Individual skill
otif-analysis
Audit delivery performance from order-level data - compute the OTIF metric ladder (tolerant to strict), find where lateness concentrates, and quantify the gap between the reported KPI and what customers experience. Use when the user mentions OTIF, on-time delivery, delivery performance, late orders, teslimat performansı, zamanında teslimat, or asks why customers complain despite a high on-time score. Differentiator - exposes measurement choices before optimizing operations.
skills-imported/otif-analysis/SKILL.md
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SKILL.mdcore · 3,896 bytes
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# OTIF Analysis
Most "delivery problems" are measurement problems first. Before recommending any operational fix, establish what the honest number is and which definition choices inflate the reported one.
## Required data
Order-level rows with: `order_id`, `requested_delivery_date` (what the customer asked for), `promised_delivery_date` (what was confirmed), `actual_delivery_date`, completeness info (lines ordered vs delivered, or qty ordered vs delivered), and a status/cancelled flag. Useful cuts: carrier, region, customer, product family.
If `requested_delivery_date` is missing, say so explicitly: only the promised-date rungs are computable, and the analysis cannot see sales-padding. Recommend capturing the requested date going forward.
## Workflow
1. **Validate before computing.** Count duplicated order rows; flag impossible dates (actual before order date); count cancelled orders and state how they will be treated. Report these counts in the output - an audit that silently cleans data is not an audit.
2. **Compute the metric ladder** on the same population, strictest last: