Capabilities Inventory optimisation and reliability

Capability · Inventory optimisation and reliability

The right stock is not the highest stock.It is the stock you can promise.

Align physical truth, service levels, lead times, variability and risk to position, protect and replenish inventory with judgement.

A capability shaped by your flows, rules and field evidence.

E-commerce peakActive scenario01SignalDemand rises on a family with long supplier lead time.02DecisionCombine targeted safety stock, channel allocation and fulfilment capacity.03ProofService, coverage and peak cost compared.04Active systemERP05Active systemOMS
01 / 04Absorb the peak without permanently inflating stock
Food industryActive scenario01SignalSeveral dates and quality statuses coexist for the same item.02DecisionOrchestrate FEFO, blocks, customer priorities and transport horizon.03ProofSelected lot, rule and remaining shelf life visible.04Active systemERP05Active systemWMS
02 / 04Serve demand without losing short-dated lots
Critical componentActive scenario01SignalA low-value component blocks a high-contribution order.02DecisionReprioritise, transfer or expedite using load, cost and criticality.03ProofShutdown risk and preventive action documented.04Active systemERP05Active systemMES
03 / 04Protect production continuity
Multi-warehouse networkActive scenario01SignalOne site is overstocked while another approaches stockout.02DecisionCompare transfer, replenishment and demand shift on equal contribution.03ProofOption, lead time and total cost reconciled.04Active systemERP05Active systemWMS
04 / 04Rebalance without multiplying transfers
01 / 0402 / 0403 / 0404 / 04
01

More reliable promise

Availability relies on understandable stock states and horizons.

02

Less urgency

Stockout, excess and delay are detected early enough to compare several levers.

03

Better-used capital

Inventory is positioned according to its contribution to service and risk.

04

Explainable policy

Every threshold, segment and exception retains a rationale and review date.

Decision framework

Connect promise, responsibility and proof.

Optimisation is not about reducing everything. It requires distinguishing the role of each item, site and commitment.

Business logic

Decisions start with explicit rules.

Connected architecture

Clear responsibilities, from signal to proof.

ERP / planificationDefines policyPROTECH WMSEnsures field executionOMS / commerceCarries the promiseTMSCarries network lead timesBIEvaluates policy

Gaps to eliminate

What weakens day-to-day decisions.

Each gap connects an observable situation to a business consequence. Diagnosis then verifies frequency, impact and cause.

01

System ≠ physical

Variances, units and statuses make displayed quantity differ from reality.

Decisions based on fictional stock
02

Available ≠ promiseable

Stock may be blocked, reserved, non-compliant or outside the horizon.

Commitment impossible to keep
03

Local overload

Stock accumulates where demand or capacity cannot absorb it.

Extra cost, obsolescence and transfers
04

Incomplete traceability

Lot, quality and history do not always follow stock through to the promise.

Quality or compliance risk

Operational journey

A chain of decisions, not a stack of screens.

Each transition identifies the participant, responsible system and expected proof.

1

Receipt

Create qualified stock

Quantity, unit, lot, date, quality and location are controlled at entry.
Owner
WMS / quality
Proof
Physically receivable stock
2

Putaway

Position by role

Family, rotation, criticality, safety and physical constraints guide location.
Owner
WMS
Proof
Location and status confirmed
3

Reservation

Protect the right demand

Customer, channel, lot, priority and horizon determine what becomes committed.
Owner
OMS / ERP
Proof
Explained promiseable quantity
4

Execution

Make inventory live

Picking, consumption, transfer and return close the field loop.
Owner
WMS / MES
Proof
Coherent movement and balance
5

Control

Review the policy

Service, coverage, stockout, rotation and variance are analysed by segment.
Owner
ERP / BI / business
Proof
Replenishment or adjustment decision
6

Return

Reintegrate with care

Expected, received, inspected, refurbished and available remain separate.
Owner
WMS / quality
Proof
Disposition decision recorded

Decision lab

Change context. Follow what genuinely needs to happen.

These scenarios are illustrative: they show decision logic and responsibilities without claiming to simulate your actual outcomes.

E-commerce peak

Absorb the peak without permanently inflating stock

Signal

Demand rises on a family with long supplier lead time.

Decision

Combine targeted safety stock, channel allocation and fulfilment capacity.

Expected proof

Service, coverage and peak cost compared.

B‑AGILEdecision flowERP / planificationPROTECH WMSOMS / commerceTMSBI

Responsibility architecture

Unify the flow without pretending one system does everything.

The responsibilities below form a reference architecture to adapt to the existing IT landscape.

01

ERP / planification

Defines policy
Owns
Demand, lead times, parameters, supply and valuation
Publishes
Requirements and proposals
02

PROTECH WMS

Ensures field execution
Owns
Locations, lots, statuses, reservations and movements
Publishes
Physical truth and variances
03

OMS / commerce

Carries the promise
Owns
Channels, priorities, published availability and substitutions
Publishes
Committed demand
04

TMS

Carries network lead times
Owns
Transfers, inbound transport and delivery
Publishes
ETA and in-transit status
05

BI

Evaluates policy
Owns
Definitions, history and root-cause analysis
Publishes
Service, coverage, rotation and risks

Actionable cockpit

Inventory truth model

The same quantity must be readable by operational state: physical, blocked, reserved, in transit, under control or genuinely promiseable.

  • Inventory accuracySize confidence, control and count frequency
  • CoverageDetect stockout and excess by segment
  • Service rateArbitrate service, cost and policy
  • Blocked stockAccelerate quality and disposition decisions
Operational view · example
Inventory accuracy01Variance between system quantity and qualified count
Coverage02Mobilisable stock versus demand and lead time
Service rate03Demand fulfilled on agreed date and quantity
Blocked stock04Value and age by reason
System ≠ physicalAvailable ≠ promiseableLocal overload
No value is a customer measurement. Illustrative functional example.

Success conditions

What must be true before automation.

01

Data ownership

Item, unit, lot, location, status and hierarchy have a system and owner.

02

Segmented policy

Parameters distinguish criticality, variability, lead time, seasonality and service level.

03

Useful counting

Controls target risks and seek the cause of variance, not just its correction.

04

Measured decision

Each threshold or policy change is compared with a baseline and horizon.

Go further

Content to prepare a real discussion.

View all resources

Frequently asked questions

Decide with the right boundaries.

How is promiseable stock defined?

Start from physical stock, then apply reservations, blocks, lots, horizons, capacity and documented service rules.

Does WMS replace ERP?

No. WMS carries physical execution; ERP or planning generally carries demand, supply and management.

Can we optimise with imperfect inventory?

Yes on a pilot scope, provided confidence, controls and authorised decisions are visible.

Is advanced forecasting required?

Not necessarily. First make history, atypical events, lead times and responsibilities reliable, then select the right method.

How are lots and shelf-life handled?

With explicit statuses, horizons, FEFO/FIFO rules, customer criteria and quality controls.

What outcomes can be promised?

No generic percentage. The project defines a baseline, indicators, scope and observation period.

Your context first

Turn availability into a reliable promise.

Identify the decisions, data, responsibilities and pilot that will deliver observable value.

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