Services

Data Analytics · Inventory

Inventory Optimization Analytics

Set inventory policy from demand, lead time, variability, and service requirements. Manufacturers need inventory decisions that account for demand variability, supplier lead time, production constraints, order policy, location, and customer commitments. We build analytics that make those assumptions visible and support controlled stocking decisions.

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01

The Problem

Inventory policy is being set by habit instead of measurable operating conditions.

Analytics problems begin when a dashboard is built before records, definitions, timing, lineage, and accountability have been reconciled across the operation.

01

What leaders see

Reports disagree about current conditions.

Teams debate inventory, production, margin, delivery, and quality numbers instead of acting on them.

02

What is actually happening

Measures inherit unresolved record conflicts.

Sources, identifiers, definitions, refresh timing, adjustments, and ownership differ across systems and teams.

03

What gets worse

Faster reporting accelerates the wrong answer.

More dashboards spread inconsistent measures and make exception ownership harder to establish.

02

What Changes

What Inventory Optimization Analytics includes.

Manufacturers need inventory decisions that account for demand variability, supplier lead time, production constraints, order policy, location, and customer commitments. We build analytics that make those assumptions visible and support controlled stocking decisions.

01

Safety Stock Optimization

Calculate optimal safety stock for every SKU based on demand variability, lead time variability, and target service level. Replace blanket formulas with item-specific calculations that balance cost and availability.

02

Reorder Point Calculation

Dynamic reorder points that update as demand patterns and lead times change. No more static reorder points set during ERP implementation that nobody has reviewed since.

03

ABC/XYZ Classification

Multi-dimensional inventory classification by revenue impact (ABC) and demand predictability (XYZ). Different inventory policies for different segments -- high-value/predictable items managed differently than low-value/erratic ones.

04

Excess & Obsolete Analysis

Identify slow-moving, excess, and obsolete inventory with aging analysis, usage trend tracking, and disposition recommendations. Quantify the carrying cost of dead stock.

05

Multi-Location Optimization

Optimize inventory placement across warehouses and distribution points. Balance stock where it's needed based on demand geography, not just where it's convenient to store.

06

Service Level Modeling

Model the trade-off between inventory investment and service level. Show leadership exactly what it costs to go from 95% to 98% fill rate -- and where the diminishing returns start.

03

How It Fits Your Operations

How Inventory Optimization Analytics fits your operation.

Operational AnalyticsWhich decision the view supports, which records establish it, and how disagreement or missing data becomes visible.
Governance dependencyMeasures need defined ownership, timing, lineage, reconciliation, and access before dashboards can become a basis for operating decisions.
Operating records to reconcile
demand and orders
materials and inventory
production and capacity
quality
shipments and commitments

What must be defined before engineering begins

  • What the business needs to change and why.
  • Which systems, records, risks, and readiness gaps shape the work.
  • What should be built, how it fits the architecture, and in what order.

Related Services and Planning

What the operating problem may require next.

Follow the dependencies behind this service instead of treating it as an isolated project.

Start With the Operating Problem

Define the smallest sound response and delivery sequence.

Metrotechs determines what the operation actually requires before selecting technology. When a structured assessment is warranted, Launchpad turns evidence into priorities, risks, architecture, and an implementation Roadmap.

Discuss the Operating ProblemExplore Launchpad
Metrotechs designs, builds, integrates, and supports the approved solution.
Launchpad is available when the engagement needs assessment evidence, a Roadmap, and ongoing delivery governance.

04

Delivery sequence

How Metrotechs delivers Inventory Optimization Analytics.

Manufacturers need inventory decisions that account for demand variability, supplier lead time, production constraints, order policy, location, and customer commitments. We build.

01

Inventory Data Analysis

Analyze current inventory levels, demand patterns, lead times, and service level performance across all SKUs and locations. Identify where investment is misallocated.

02

Policy Design

Design inventory policies by segment -- safety stock formulas, reorder points, review frequencies, and replenishment methods. Align with operations on service level targets.

03

Optimization Modeling

Run optimization models to calculate target inventory levels. Compare current vs. optimized inventory investment and projected service level impact.

04

Implementation & Monitoring

Update ERP planning parameters with optimized values. Deploy monitoring dashboards tracking inventory turns, service levels, and excess stock. Monthly reviews to maintain optimization.

05

FAQ

Questions that usually decide the scope.

Straight answers to what operators ask before committing budget to this work.

Typical results: 15-30% reduction in total inventory investment while maintaining or improving service levels. The biggest wins come from right-sizing safety stock on high-value items and eliminating excess on slow-movers.