed the decision:

Talking to other Domo customers and customers of other platforms, that really was a difference. I was told by one person who's doing a similar role that their developers loved Tableau, but their users loved Domo. And that was a key selling point for me.

Driving Domo adoption

After Mayer Electric chose Domo, usage proliferated. As of my interview with Wagner, they were at 815 Domo users - out of 1,250 total employees:

The only folks left that don't have it are in roles where they're not in front of a computer the majority of their day: truck drivers, warehouse associates, things like that.

It took half a year after go-live for the Domo traction to build. But was Wagner able to support that adoption by himself?

We got Domo in December of 2016. It probably took us about six months to get our feet under us. And honestly, a lot of that time was me learning some new things. Like I said, I was an Excel guy, but I needed to obviously learn Domo, and some SQL, which I got help on from our IT department. I'm a team of one, so I don't have somebody I could lean on to figure it out as we went. But it was pretty straightforward.

To drive Domo adoption, Wagner combined top-down and bottom-up:

After that first six months, we rolled Domo out to our executive team - and then to our branch manager. We went down the organization to start... I was also doing a bottom-up approach to addressing development needs.

Getting data results - by winning over business users

Wagner used Domo to shift Mayer Electric's reporting approach. At first, he created dashboards based on individual questions from frontline managers. But starting in April 2019, Wagner gave certain line managers more rights in Domo. That worked:

Up until then, everyone was just a participant user. In other words, they were consuming data. This person, we gave them rights to build content. I see that as a turning point for us where things really took off. Nathan Harr, he's our Domo master for accounting. He obviously understands that job. He does it day in, day out. He knows things and has developed things that I never could have as the analytics guy.

Mayer Electric now has eight different people performing that Domo master role in different functions. "Our plan is to expand that as much as we can," says Wagner.

Wagner didn't sugarcoat the initial resistance of some users. "They were honestly very content, doing things the way they've always done it," Wagner says of the finance team. But Wagner says having an internal advocate, in this case Harr, was the key. They looked for small wins to build on. Wagner cited the monthly close process, where the 6-8 person accounting team would run a report and print a stack of paper "a few inches thick," and see if they spotted anything unusual. Enter Domo:

We wrote something in Domo where it looks at every account for every business unit for every period, and statistically identifies outliers, things that are significant. It could be something that's $100; they could pop up on this report. Essentially, the way we look at it is we're delivering the needles now. So they can find them, and it's not at the end of the process. Anytime during the month, they can look at that report, and address something as it happens. That's just one example of a lot of change that went on in that group, and it's still going on.

Those changes led to tangible benefits: they've also reduced their year-end closing process, completing it 14 days faster than the previous year. Wagner:

Their month-end close processes are seeing the same kind of impact. It's taking a couple days less than it had in the past. And I think their executive reviews are quicker or more streamlined. They can do them on a tablet or a phone, and it looks really good, too. That's surprising for an accountant, that the aesthetic came out of it. But again, it's a nod to Domo and the capability of the tools.

Domo in action - Mayer Electric sample cards

I asked Wagner if he could provide us with a few customized Domo "cards" that are popular with users at Mayer Electric. He shared a few annotated examples with sample data, explaining the value of each card. Start with this Domo card for identifying general ledger outliers:

Mayer Electric - Domo 1
(Via Mayer Electric, used with express permission.)

Next up: Wagner shared a role-based Domo card for Branch Admins:

Mayer Electric - Domo 2
(Via Mayer Electric, used with express permission)


Wagner's third card is used by Mayer Electric's ticket writers, again to highlight action items:

Mayer Electric - Domo 3
(Via Mayer Electric, used with express permission)

The wrap - AI/ML versus common sense

I asked Wagner if he believes AI/ML will be an asset to Mayer Electric, surfacing action items beyond what you might see on a dashboard. Short answer: yes, and the general ledger outliers could be considered an early example of that. Wagner's team is now looking at a project to understand Mayer Electric's "customer DNA." Could AI/ML play a role? Wagner says data science concepts can seem abstract; it's not always easy to know what will apply to Mayer Electric. But the examples are out there:

There are so many natural stories you hear. Things like a dental office that wants to understand how to plan their appointments, and they realize on days with bad weather, they get the largest number of cancellations. 

Is there something like that, where there's a correlation for us? We're looking at things like our deliveries, how often we go to certain places, what's our distance we drive, again, trying to find nuggets of efficiency, that we can back up with common sense.

We talked about earning user trust in new data tools, amidst potential fears of change or job displacement. At the time of our talk, Wagner was set to go on an internal roadshow, talking directly to managers about data-informed decisions. He also planned to discuss useful research versus distraction:

The night you got the Internet the first time, how much time you did you spend clicking things? This can be like that, too. There is meaningful data, and then there's distraction, and how do you understand the difference?

A classic BI dilemma: cool dashboards don't guarantee better decisions. Wagner:

I want our managers to feel comfortable challenging the data. But also understanding they may be imposing additional risk by doing that. Maybe they ought to think about it, and then try to ask another deeper business question to validate.

Wagner also hopes to fan the sparks of data curiosity, the flip side of distraction: "We want to encourage data curiosity, while limiting data distraction." A worthy goal indeed.

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