Branch-level service variation could be the overlooked cost of growing a copier dealership

Faraha Jebi, UI/UX Designer at Auralis AI

Faraha JB

October 23, 2026 · 4 min read

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  1. Growth is how a dealer ends up with more of these seams
  2. Branch data doesn’t surface itself
  3. The report built to compare branches
  4. Sources

Two studies from different settings land on a similar point: local management can account for a meaningful share of the gap between one part of an organization and another. Gallup estimates that managers account for at least 70% of the variance in employee engagement scores across business units. A separate study of a technology services company found that swapping a bottom 10% supervisor for a top 10% one raised a team’s output more than hiring one more person would, on a nine-person team. Neither study is about copier dealers, and neither measures a service call.

They raise a question we keep coming back to for copier dealers: whether that same kind of local difference shows up in how branches handle service calls. Does one branch answer a call a little differently than the branch across the state line? We have no evidence that it does, only a reason to think it’s worth checking.

Growth is how a dealer ends up with more of these seams

A dealer that grows, whether through an acquisition or by opening a new office, can end up running more than one operation day to day, each with its own habits for how a service call gets logged and who gets called first.

We don’t have a number for how much of that turns into real inconsistency once the org chart settles. We couldn’t find a published figure for copier dealers specifically, despite looking. What we can say is that for dealers running e-automate, branching is a real structural level in the software, and Service Statistics can analyze service activity by branch.

Branch data doesn’t surface itself

You can create more than one branch under a company in e-automate, and here’s the part that matters for this: you can configure e-automate so a user only sees the data tied to their own branch when they log in. For a dispatcher whose job is one branch, restricting the view that way can make sense on its own. If access is set up that way, a cross-branch look at the business needs someone with wider access to go run a report for it.

The report built to compare branches

The report for that is Service Statistics, and it can analyze service activity by rep, branch, and/or company. Set goals for things like average response time, mean time to repair, recall percentage and efficiency, and the report flags any data missing the goal in red font. The report only includes a Main Branch Averages section if you include two or more technicians in the run. ECI recommends running it for at least one month. A shorter period, the help page warns, may not provide enough data for meaningful statistics.

One limit worth knowing before you trust it: the report only counts calls with a labor record attached. A call a dispatcher closed on the phone without logging labor won’t show up, so a branch that resolves more on the phone can look quieter than it actually is. Interpret the numbers alongside what you already know about how each branch operates.

We’d pull it by branch before we’d look at the company-wide average. A company-wide average can obscure a branch running fine sitting next to one that isn’t.

In our experience, the branch and executive dashboards dealers ask for are light ones, an end-of-day summary or a dispatch room view, not a big build. Service Statistics, run by branch, gives you a rough preview of what a view like that would show.

Service Statistics doesn’t prove your branches are running differently, but it’s one way to check.

If the branch numbers do point at routine work piling up, Choosing the right AI automation for your team compares scripted bots, generic AI and AI agents, and how to tell which one your desk needs.

Sources

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Faraha Jebi, UI/UX Designer at Auralis AI

Faraha JB

UI/UX Designer

Faraha leads UI/UX at Auralis, designing the interfaces and interactions that make an AI agent feel trustworthy and genuinely helpful to use. From first wireframe to final pixel, she owns the details that decide how the product feels. Her craft shows in the places most teams overlook — empty states, error messages, and the micro-interactions that build trust in an AI product. She designs for clarity first, and it shows on every Auralis surface.

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