Across-the-Board Inventory Cut at an Aftermarket Parts Distributor
An aftermarket parts distributor holds 22,000 SKUs in one central DC and six branches. Inventory is $34M, turns are 4.1, and line fill is 91.2% against a 97% target. Backorders run 8,400 lines per month, and overnight expedites cost $95,000 per month. Last quarter, finance imposed a 15% across-the-board inventory cut. Fill rate fell four points, and expedite cost rose 30%. Safety stock is currently set as four weeks of average demand for every SKU, regardless of variability. ABC analysis shows 12% of SKUs generate 78% of revenue, while 65% generate 6%. About 1,100 SKUs had no sales in the past 12 months but carry $1.9M of inventory. Carrying cost is 22% per year.
1. Explain why the across-the-board cut damaged service, using the data.
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The across-the-board cut treated all SKUs as if they had the same variability and service consequence. Safety stock was four weeks of average demand for every SKU, which already overstocked stable, low-value items and understocked erratic fast movers. A 15% cut removes inventory wherever it is easiest, often from A items because they carry the most dollars. That is exactly where a stockout stops a sale and triggers an expedite.
C items are 65% of SKUs but only 6% of revenue; cutting them frees little cash and creates many small stockouts that still generate backorders and customer friction. The 1,100 no-sale SKUs tying up $1.9M are the real target, but they need a disposition process, not a blanket cut. The 30% rise in expedites confirms the cut reduced availability, not waste. The lesson: inventory reduction must be segmented by variability, margin, and criticality; a uniform percentage is a finance convenience, not an inventory policy. The four-week rule also ignores lead-time variability from suppliers, which is likely a major driver of the fast-mover shortages.
2. Design a segmented inventory policy with service-level targets and safety stock logic. Include what to do with the 1,100 dead SKUs.
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Segment with ABC/XYZ. Set service targets by segment: A/X 98-99% fill, A/Y 97%, B 95%, C 90%, and critical spare parts by customer contract. Replace the four-week rule with a safety-stock formula: SS = z x sqrt(LT x sigma-d squared + d squared x sigma-LT squared), using actual demand and lead-time variability. Use fill rate rather than cycle service level where partial shipments are acceptable. For intermittent SKUs, use Croston or bootstrapping rather than normal-demand formulas. Review C items less often but set min/max.
For the 1,100 dead SKUs: freeze replenishment, identify contractual or service obligations, then return to vendor, liquidate, donate, or scrap; target $1.4-1.6M recovery. Reallocate the freed cash to A items. Pilot one branch for eight weeks and measure fill, expedites, and turns before rolling out. Do not cut all C items to zero; some may be low-revenue but essential to a customer relationship, so classify by criticality before disposal.