The happy path is not enough

A new enquiry arrives. A contact is created. A task appears in the right place. The demonstration works. But that is only part of the job.

I am also interested in the day information is missing, a tool responds too late or the same request arrives twice. That is often when an automation reveals whether it really helps the team or creates another clean-up task.

Decide which system is authoritative

Before connecting two tools, I would write down what each one owns. Where should a customer’s name be changed? Which system determines order status? Should a change in the destination system travel back to the source?

These questions sound straightforward until two systems show different values. A small process map, with responsibility assigned for each important piece of data, avoids a lot of ambiguity.

Plan for common exceptions

I would group situations into three categories: continue, retry and request intervention. A missing optional value does not necessarily need to block the entire workflow. An ambiguous identity may be a good reason to stop.

• Should a repeated request update an existing item or create a new one?
• Can a temporary error be retried without repeating the entire action?
• Who receives an alert if the workflow remains blocked?
• Where can someone find the context needed to understand the failure?

Technical documentation guides recovery. For example, Klaviyo explains rate-limit responses and how to respect the communicated delay before another attempt. See its API limits and errors documentation.

Make the operation visible

A quiet workflow is not always a working workflow. I would define a few simple signals: the last useful execution, items still waiting and errors that need a decision.

I would also document how to pause, resume and correct a case. On the day the person who built the workflow is unavailable, that information becomes more useful than an impressive diagram.

Start small, then expand

For an initial launch, I would choose a limited scope and examples that can be followed. I would check the result in the destination tool and then the ability to handle an unusual case.

Automation is more than moving data. It means deciding what should happen when the data or tools do not behave as expected.

Success also depends on how easily your team can understand the system and take over. That independence deserves to be delivered alongside the connection.