Customer Collaboration — Demand Signal Sharing and VMI.

I· Integrated

From → To

From the planning pain to customer collaboration — demand signal sharing and vmi.

What it is

VYAN extends planning to customer locations operating under VMI or visibility-sharing agreements. Customer-pull patterns are tracked through Pull Erraticity Index — a measure of consumption volatility specific to VMI locations — and feed driver distributions for that customer’s demand. Customer demand is decomposed into pull (revenue) and replenishment (planning) signals; the planning engine respects both. Distributional commits flow downstream to customers, mirror to the supplier-collaboration pattern — the customer sees the buyer’s expected supply envelope, not just a confirmed quantity.

Forecast accuracy at customer locations rises because the system sees actual consumption, not stated forecast.

Value

Forecast accuracy at customer locations rises because the system sees actual consumption, not stated forecast. VMI relationships deliver their full value — service rises, working capital is properly attributed, partner terms enforced in the engine. Customer relationships are strengthened by quantified transparency, not by buyer-side fire drills.

Pain

Customer demand signals arrive late, often only as firm POs, often only after the customer’s own plan has hardened. The buyer-side forecast is a guess at what the customer will order. VMI relationships exist but most planning systems treat VMI inventory as either own-inventory (misrepresenting working capital) or external-noise (missing the supply opportunity). The customer’s pull variability is invisible to the engine. Roadmap. V1 supports VMI modeling with pull/replenishment decomposition and Pull Erraticity Index. Full request-commit collaboration with distributional signals downstream to customers is V2 scope.

Impact

Forecast accuracy structurally capped by the latency of customer signal. VMI relationships under-deliver on their promise because the system doesn’t see the customer’s actual consumption pattern. Shortage events propagate to customers who could have been warned earlier with a quantified expectation.

What ships in this capability

01VMI-aware demand decomposition (pull vs replenishment)
02Pull Erraticity Index calibration per VMI customer
03Distributional supply commit publication downstream
04Customer-side consumption-signal ingest
05Per-customer driver distributions for variability