Contact center operations

What I have done in this field

I have built service units from nothing and taken over existing ones. From a site with forty seats to the service center of a private university that took on first-level support for three departments.

Building

Site selection, recruiting lead time, technology, first client. When my site builds went wrong, it was mostly during preparation. My rule of thumb: if you want to open in January, start hiring in October. Have the knowledge base ready before the first call.

Quality and pay

A quality system nobody understands changes nothing. So I built scorecards a team manager can explain in a conversation, and only tied pay to them once the measurement was stable.

When I introduced a scorecard for agents, there was a great deal of skepticism, and the works council was at the table. We went through the metrics together until it was clear what they reward and what they cannot measure. In the end the system worked, and it convinced the people who had been against it. Since then, I first ask what a metric rewards, and only afterward whether it can be measured.

Multilingual teams

You do not lead a team from nine countries with one rulebook. Expectations about response time, directness and escalation differ, and without shared definitions people argue about interpretation instead of performance.

Knowledge is the real obstacle

When we built a first-level function, the technology was ready within weeks. Agreeing who gives which answer, and who keeps it up to date, took months. That determines whether an overflow team actually eases the workload.

What AI has changed

I introduced an AI solution for inbound calls. It took load off the operation, and it set off knock-on effects I had not accounted for. Automating the simple cases also changes the remaining ones: how long they take, how hard they are, and what a good call even means afterward. That calculation belongs before the rollout, not after it.