Building end-to-end chain visibility across 3PLs, distributors, and channels: the weeks-of-cover math that makes it useful, the SKU-aliasing swamp that makes it hard, and the snapshot-versus-transaction trap. Public excerpt; the full teardown lives in the Builder library.
Supply chain visibility is a data-unification build wearing an operations costume: the dashboards are ordinary once the chain's five disagreeing systems have been made to tell one story. Four layers do the making.
Layer 1 — Ingestion from everything that touches inventory. Commerce platforms, 3PL and warehouse systems, distributor EDI feeds, supplier confirmations — landed raw on schedule. EDI deserves special respect: the standards are standards the way English is a language, and every distributor speaks a dialect. Budget for per-partner mapping and keep the raw documents forever.
Layer 2 — Product identity, or: the SKU-aliasing swamp. The same physical product exists as your internal SKU, the 3PL's item code, each retailer's identifier, a case-pack variant, and a marketplace listing. Until a mapping layer resolves all of them to one product (with pack-size math handled explicitly), "how much inventory do we have?" has five answers. This mapping table is the least glamorous and most valuable artifact of the build — same lesson every industry teaches, CPG just teaches it with more aliases.
Layer 3 — The cover model. Raw counts flatter you; the useful number is weeks-of-cover: position against live velocity and supplier lead time, per SKU per location. Cover is also where lead-time truth enters — quoted versus actual, by supplier, trended — because cover computed on the supplier's optimistic quote is a countdown clock set wrong.
Layer 4 — Flags, not just charts. Projected cover breaching the reorder horizon, a PO slipping, an SLA trending down — routed to specific owners with the context attached. The dashboard earns attention in week one; the flags are what still deliver value in month six when nobody's staring at charts anymore.
The 3PL's snapshot and its transactions told different stories. Daily inventory snapshots from the 3PL didn't reconcile with the transaction feed (receipts minus shipments) — drifting apart by a little more each week. The gap was real: adjustments, damage, and cycle-count corrections that appeared in snapshots but never as transactions. The fix was structural: trust the snapshot as truth, use transactions for freshness between snapshots, and surface the reconciliation gap itself as a metric — because unexplained shrink is an operational finding, not a data bug to hide.
A case-pack conversion doubled an inventory position. One retailer's feed reported eaches; the mapping assumed cases. A SKU showed comfortable cover while its actual position drifted toward a stockout. Unit-of-measure became an explicit, validated field on every mapping — with magnitude checks that flag when one node's position moves in a way the flows can't explain. Silent unit errors are the CPG cousin of the energy stack's unit trap: same lesson, different warehouse.
The full teardown — the per-partner EDI mapping approach, the product-identity table structure, the cover-model math, and the reconciliation-gap monitoring — lives in the Builder library.
Implementation detail, checklists, and the parts we'd rather not have public — for members.
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