How to know when a van sales route needs to be split in two

A snack and confectionery distributor started one van on a route of 38 stores. Eighteen months later, the same van was still running the same route — except the store count had grown to 61, one or two new accounts added almost every month because business was good and nobody wanted to turn away a sale. Nobody had ever decided to make the route bigger. It just did, one small store at a time, the way a junk drawer fills up.

The symptoms showed up before the cause did

The first sign wasn't a number anyone was tracking. It was the rep calling in around 3 pm to say he wouldn't make the last four stops before closing. Then it was a corner store owner mentioning, almost as an aside, that the competitor's rep had started showing up on Tuesdays too — the same day iotoms's rep used to come before his visit times had drifted from mid-morning to late afternoon. Then it was the load sheet: a van sized for 38 stores' worth of daily volume was running short on the fast movers by stop 50, so the last third of the route was getting whatever was left, not what the store had ordered.

None of these looked like a routing problem from the inside. The owner's first instinct was to blame the rep — he must be slow, or taking long lunches, or not managing his time. A second rep covering the route for a week during a leave of absence hit the exact same wall at the exact same stop number, which settled that argument. The route itself had quietly outgrown one van, one rep, and one working day, and everyone had been managing the symptoms — later stops, thinner stock, more customer complaints — without ever naming the actual cause.

Why nobody caught it earlier

Growth by addition is invisible in a way growth by acquisition isn't. Adding one store to a 40-stop route doesn't change anything anyone can feel that day. It's the fortieth addition that breaks something, and by then there's no single decision to point back to — just a route that used to fit in a working day and now doesn't, with no record of when it crossed the line. Paper route sheets and a rep's own sense of "I can manage" hide the drift especially well, because a good rep will absorb the first 20% of overload by working faster and skipping breaks before they ever say anything.

The other reason it goes unnoticed is that the obvious fixes look like they're working. Add a little overtime. Push the low-priority stops to every other day instead of daily. Load the van a bit heavier. Each of these buys a few more months before the same pressure resurfaces, worse, because the underlying route is still one route trying to be two.

The turning point: measuring the route instead of guessing at it

The distributor didn't split the route on a hunch — a supervisor pulled the actual visit data the field app had been logging the whole time: check-in and check-out timestamps at every stop, order size, and drive time between stores. It showed exactly what the rep had been saying with less precision for months: average visit time had crept up as sales at each store grew, drive time between the far-flung newer stores added up faster than anyone had noticed, and the honest capacity of one van on that geography was around 45 stops a day, not 61.

With that, splitting the route stopped being a guess about who should go where. The 61 stores were mapped by location and grouped into two clusters that kept driving distance low within each half, rather than just cutting the list in two alphabetically or by revenue. The higher-value, tighter-clustered half stayed with the original rep, who already had the relationships. The newer, more spread-out half became a second route, with a rep hired specifically for it and a load-out sized to that route's actual volume.

The rollout mattered as much as the split itself. Customers on the new route got a heads-up call before their visit day changed, so the switch looked like better service — a rep who actually arrived on time — rather than a disruption. The first two weeks were watched closely: visit times, stockouts, and any store that seemed to be falling through the cracks between the two routes. By week three, the numbers that used to show up as vague dissatisfaction — a late visit, a thin shelf, a shrugging "we'll get you next time" — had mostly disappeared, and the total volume moving through the two routes was higher than the one overloaded route had ever managed.

Actions: how to tell when a route needs to split

• Watch visit-time drift, not just visit count. A route that used to close by 2 pm and now closes at 5 pm with the same stop list is a route running out of capacity, even if nobody's added an account this month.
• Check whether the last quarter of the route is getting a worse service level — thinner stock choices, shorter visits, more "we'll catch you next time." That's the load and the day running out at the same point, every day.
• Pull actual per-stop time and drive-time data before deciding how to split, instead of splitting a customer list by headcount or by revenue. A geographic split that keeps drive time low inside each half beats an even split that doesn't.
• Size the new route's load-out to its own volume, not half of the old van's average — a newly split route usually has a different order mix than the parent route did.
• Announce the change to customers before it happens. A route split that looks like better service keeps the accounts; one that looks like a disruption invites a competitor's rep to fill the gap.
• Watch the first two to three weeks closely for stops that fall between the two new routes — that's usually where a split needs a small correction, not a full redo.

iotoms logs every stop's arrival, departure and order size from the same field app the rep already uses, so a route's real capacity shows up in the console as a trend — average visit time, drive time between stops, stockouts by route — well before a rep has to call in and say he's not going to make it.