How to size a contract review team without guessing

Ask a legal ops lead how they'd justify hiring another contract reviewer, and the evidence they reach for is almost always the same: contract volume is up this year, so headcount should go up too. It's a reasonable instinct, and it's also a weak way to build the case, because a good chunk of that volume never lands on a reviewer's desk to begin with.

If your intake process routes contracts into buckets, some paper gets auto-approved on sight, some gets a quick confirmation against a position your team already decided, and only a slice needs someone to sit down and actually think about it. Total contract count blends all three together. Ask for a new hire based on total volume, and you're asking finance to fund capacity for work that was never going to consume a reviewer's time in the first place. A sharp finance partner catches that in the first meeting.

The pressure behind the request is real. Nearly 8 in 10 corporate law departments reported legal matter volumes increasing over the past year, and at the same time, nearly two-thirds reported flat or decreasing attorney headcount. The gap between rising work and flat staffing isn't going away on its own. But the case for closing it needs a better number than "contracts are up."

Count the bucket that actually eats hours

The number to build a staffing case around is the count of contracts landing in full review, not the total coming through the door. Multiply that by the average hours a full review actually takes, redlines and back-and-forth included, and you get the real hours of work the queue generates in a month. Compare that to the hours a reviewer has left after meetings, training new hires, and the rest of a normal week, and you have something a budget conversation can hold onto.

This also shows you the lever you actually have when volume rises. The routing logic that sorts contracts into those buckets in the first place is worth getting right before anything else, because if the share of contracts landing in full review keeps climbing, your playbook and your intake rules are covering less of what's arriving than they used to. That's worth fixing before you fix it by hiring. If the ratio holds steady and the hours per full review haven't moved, more volume really does mean more people, and now there's a number behind the ask instead of a feeling.

Why the queue doesn't slow down evenly

There's a second reason contract volume alone misleads people, and it has nothing to do with legal work specifically. It shows up in call centers, emergency rooms, and warehouse loading docks: when a resource runs close to its full capacity, wait times don't rise in a straight line with demand. They bend upward fast.

An operations professor who teaches this exact math to MBA students frames it in plain terms: cut a system's spare capacity in half and the average wait roughly doubles, not because the system got twice as busy but because it now takes twice as long to work through a backlog once one forms. A review queue running at, say, 70% of a reviewer's available hours can absorb a rough week without falling behind for long. The same queue running at 90% doesn't have that room, and one busy week turns into a two-week backlog that doesn't shrink until volume actually drops.

That's the practical reason "we're a little behind" turns into "we've been behind for six weeks" almost overnight. The team wasn't gradually more understaffed the whole time. It crossed a point where its spare capacity nearly disappeared, and the queue did the rest on its own.

Where AI changes the math, and where it doesn't

An AI contract review workflow can shrink the hours side of the equation by running a first pass against your playbook and handing the reviewer a shorter list of items that actually need a judgment call. That's real capacity, even if it isn't unlimited capacity. It does nothing to the demand side. The number of contracts needing a decision doesn't change, and a person still has to work out what a flagged clause means for this particular deal. Treat it as a way to raise how many full reviews one person can get through in a week, not as a reason to stop counting.

Building the model behind that math doesn't take a dashboard. A spreadsheet with monthly full-review counts, average hours per review, and available reviewer hours will tell you more than a raw contract count ever will, and it's a number finance can actually evaluate instead of taking on faith.

Try goHeather free if you want to see what a first pass looks like against your own queue before you build a staffing model around it.

This is legal information, not legal advice; consult a lawyer for legal advice.