Inventory Optimization
Inventory Optimization Software Built on Statistical Segmentation, Not Guesswork
TranslytiX segments every SKU into a statistically-defined category — by volume, variability, peakedness, and skew — and applies the safety-stock method that fits that category. Multi-echelon optimization, automated hub replenishment, and inventory prebuild run on top, all with planner override and full governance.
- inventory reduction
- 5–10%
- service level (OTIF)
- Improved
- ageing & expiry risk
- Reduced
What is inventory optimization software?
Inventory optimization software determines how much stock to hold and where to position it so a business hits its service-level targets at the lowest total cost — replacing static safety-stock norms and spreadsheet formulas that quietly inflate working capital.
TranslytiX starts from statistical SKU segmentation: every item is classified by demand volume, coefficient of variation, peakedness, skewness, and zero-demand frequency into one of six categories — from Stable & High Movers to Obsolete/Dormant — each with its own safety-stock formula. Multi-Echelon Inventory Optimization (MEIO) then sets safety stock and Days-of-Supply targets across every node simultaneously, rather than one warehouse at a time, and an Inventory Prebuild module pre-positions stock ahead of seasonal peaks and campaigns. Every recommendation is planner-overridable and logged.
How does Translytics do inventory optimization?
Multi-Echelon Inventory Optimization (MEIO)
OR-based safety stock and DOS targets calculated across all nodes at once, with system recommendations planners can override.
Statistical SKU segmentation
Six data-driven categories — by volume, variability, peakedness, and skew — each mapped to a tailored safety-stock formula and planning strategy (MTS, MTO, VMI, consignment).
Inventory Prebuild module
Profiles forecasted demand to flag high-growth or campaign-critical SKUs, then generates a plant/product build calendar with readiness tracking before the plan locks.
Automated hub replenishment
Calculates replenishment quantities from plant to central warehouse to regional depot to distributor, using live inventory position, dynamic safety stock, and MOQ rules.
Inventory visibility & KPIs
Centralized view of total inventory, DOS, in-transit and damaged stock, ageing, and expiry-risk projections, with rebalancing recommendations across nodes.
Alerts, action boards & governance
Exception-driven workflows — excess inventory control tower, expiry alerts, slow-mover flags — assigned and tracked against named planners.
Why static safety stock norms fail — and what replaces them
Most inventory programs set a safety-stock rule once and revisit it annually, which is why reductions rarely hold. TranslytiX treats safety stock as a live, per-SKU calculation:
- Category-specific formulas — a Stable High Mover, an Event-Driven Lumpy SKU, and a Dormant item each get a different safety-stock method, instead of one blanket days-of-cover rule.
- Dynamic, not annual — safety stock recalculates from live demand variability and lead time, not a policy set once a year.
- Network-level thinking — MEIO sets targets across plant, hub, and depot together, so protection isn’t duplicated at every node.
- Ownership built in — every recommendation is tracked to a named planner with an override log, so accountability doesn’t depend on a spreadsheet.
Built for the operating complexity of real supply chains: TranslytiX (TX) plugs in above the ERP you already run — SAP, Oracle, ERPNext, or Tally — with no rip-and-replace, and is deployed in outcome-based 90-day cycles.
How to choose inventory optimization software: 6 questions to ask
Inventory software promises lower stock and better service at the same time. These questions show whether a tool can actually deliver both on your network.
1.Does it optimize across echelons, or one location at a time?
Setting safety stock separately at the plant, warehouse and depot double-counts buffers. Multi-echelon optimization decides where in the network each unit of stock does the most good.
2.Does safety stock reflect both demand and lead-time variability?
Many tools size buffers on demand variability alone. Supplier and transit lead times that swing by days are often the bigger driver of stockouts and excess.
3.How are SKUs segmented?
ABC by value is not enough. Look for segmentation by demand behaviour (variability, intermittency, lifecycle) so each group gets its own policy rather than one rule for all.
4.Are the outputs actions or reports?
Planners need replenishment orders, transfers and prebuild recommendations they can approve, not another dashboard showing what went wrong last month.
5.Can it see ageing and expiry risk?
Stock that is technically available but ageing or near expiry is a cost waiting to happen. The software should flag it early and route it before it becomes a write-off.
6.Will it show the inventory-versus-service trade-off on your data?
Before committing, ask to see what service level each inventory budget buys, SKU by SKU, using your own history. That curve is the business case.
Comparing several vendors? Read our full guide to evaluating supply chain planning software.
Implementation: what to expect
TranslytiX is deployed in outcome-based 90-day cycles on top of your existing systems.
1. Connect and baseline
TranslytiX reads your data from the ERP you already run (SAP, Oracle, ERPNext or Tally) and we measure today's inventory value, service level (OTIF) and ageing, so every later result is compared with your own starting point.
2. Configure and validate
Your business rules and constraints are set up, and results are back-tested against your own history, so planners can see the difference before anything goes live.
3. Go live with your planners
Planners work from TranslytiX recommendations, with overrides logged and explained, and no rip-and-replace of existing systems.
4. Measure and expand
At the end of the cycle we compare inventory value, service level (OTIF) and ageing with the baseline, then extend to further sites, products or modules.
Proven in production, not in slides
Petrochemical PR Automation & Safety Stock Optimization
AI-driven PR automation with optimized safety stocks reduced stockouts for a leading petrochemical corporation.
Read the success storyEnterprise Supply Chain Transformation
Enterprise-wide AI analytics optimized network design, inventory, and service levels across regions.
Read the success storyQuestions, Answered
Inventory optimization software determines the right amount of stock to hold — and where to hold it — so a business meets service-level targets at the lowest total cost. TranslytiX starts from statistical segmentation: every SKU is classified by demand volume, variability (coefficient of variation), peakedness, skewness, and zero-demand frequency into one of six categories, each with its own safety-stock formula. Multi-Echelon Inventory Optimization (MEIO) then sets safety stock and Days-of-Supply targets across the whole network — plant, hub, and depot — simultaneously rather than node by node. Company-reported results include 5–10% inventory reduction with improved OTIF service levels, validated across footwear, FMCG, FMCD, industrial, chemicals, and B2B engineering manufacturers.
Multi-echelon inventory optimization sets safety stock and inventory targets across every stage of the network — plants, central warehouses (hubs), regional depots, and distributors — at the same time, instead of optimizing each location independently. TranslytiX’s MEIO engine is OR-based: it calculates safety stock and Days-of-Supply targets per SKU at every node simultaneously, generating system recommendations that planners can review and override. Because it treats the network as one system rather than isolated warehouses, it avoids the duplicated safety stock that single-echelon planning creates at every node "just in case."
TranslytiX classifies every SKU into one of six categories using statistical thresholds on demand volume, coefficient of variation, peakedness, and skewness: Stable & High Movers, Predictable Medium Movers, Strategic High-Value SKUs, Event-Driven Lumpy SKUs, Obsolete/Dormant SKUs, and a Moderate/Manual-Review bucket for items with no strong pattern. Each category has a distinct safety-stock formula — for example, high movers use a lead-time-scaled average demand calculation, while event-driven SKUs use a service-level z-score applied to demand variability. This means a fast-moving, stable product and a spiky, event-driven product are never governed by the same blanket rule.
Inventory Prebuild is a TranslytiX module that identifies SKUs needing early stock build-up ahead of seasonal peaks or planned campaigns. It profiles forecasted demand to flag high-growth or campaign-critical items, prioritizes them by lead time, capacity, and risk, and generates a plant/product-wise build calendar with recommended quantities and start dates. Readiness is tracked against the sales calendar with alerting dashboards, and once confirmed, the prebuild plan locks and flows directly into production and supply planning. Reported benefits include fewer stockouts during peak events, better S&OP alignment, and fewer emergency production runs or airfreight costs.
See your own data make better decisions
Book a personalized demo and see how decision intelligence changes inventory optimization — on top of the systems you already run.