TL;DR
Slotting or picker routing first? Slotting, almost always. Routing finds the shortest path through the stops an order gives you; slotting changes what those stops are. Here is why routing is the smaller, already-solved lever, why its ceiling is fixed by placement, and why the standard routing textbook itself tells you to slot better.
The short answer
Slotting, in almost every case. Routing finds the shortest path between the locations an order forces you to visit. Slotting changes which locations the order forces you to visit at all. One shortens the trip. The other can remove the reason the trip was long. When people ask which to fix first, they are usually comparing two things that are not the same size, and the smaller one gets most of the attention because it is the one that has already been packaged and sold to them.
This article is about why that ordering is backwards, and it is fair to routing while it says so. Routing is not a mistake and it is not wasted effort. It is a genuinely well-solved piece of mathematics that belongs in the picture. It is simply the second thing to reach for, not the first, and the clearest proof of that comes from the standard textbook on routing itself, which spends part of its routing chapter telling you to go and slot better.
The two levers, stated precisely
Picture one order with four lines on it. Four items, sitting in four locations somewhere in the building. A picker has to collect all four and bring them back to pack. There are exactly two ways to make that shorter, and they act on two different things.
Routing takes the four locations as given and asks, in what sequence should I visit them so the walk is shortest? It is a sequencing decision. The stops are fixed; routing chooses the order of the stops and the path between them.
Slotting asks a question one level up: which locations should those four items be in at all? It is a placement decision. It can move a fast item from the far corner to a slot beside the pack station, so that the trip that used to cross the building now barely leaves it. It can put two items that keep leaving on the same order next to each other, so a leg of the trip that used to exist stops existing.
That is the whole distinction, and it is why the two are not interchangeable. Routing improves a trip. Slotting can eliminate the walk that made the trip long in the first place. Routing works inside the set of stops it was handed. Slotting decides what that set is.
Why travel is the thing worth fighting
Both levers exist to attack the same cost, so it is worth being precise about what that cost is. Travel is not a minor line. In Bartholdi and Hackman’s words, opening the chapter on routing:
Travel time to retrieve an order is a direct expense. In fact, it is the largest component of labor in a typical distribution center.
Read that carefully, because it sets up the whole decision. Travel is the largest component of picking labour, and it is pure waste in the specific sense that it costs hours and adds nothing to the order. Every hour a picker spends walking is an hour they are not picking. So the question of slotting or routing first is really the question of which lever removes more of the largest cost in the building, and the answer turns on what each one can actually reach.
Routing is the smaller lever, and it is already largely solved
Here is the part that surprises people. Routing, the thing most warehouse-efficiency conversation is about, is close to a solved problem, and has been for decades.
Finding the shortest path that visits a set of locations is the classic Traveling Salesman Problem, which in general is famously hard. But a warehouse is not the general case. Travel is constrained to aisles and cross-aisles, and that structure, in Bartholdi and Hackman’s words, "makes it possible to find optimal solutions quickly by computer." The foundational result is an algorithm by Ratliff and Rosenthal, and the title of their paper says the whole thing out loud: "Order-picking in a rectangular warehouse: A solvable case of the traveling salesman problem." Solvable. The picker-routing problem, for a normal aisle layout, has a known fast optimal method and a family of simple near-optimal ones on top of it, the serpentine or S-shaped pass through the aisles, branch-and-pick, and their variants.
So if routing is solved, why does any walking remain? Two honest reasons, and neither one is a flaw you can route your way out of.
The first is that most systems do not run the optimal method anyway. Again verbatim: "most warehouse management systems do not support pick-path optimization beyond simple sorting of locations." In practice the WMS sorts your pick lines into location order and lets the picker walk them in roughly that sequence, which is a decent heuristic and nothing like the full optimisation the theory allows. That gap is real, but it is a gap between good routing and the best possible routing. It is small next to the other reason.
The second reason is the one that matters. Even flawless routing can only ever find the shortest path through the stops the order handed it. That is its ceiling, and the ceiling is fixed by placement. If two items on the order sit at opposite ends of the building, the shortest possible path between them still crosses the building. Routing cannot delete a stop, cannot move a stop closer, and cannot decide that two stops should have been neighbours. It optimises the trip. It has no power over why the trip is shaped the way it is. Hand routing a badly slotted warehouse and it will return the shortest walk through a layout that should not have produced that walk at all.
Slotting changes the stops themselves, which is the bigger number
Slotting acts on the thing routing has to treat as fixed. Move a busy item from the back corner to a slot next to pack, and you have not shortened one trip. You have shortened every future trip that item ever appears on. The saving compounds across the whole order stream, quietly, for as long as the item stays there. Put two frequently-co-picked items beside each other and you remove a leg from every order that contains both. Routing re-solves each trip inside today’s layout. Slotting improves the layout that every trip, and every future routing decision, then runs on top of.
That is the sense in which slotting is the larger lever. It changes the problem rather than solving the given instance of it better. And the effects stack in the right order: get the placement right and the routing that follows has less to do, because the stops are already close together and roughly in line with the pick path.
You do not have to take that framing from a slotting advocate. Take it from the routing chapter. In the middle of explaining how to generate short pick paths, Bartholdi and Hackman stop and give this advice:
it is generally better to store the most popular skus close to the path outline, so that they can be reached with little or no detour
And the caption to their figure 10.7 states the result plainly:
A much shorter travel path is possible if popular items are stored close to path outline
That is the textbook on routing telling you that the way to get short routes is to place items well. The best routing has already assumed good slotting underneath it. Slot poorly and you have capped what routing can return before routing even starts.
So why does routing get all the attention?
If slotting is the bigger lever, the fair question is why the industry conversation, and most of the software, is about routing. The answer is not that anyone is foolish. It is that the two problems are shaped very differently for a vendor.
Routing is a clean, self-contained algorithm. It does not need to know anything about your business. A rectangular warehouse is a rectangular warehouse, the maths is the same everywhere, and a routing feature written once ships to every customer. It demonstrates well in a sales meeting, it lives naturally inside a WMS, and it produces a visible line on a screen. It is, in every sense, packageable.
Slotting is the opposite kind of problem. The right placement for your building cannot be computed from a diagram of aisles. It has to be read out of your order history, which items you actually pick, how often, in what quantities, and above all which ones keep leaving together. That answer is specific to you and specific to this year, and it is unglamorous to produce because the work is reading data rather than running a slick algorithm. It does not demo in thirty seconds. So the lever that is easy to sell has crowded out the lever that is worth more, and a picker somewhere is walking the extra distance that neither the routing feature nor anyone’s intuition ever accounted for.
None of that makes routing wrong. It makes it the smaller, solved, sellable half of the problem, sitting in plain view while the larger half sits unread in a table of orders.
Do both, in this order
The honest recommendation is not that routing is pointless. It is a sequence.
Fix location truth first. If the system does not accurately know where things are, neither lever works, because both are computing over a map that is wrong. That is belief one of this whole cluster and it is covered in the chapter on location accuracy. Optimising on bad location data is a confident wrong answer whether you are slotting or routing.
Then slot from the order history, because slotting changes the set of stops that everything downstream has to deal with, and it is the bigger number.
Then let the system route, because once the stops are few and close, sequencing them well is the finish, and it is a finish the WMS is already equipped to give you at little cost.
Reverse those last two and you are polishing the path through a layout you were about to change. Do slotting first and the routing you already have gets easier automatically, which is exactly what figure 10.7 was showing.
One scoped note on the system side, because it comes up. Chapter 1 of this cluster enumerated the eleven location directive strategies in Dynamics 365 and found that none of them ranks placement by velocity, distance, or affinity. The same division of labour applies here. Dynamics 365 will sequence and direct pick work reliably, and it will send pickers to whatever locations your placement put items in. What it does not do is re-derive that placement from a year of orders, because that is analysis you run on your data, not a switch inside the ERP, and it is right not to pretend otherwise. The routing it does, it does as a system of record executing a layout a human decided. Deciding the layout well is the part that is left to you, and it is the part with the larger payoff.
The short version
Routing finds the shortest path through the stops an order gives you. Slotting decides what those stops are. Routing is the smaller lever and is already close to solved, a special case of the Traveling Salesman Problem with a known fast method, though most systems only sort locations rather than run it. Its ceiling is fixed by placement, because the shortest path through two items at opposite ends of the building still crosses the building. Slotting moves the items, so it shortens every future trip at once and can remove a leg entirely, which is why the routing textbook itself tells you to store popular items near the pick path. Fix location accuracy first, slot from the order history second, route third. Do it in that order and every step makes the next one cheaper, and the whole point of getting it right shows up the same way every part of this does: more lines out the door per person hour with the crew you already have.
For what warehouse slotting is and how the placement decision is actually made, read What is warehouse slotting?.
For how you put a number on the walking both levers are trying to reduce, read How do you measure warehouse travel waste?.
For the full ground-up treatment of the problem this sits inside, read Warehouse Pickup Optimization: The Operator’s Guide.
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The mechanism behind these articles, applied to the warehouse you already run.
Mudassir Marwat
Founder & CEO, Cognilium AI
Mudassir Marwat
Founder & CEO, Cognilium AI
Mudassir Marwat's argument is that ERP systems record decisions they never optimise.



