The Batching Trap: 3 Ways It Feels Efficient but Isn’t

One of the Lean principles we teach in our Introduction to Lean Thinking workshop is to make value flow at the pull of the customer. Flow is the continuous delivery of value. The opposite of flow is batching your work, yet people insist on doing this for efficiency. Don’t fall for the batching trap! Here are three ways it feels efficient, but isn’t.

Making Value Flow at the Pull of the Customer

Most service organizations are built to push. Work gets started because a staff member is free, forms have piled up, or the schedule says it’s Thursday, not because a customer is waiting on the outcome. Making value flow means arranging the steps that create value so work moves through them steadily, without stopping in queues, inboxes, or hand-offs.

Think of a patient referral at a specialty clinic. The actual work of reviewing records, verifying insurance, and scheduling might take forty minutes, yet the referral often sits for two weeks. It waits in a fax queue, then for a batch review on Fridays, then for a callback after playing phone tag.

Flow attacks that waiting. It brings the people involved closer together, shrinks batches toward a best case of one, and removes the hand-offs that let work go cold. The goal is a process where a request, once started, keeps moving until it’s done.

Pull adds the discipline that keeps flow honest: nothing is produced until a customer signals a need for it. In service work, overproduction is easy to miss. It is reports that nobody reads, intake packets assembled for appointments that get cancelled, or proposals written before the client has confirmed the scope. Pull means responding to real demand instead of guessing at it.

Together, flow and pull change the central management question. Leaders stop asking how to keep everyone busy and start asking how to deliver exactly what the customer needs, when they need it, with as little waiting as possible. For most service organizations, that shift frees up significant capacity.

What is the Batching Trap?

People batch work because, from where they sit, it looks efficient. A billing specialist who processes all claims on Thursday afternoon avoids switching between tasks, gets into a rhythm, and clears a visible pile in one sitting. A manager who reviews time-off requests once a week protects her calendar. Each person is optimizing their own piece of the process, and often doing it well. What they can’t see is the cost that lands on the customer and the next step downstream: the claim that waited six days, the employee who couldn’t book a flight.

Most service organizations reinforce this blind spot with the metrics they track. They measure utilization, items processed per hour, and how full each person’s day is, but rarely the elapsed time from request to result. When busyness is what gets noticed and rewarded, batching is the rational choice.

There are structural reasons too. Some steps carry a real setup cost, like pulling a physician into a review meeting or logging into a clunky system, and batching spreads that cost across more items. Software often encourages batches through nightly runs, weekly billing cycles, or approval queues designed around a team’s calendar.

Batches also feel safe. A full inbox signals job security, and a big pile hides problems, while single-piece flow exposes every delay and error immediately. The answer isn’t to tell people to stop batching. It’s to lower the cost that makes batching attractive, by simplifying setups, giving decision authority to the people closest to the work, and measuring lead time alongside productivity. Once small batches are easy and the customer’s wait becomes visible, the behavior changes on its own. 

3 Ways it Feels Efficient to Batch but it Isn’t

These three issues related to process time, quality, and variation are often only noticed by downstream users or end customers.

1. Fewer interruptions feel faster, but the customer waits longer. Processing all referrals in one Friday session saves a few minutes of task switching. But a referral that arrives Monday now waits four days before anyone touches it. The work itself takes no less time; it just sits longer between steps. In most service processes, the value-added time is a small fraction of total lead time, so a batching policy that saves minutes of effort while adding days of delay is a bad trade, even though it never shows up on anyone’s productivity report.

2. Clearing a big pile feels productive, but it multiplies errors. When forty claims go out together and one coding mistake is baked into the routine, all forty carry it. The denials come back weeks later, long after anyone remembers what went wrong, and the rework costs far more than the original task. In a one-at-a-time flow, the first error surfaces quickly and gets fixed before it spreads. Batching hides problems right up until it makes them expensive.

3. Batching feels like it keeps everyone busy, but it creates waves of overload and idle time. When Friday’s referral review releases thirty approved patients at once, the schedulers face a flood on Monday. Calls stack up, callbacks slip, and overtime kicks in, followed by a quiet stretch midweek while they wait for the next batch. Leaders read the Monday crunch as a staffing shortage and the midweek lull as slack. Neither is real. Both are artifacts of the batch, and smoothing the flow often reveals more capacity than the team knew it had.

Using a KPI dashboard can help organizations see the issues batching creates in processes.

Summary: Flow Reveals Waste

Here is one final point about forcing your process into flow that comes up at most training workshops I lead. Any time I hear an argument for why continuous flow won’t work in a process I ask the reasons why. Then I get out my notepad, because all of the reasons I hear for why flow won’t work are wastes in the process.

Some of these wastes may be issues you can’t fix, yet. For example, I used to batch my check deposit process because I had to drive 15 minutes from my office to the bank anytime I needed to deposit a check. Now that my bank offers mobile deposits (a pull process for their customers) that constraint is gone and I no longer batch that process.

So if you are batching your work record the reasons why this is necessary and attack that waste!

Please share your stories about batching or ask questions below.