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This is why you still see UPS trucks on the road after 5

In March I commented that the time had been passing quickly since I started driving for UPS. Back then I’d gone a whole month between posts. Now it’s August and I haven’t posted anything for five months!

As usual, I’ve been very busy. If you’re a regular reader, you know that my job is more than full-time work. With more than half of 2021 accounted for, my average time on the clock has risen to 52 hours per week.

Here’s a week-by-week summary of hours worked:

WeekStraight
Time
Hours
Overtime
Hours
TOTAL
HOURS
Jan 3-932.2727.6159.88
Jan 10-1636.4724.2560.72
Jan 17-232422.546.5
Jan 24-303215.6447.64
Jan 31-Feb 63215.6547.65
Feb 7-133212.9544.95
Feb 14-2031.9214.7946.71
Feb 21-2730.5513.5444.09
Feb 28-Mar 63214.8446.84
Mar 7-1339.624.2743.89
Mar 14-2031.5315.0246.55
Mar 21-2734.8325.0659.89
Mar 28-Apr 336.6322.7259.35
Apr 4-1038.5817.5156.09
Apr 11-1715.7812.628.38
Apr 18-244019.0559.05
Apr 25-May 139.5319.8859.41
May 2-83219.6851.68
May 9-15406.8346.83
May 16-223218.6850.68
May 23-294019.0459.04
May 30-Jun 5408.948.9
Jun 6-123218.850.8
Jun 13-193219.4851.48
Jun 20-264018.6658.66
Jun 27-Jul 34024.7264.72
Jul 4-1039.9510.3550.3
Jul 11-1739.6422.8762.51
Jul 18-2439.820.1659.96
Jul 25-3139.2720.3859.65
Aug 1-7326.438.4
Aug 8-144013.2453.24
I tabulated these from my weekly pay stubs. There are several weeks where I used sick time for personal business: a death in the family, a graduation ceremony, and a doctor’s appointment. These are few enough that they don’t lower the overall weekly average significantly.

Slightly more than half of my weeks included less than 40 hours of straight time. Those are the weeks where I’m forced to work on Monday, my scheduled day off, only to get ‘laid off’ on Tuesday. The collective bargaining agreement stipulates that overtime kicks in after eight hours of work per shift, so it’s possible to earn overtime with less than 40 hours of straight time in a week.

Why would I be forced in to work on my day off, only to get laid off on a day I’m scheduled to work? This is just one example of the puzzle that is staffing. It’s not unique to UPS or the logistics industry. One can find similar staffing dilemmas across many industries, such as foodservice, health care, and hospitality, among others. But I’ll describe what it looks like from my own perspective.

Every day, tens of thousands of packages arrive at my local warehouse, which is colloquially referred to as ‘the building.’ These ‘units of work’ are then loaded up for delivery to a home or business somewhere in the territory covered by the building.

Depending on total package volume, the territory gets divided up into a certain number of routes. Higher package volume means dividing into a greater number of more concentrated routes, while lower volume means the opposite: a smaller number of more dispersed routes.

It’s not entirely unlike staffing in schools based on the number of students; hospitals or other health care facilities based on the number of patients; or hotels or restaurants based on the number of (expected or actual) patrons.

But back to my own particular case. Each route needs a truck. Each truck needs not only a driver, but also a location in or around the building to be loaded and unloaded. There’s a team of early-morning office staff who set about solving this puzzle on a daily basis.

Dispatchers create or ‘build’ the routes, adding or cutting routes where necessary, and setting down the ever-shifting boundaries between routes. I believe they also keep track of the various routes’ spaces along the conveyor belts and bay doors around the building, with most routes having a more or less permanent space assignment.

Building a route is more than just bundling a set of ‘stops’ in a particular geographic area. It also optimizes the sequence of stops to minimize distance traveled. This is called ‘trace,’ or ORION, after the computer software used.

This is an example of a UPS route. Each green number represents a delivery or pickup stop in the numerical sequence prescribed by ORION.

Every driver will tell you that they almost never follow trace or go in strict ORION order. They use their own knowledge and skills to come up with a workable route based on local conditions, factors the computer doesn’t know or consider.

Sometimes this results in ‘beating’ the route – going faster than the computer estimate. But more often than not it means going slower than the computer estimate for one reason or another.

Next, Operations Management Supervisors (‘OMS’s) assign these built routes to particular drivers. But just as most trucks have a more or less permanent space in or around the building, most routes have a more or less permanent ‘bid’ driver.

Only routes without a bid driver need an assignment, then. These routes are then covered by ‘cover drivers,’ of which I am one. (Since routes are bid out on a seniority basis, all 22.4 drivers and some – usually less senior – Regular Package Car Drivers are cover drivers.)

While the work of dispatchers is performed largely with twenty-first century technology, on computers using data and algorithms, the work of OMS’s – at least as far as staffing is concerned – is performed old-school, on a white board in the office.

Every route and every driver has a name magnet. Route-driver magnet pairs are then organized according to their location around the building. Magnets of routes that have been cut are set off to one corner of the board; active routes are organized by their respective color-coded conveyor belts.

Magnets of drivers who are not working populate the outer edges of the board, grouped together by category: Sick, Vacation, Family and Medical Leave Act (FMLA), Jury Duty, Bereavement, Worker’s Compensation (‘Comp’), Disability, Temporary Alternate Work (TAW), Military Leave, and so forth. This leaves only so many cover drivers’ name magnets still in play.

The White Board in the office. I had to take a quick pic through the window at the end of my Saturday shift after a supervisor, during a busier time, had told me no one was allowed to photograph it. On the cabinet to the right is a very outdated list of which drivers are skilled at covering which routes. When I asked the OMS what goes through her mind when she pairs drivers with routes, she told me it was based on her level of confidence in their skills on a particular route. Thus cover drivers often get ‘typecast’ into specific routes, or certain parts of the area (called ‘loops’), or particular kinds of routes (e.g., rural ‘extended’).

The puzzle of staffing is making sure that one has just enough drivers to cover the routes, with a little cushion for emergencies which always pop up.

Why not simply hire more drivers and give each of them closer to full-time hours – or even part-time hours? Well, there is a class of on-demand drivers known as ‘utility drivers’ or ‘air drivers,’ who often are already working part-time in the warehouse. They fill in during short-term spikes in demand.

But the collective bargaining agreement includes language about a ‘guaranteed eight.’ Full-time drivers are guaranteed eight hours’ worth of work each shift they report to work, and the company must pay them for a full eight hours regardless.

On the other hand, the contract also includes what’s known as ‘the 9.5 rule.’ Full-time drivers whose routes keep them working beyond nine-and-a-half hours per shift are entitled to ‘grievance pay’ after the second occurrence in a given week. The company must begin shelling out triple time for anything beyond 9.5 hours on that third shift of the week.

Taken together, these two rules compel dispatchers to build routes that are computer estimated to be completed within that window between eight and nine-and-a-half hours.

And since no two routes are ever the same – indeed, a single route is never the same from one day to the next – OMS’s must even things out over the course of a shift, directing those drivers finishing their routes ahead of schedule to help drivers on pace to finish late.

Both the ‘guaranteed eight’ and the ‘9.5 rule’ were introduced because the union was concerned about the company replacing full-time drivers with part-timers. In theory, these two provisions are intended to preserve the full-time status of the job and to place a ‘floor’ and a ‘ceiling,’ respectively, for hours worked in a shift. In daily practice, however, most of the pressure is upward.

It’s upward for a couple of reasons. First, because individual drivers must choose to file individual 9.5 grievances for each and every violation. The process is slow and cumbersome, probably by design to discourage its use. I’ve heard that some longtime drivers have never once filed a 9.5 grievance.

And second, because neither the guaranteed eight nor the 9.5 rule apply to 22.4 drivers, who account for up to twenty-five percent of the full-time drivers in any particular building. If I, as a 22.4 driver, finish my shift in less than eight hours, then I must ‘code 5,’ meaning I only get paid for time actually worked.

Everything else being equal, of course management would prefer all drivers to work faster and finish their shifts sooner, because time is money. But drivers know that the faster they work, the more work management will expect of – and impose on – them. Those computer estimates will be updated based on actual performance data. So the goal is to work just fast enough so as not to need help from another driver, but not so fast as to be sent out to help another driver.

‘Just-in-time’ staffing is a fascinating puzzle, to be sure. But it’s also a constant challenge, as it’s a delicate balancing act between spreading the work out too thin versus piling it on too thick. Companies have a tendency to go to one or the other extreme to cut costs. It’s up to workers and their representatives to ensure that balance is maintained.

One reply on “This is why you still see UPS trucks on the road after 5”

Ok, So this is like one of the most thorough explanations of a complex system that the average person signing for a package from UPS would never imagine existed. It’s an incredible marriage of business technology and efficiency with human psychology and effectiveness. I’m impressed By the exposition including photos that feel like they might be worthy of spycam status. Thanks.

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