Data Analytics · Inventory

Carry less inventory and stock out less \u2014 at the same time.

Most manufacturers solve stockouts by adding more safety stock, and solve excess inventory by running promotions. Neither addresses the root cause. Analytics-driven inventory optimization calculates the right stock levels for every SKU at every location based on actual demand variability and service level targets.

Begin AssessmentAll Services
The Problem

Inventory Levels Set by Gut Feel and Fear of Stockouts

Safety stock set by a blanket formula or "whatever the buyer thinks is enough" \u2014 not by demand variability analysis
Reorder points that haven\u2019t been updated since the items were set up in the ERP
ABC classification done once and never maintained \u2014 C items getting the same attention as A items
Excess inventory and stockouts happening simultaneously because different SKUs have different demand patterns
What We Deliver

Service Scope

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 \u2014 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\u2019s needed based on demand geography, not just where it\u2019s 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 \u2014 and where the diminishing returns start.

How We Work

Engagement Process

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 \u2014 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.

Common Questions

Frequently Asked Questions

Work with Metrotechs

Every engagement starts with an assessment.

Not a proposal. Not a sales call. We tell you what we find, not what you want to hear. The Launchpad assessment maps your operation before any software work begins.

Begin AssessmentTalk to the team