Early Adopter Stories

How design-partner teams are reducing forecast error in their supply chains.

A small cohort. Real supply chain work.

Lean Path works with a carefully selected group of design-partner plants and suppliers in Japan's automotive sector. These teams help shape the product by working with us directly during the early-access period, in exchange for close support and forecasts calibrated to their actual operations.

Design-partner cohort, 2026

Tier-2 Stamping Supplier, Aichi Prefecture

This team was managing machining schedules against a pattern of emergency orders from their primary customer. Order timing was unpredictable, safety stock levels were set by intuition rather than signal, and planning was largely reactive to the previous month's shipments.

During the pilot, Lean Path mapped the assembly plant's pull schedule against the supplier's standing orders and flagged three recurring over-order patterns tied to a seasonal model changeover cycle the planning team had not isolated. The pilot ran for eight weeks, focused on a defined set of stamped component families.

Reduced unplanned reorders across tracked SKU families over the pilot window
Three recurring over-order patterns identified and explained to planning staff
Planning team moved from shipment-history baseline to forward pull schedule as primary input

Pilot profile

8 weeks

Structured engagement from initial data connection to full forecast accuracy review

Pilot profile

6 weeks

From first ERP data export to weekly forecast delivery integrated into existing planning workflow

Design-partner cohort, 2026

Assembly Support Plant, Kanagawa Prefecture

This production planning team was ordering based on the previous month's shipment volume rather than the assembly line's forward pull schedule. The mismatch created consistent over-ordering on high-volume part families and under-ordering on low-volume components that spiked unpredictably with model variants.

Lean Path's focus during this pilot was establishing a demand baseline calibrated to the assembly line's actual daily schedule, distinguishing steady-state pull from model-variant exceptions. The outcome was a planning cadence grounded in what the line was actually going to need, rather than what it had ordered before.

Improved alignment between purchasing orders and actual line pull during the pilot window
Model-variant demand spikes separated from baseline SKU families for distinct planning treatment
Planning team transitioned to weekly forecast review cycle rather than monthly order review

"Before this we were ordering against last month's numbers. Now we have something that actually looks at what the line is going to pull. It changes the whole framing of what a planning week looks like."

Supply chain planning lead, early-access design-partner program

Join the next design-partner cohort

We work with a small number of sites at a time. If your team is managing multi-tier demand planning in automotive supply chains in Japan, we would like to hear from you.