Everyone knows tech debt. You shipped fast, you cut corners, and now the codebase punishes you for it with interest. Ops teams have spent a decade watching engineering teams live with it and feeling smug.
Stop feeling smug. The same thing is happening in your automation stack, and it’s further along than most operations leaders want to admit.
Here’s the pattern, and see if it sounds familiar. A problem appears. Failed orders, mistagged returns, a courier exception, whatever. Someone builds a workflow to catch it. The workflow works. This is genuinely good, and it happens again, and again, in the returns platform, in the flow builder, in the middleware, in the email tool, in a few Zaps somebody set up in 2023 and left the company without documenting.
Three years later the brand owns dozens of automations, sometimes hundreds. Each one made sense when it was built. Together they form a web nobody fully understands, where changing one rule risks breaking three others, so nobody changes anything, so the automations drift further from how the business actually works, so more automations get built to patch the drift.
That’s debt. It has all the properties of debt. It accrued from decisions that were individually reasonable. It charges interest, in this case the growing gap between what your automations assume and what your operation does. And the payments are invisible right up until they’re not, usually during peak, when the web does something nobody predicted and nobody can trace.
One conversation we had recently put a sharper edge on it. The observation was that less-automated brands are, in one specific way, better positioned right now than the sophisticated ones. They haven’t got the tangled web. When they adopt new tooling, including AI tooling, they’re building on a clear site. The mature brands have to untangle first, and untangling a production automation web while it’s running is the operational equivalent of rewiring a house with the electricity on.
How to tell if you have it
A few honest questions. Can anyone in the business produce a list of every automation currently running, across every tool? Not a partial list. All of them. If the answer is no, you have automation debt by definition, because you’re paying interest on liabilities you can’t enumerate.
Second question. When did you last delete an automation? Teams add workflows constantly and retire them almost never, because deleting feels risky and nobody owns the decision. A stack that only grows is a stack that’s rotting.
Third. When something weird happens in an order flow, how long does diagnosis take, and how much of that time is spent working out which automation touched it? If the answer involves opening four different tools and asking someone who left, you already know.
Paying it down
The fix is not a tool. Resist the vendor who says otherwise. The fix is treating automations the way good engineering teams treat code.
Start with an inventory. Every workflow, every tool, one register, with an owner and a one-line statement of what business outcome it serves. This is boring and it takes a fortnight and it’s the single highest-value exercise available to most ops teams this quarter. You will find automations nobody can explain. Those go on the kill list.
Then kill things. Set a rule: for every workflow added, one gets reviewed for retirement. The point isn’t the ratio, it’s making deletion a normal act instead of a scary one.
Then raise the bar for new ones. “Add a workflow” should face the same scrutiny as “add a system,” because that’s what it is, a small system, with maintenance costs and failure modes and an integration surface. The question to ask isn’t “can we automate this” but “is this a downstream patch for an upstream problem we should fix at source.” A remarkable share of automations exist to tidy up bad data that a mandatory field would have prevented. Fix the field, delete the workflow.
Where AI actually fits
AI is being sold as the answer here, and it’s half true. Used to understand the web, mapping what exists, tracing what touched an order, explaining what a five-year-old workflow actually does, it’s genuinely powerful, and it’s the best untangling tool available right now.
Used the other way, it’s an accelerant. AI makes building new automations nearly free, which means a team with no discipline can now generate strands for the web faster than any human ever could. Cheap creation plus expensive maintenance is exactly the equation that produced tech debt in software. We’re about to run it again in operations faster than more teams are ready for.
The brands that come out of this well won’t be the ones with the most automations or the fewest. They’ll be the ones who can produce the register, name the owner of each strand, and delete something without holding their breath. Everyone else is still rewiring the house with the power on.
If nobody in your business can produce the full list of automations running right now, book a call with us. The inventory is the fortnight of work we help brands get through.