Most automation projects do not fail at launch. They fail quietly, three months later, when the team goes back to the spreadsheet. We build the kind that sticks.
If you are researching automation consultants, odds are decent this is not your first attempt. Somewhere in the company's past there is a Zapier account nobody logs into, a workflow tool bought after a convincing demo, or an integration a developer built that stopped working when an API changed and was never revived. The team routed around it, the subscription kept billing, and the manual work came back like weather.
The uncomfortable truth is that these projects rarely fail for technical reasons. They fail because the automation was designed around a tool instead of around the workflow, because nobody mapped the exceptions before building the happy path, or because the people who had to live with the system were handed it instead of consulted on it. We wrote up the full anatomy of this pattern in why your last automation project didn't stick, and the longer analysis in our insights article on why automation projects fail.
Our engagements are structured specifically against that failure mode: diagnose the workflow first, design around the exceptions, build with the team rather than at them, and come back at 90 days to verify the automation is still running and still being used.
Three design decisions, all made before any tool is chosen, determine whether an automated workflow is still alive a year later.
Every workflow has a clean version that happens 80% of the time and a messy version that happens the other 20%. Automation built for the clean version collapses the first week a rush order, a partial payment, or an angry customer arrives. We document the exceptions during the diagnostic and design explicit routes for them, including the route that says a human handles this one.
The most expensive automation failure is the invisible one: the workflow that stops firing and nobody notices until a customer calls. Every workflow we build alerts a named person when it fails, and the handoff documentation says what to do when that alert arrives.
The people running the manual workflow today know where the bodies are buried, which steps are theater, and which field in the spreadsheet actually matters. We interview them in the diagnostic, review the design with them before the build, and train them during the build. Automation imposed from above gets worked around. Automation the team helped design gets defended.
We do not resell software, and we do not take referral fees from platforms. It is the mechanism that keeps the diagnosis honest. A consultant whose revenue depends on a platform will find that every problem happens to need that platform. Ours depends on the workflow working, so the tool gets chosen last, after the map is drawn and the design is approved.
In practice, a single engagement often mixes approaches: native automation inside the CRM you already pay for, an integration platform where systems need to talk, and custom code only where nothing off the shelf fits. Sometimes the right answer is embarrassingly cheap, a feature already included in software you own, switched off. The diagnostic finds that before you spend build money on it. This discipline is part of every engagement model on our services page, and it applies double when the workflow crosses systems, the situation we cover in why your systems aren't talking.
A meaningful share of our diagnostics end with us recommending against part of the automation the client came in wanting. A workflow that is still being argued about should not be frozen into software. A task that takes a person twenty minutes a week will never repay a build. A decision that depends on judgment and context, whether to bend a policy for a good customer, how to word a delicate email, belongs with a person. And a broken process, automated, is just a broken process with better throughput. When the underlying process is the real problem, the right engagement is business process consulting first, automation second. We would rather lose a build than sell you one that ends up in the drawer with the last one.
Launch day is the worst possible moment to declare an automation project successful, because adoption has not been tested yet. So we do not. At kickoff we baseline the manual hours, the error rate, and the cycle time of the workflow as it runs today. Ninety days after the automation goes live, when the novelty is gone and the team has had every chance to fall back to the old spreadsheet, we measure again and put the comparison in writing. If the numbers moved, you will see exactly how far. Our client results show what those audits look like.
Every engagement is baselined at kickoff; results are measured against that baseline, not against averages.
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