How I approach system design, capacity planning, QA statistics and the responsible use of AI where mistakes are costly.
Off-the-shelf dashboards break down under the repetitive work of operations analysts. I build single-window workbenches with sub-second feedback, no wasted re-renders, optimistic local caching and full keyboard support.
Planning capacity on headcount or scheduled shifts alone sets teams up to fail. I model real capacity in worked hours only: subtract shrinkage (breaks, training, sick leave), match queue arrival patterns and plan overtime thresholds.
Auditing 5 tickets picked at random gives a false sense of security. I build structured QA sampling engines that calculate statistically representative sample sizes, track inter-rater reliability and separate systemic root causes from random human error.
Fully autonomous AI in trust, safety and content intelligence brings serious hallucination and liability risks. I build strict human-in-the-loop gates: AI pre-classifies and summarizes, and the trained human operator makes the final call.
I run multinational service delivery across European markets. I manage SLA, ART, CSAT and AHT to contract, and I run calm, structured post-mortems when serious outages happen.
Cutting cognitive waste (Muda) and overburden (Muri). I use DMAIC to redesign workflows, which has cut cycle time by up to 40% and operating costs by 65% across multi-skilled hubs.
1. Software either costs operators time or gives it back. Off-the-shelf enterprise suites often add admin overhead that slows front-line teams down. Custom tools built on lightweight web standards return that time to operators.
2. Metrics have to reflect what is really happening. High CSAT bought with an unmanageable backlog or burnt-out teams is a failure that looks like success. Healthy operations balance throughput, customer satisfaction and operator endurance.
3. AI assists. People decide. In sensitive areas like trust, safety, moderation and employee performance audits, AI should produce structured recommendations with confidence scores for a human to sign off. It should never issue verdicts on its own.
Tell me about your operations challenges, tooling needs or service delivery goals.