Industries · FMCG & consumer goods

Keep service high without teaching the forecast your stockouts.

Consumer demand moves by SKU, channel, geography and event. Recorded sales alone understate demand whenever stock was unavailable. SIAARU separates the signal from the constraint, then connects the corrected demand view to inventory placement and replenishment.

See the operating pattern
Nerve · FMCG & consumer goodsILLUSTRATIVE

“Which SKUs are likely to stock out next week, and which forecast periods are distorted by lost sales?”

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Nine SKU-location pairs need review. Two demand periods were censored by stockouts, four transfers can protect service, and three replenishments require approval. Each recommendation shows the sellable days and source movements used.

Source rows attachedApproval requiredOutcome rechecked

01 — What the operation exposes

The pattern behind the daily fire drill.

01

Censored demand

A stockout appears as weak sales and pushes the next forecast lower.

02

Channel blindness

Distributor and retailer stock is late, incomplete or mixed with owned inventory.

03

Ageing versus availability

The network holds excess stock while the selling location is empty.

04

Event-driven volatility

Promotion and festival effects arrive faster than static parameters change.

02 — SIAARU's response

From fragmented signal to governed action.

Nerve does not replace the operating system of record. It connects the dependency, prices the consequence and moves one evidence-backed decision to the correct owner.

01

True demand

Replays stock movements to identify periods where recorded sales were constrained by availability.

02

Channel view

Keeps reported, unreported and zero stock as three separate operational states.

03

Stock optimisation

Calculates safety stock and reorder points from demand and lead-time variability.

04

Ageing action

Ranks dead and slow-moving stock by working capital and the downstream demand still attached.

03 — Decision flow

One change. One traceable chain of consequence.

Every result remains illustrative until it is computed from the client's own approved data. No benchmark or customer outcome is implied.

  1. 01Sales and stock signals arrive
  2. 02Censored periods are identified
  3. 03Transfer and buy options are compared
  4. 04Planner approves and service is rechecked

04 — Capabilities

The modules behind demand, freshness and service in one decision.

05 — Control boundary

Autonomous attention.
Accountable execution.

DefaultRead existing systems and recommend
ApprovalNamed person and policy gate
OptionalClient-approved write-back by action
ProofSource, rationale, timestamp and result

Bring one real constraint

See FMCG & consumer goods decisions
on your operating data.

Start with a CSV export or a read-only connection. We will map one decision from signal through approval and verification.

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Bring one month of data. Leave with your own control tower.

A demo runs on your material master, your purchase orders and your stock — not on ours. Thirty minutes, and you see your own exceptions rather than a scripted one.

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