Lesson 10 — The catalogue quotes the highest

Multi-supplier materials show 10–30% price variance — and the catalogue typically carries the highest of the three

For materials with multiple suppliers, the prices from those suppliers routinely span 10–30%. Same molecule, same dose, same specification, three vendors — and the highest is 25% above the lowest. This is not unusual; it is routine.

What’s more pointed: the catalogue’s quoted price for the material — the one used in cost reports, the one feeding margin calculations — tends to be the highest of the available supplier prices, not the average or the median.

Why the catalogue quotes high

Catalogue prices are often set at master-data entry time using the first supplier’s invoice, or the most recent invoice, or a buffer above expected cost. Once set, they tend not to drop when cheaper suppliers enter. The mechanism is price ratchet upward, price sticky downward.

Three operational reasons:

• The catalogue feeds DRG cost reports. Conservatively-high prices protect against margin surprises.
• Update friction. Lowering a catalogue price requires a master-data change with downstream effects (DRG calibration, cost-centre reports). Increases are routine; decreases need a reason.
• Supplier-mix volatility. If supplier A is cheaper this quarter but supplier B was cheaper last year, the cautious price is the higher one — it stays right when the mix shifts.

What this does to the analytics

The headline financial impact: catalogue prices systematically overstate cost. On materials with multi-supplier variability, the catalogue’s CHF is 5–15% above the actual blended invoice price. Across a 10–15 K-material catalogue, this is meaningful.

Three signal pathologies follow:

1. signal_negative_margin under-fires. A material’s margin computed against catalogue price is more pessimistic than the real margin. Genuine negative-margin items can hide behind the optimistic-buffer cushion.
2. signal_cross_site_price_consistency misreads supplier mix. Two hospitals with different supplier-share distributions can show the same catalogue price and very different invoice realities. The signal sees consistency in catalogue and misses divergence in execution.
3. signal_multi_source_materials is mostly accurate but reads the catalogue’s quoted price, which is the wrong reference for “is this material being procured efficiently?”.

What changed in the analysis

Two structural moves:

1. Invoice-weighted blended price became a parallel measurement to catalogue price. The dbt model surfaces both: catalogue_price (what the master data says) and blended_invoice_price (volume-weighted average across actual invoices in the window). Signals downstream choose which is appropriate.
2. The Wisdom anchored a new thesis: thesis_catalogue_price_drift — materials whose catalogue price exceeds blended invoice by > 10% for two consecutive quarters are flagged for catalogue refresh.

What stays interesting

• A narrow multi-supplier spread (< 5%) on a material that should have variability is itself signal. Either the suppliers are coordinating prices (a procurement concern) or two of them are actually the same vendor under spelling drift (Lesson 04).
• A widening spread over time can indicate that one supplier is exiting the market and the remaining vendors are raising prices toward the absent competitor’s ceiling.

Why this is in a Lessons journal

Because “the catalogue price is the price” is the kind of foundational assumption that costs analysts a year before it gets questioned. The catalogue’s price is a record of an entry decision, often years stale, sometimes deliberately conservative. The Wisdom is what separates the data the system thinks it has from the data the procurement reality actually generates. Once that distinction is named, the analysis can hold both numbers and read them honestly.

Sources

• Wisdom: smebit_multi_supplier_price_variance.yaml
• Provider: a hospital procurement director with medical-supplies oversight
• Anchor signals: signal_multi_source_materials, signal_cross_site_price_consistency
• Anchor thesis: thesis_supplier_concentration_risk
• Date Wisdom captured: 2026-05-08