Wholesale Distribution Supply Chain Planning Software to Optimize Inventory Without Compromising Service

Range-based probabilistic AI for long-tail demand forecasting, multi-echelon inventory optimization, and network rebalancing deliver higher service with less inventory across large, dispersed B2B distribution networks, even when demand is intermittent, margins are tight, and the cost of a stockout is high.

In Distribution, Your Margin Is Trapped in Inventory — Most of It in the Long Tail.

In wholesale distribution, 15–30 cents of every revenue dollar is tied up in inventory and the cost of carrying it. Most SKUs move slowly or intermittently, so deterministic forecasting treats lumpy demand as a stable average — systematically overstocking slow movers while strategic items run short. Add long, unreliable supplier lead times, SKU proliferation, and "Amazon-standard" service expectations, and traditional planning breaks fast: stockouts, expediting, and working capital all climb at once. ToolsGroup’s wholesale distribution supply chain planning software closes that gap with range-based probabilistic forecasting built for the long tail and decision intelligence that rebalances inventory across your entire network — continuously steering service, cost, and margin toward your financial targets to deliver higher service with less inventory.

• 99%+ Service levels
• Up to 30% Inventory reduction
• 50% Fewer stockouts
• Up to 60% Less expediting

Trusted by Wholesale Distributors

Across electrical & electronics, packaging, industrial & MRO, and office products

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Why Traditional Planning Breaks in Distribution

When demand is intermittent and the consequences of failure are huge, traditional planning breaks fast — leaving teams firefighting while working capital, expediting, and lost sales all climb at once.

Challenge 01: Working capital & margin erosion

Slow movers get overstocked while high-demand items run out — so working capital is used inefficiently and margins erode from both directions.

Challenge 02: Poor forecast accuracy on the long tail

Intermittent, low-volume SKUs defy deterministic forecasting, so inventory gets held as insurance — tying up cash and hitting margin.

Challenge 03: Unreliable supplier lead times

Suppliers deliver inconsistently, with long, unreliable, and shifting lead times that make every stock position fragile.

Challenge 04: Rising "Amazon-standard" expectations

Customers demand faster lead times and higher fill rates across an ever more complex fulfillment network — while online rivals and price transparency squeeze margin.

Challenge 05: Manual, reactive planning

Disjointed systems and experience-and-guesswork planning keep teams firefighting, with fixed days-of-coverage stock and tribal knowledge walking out the door.

Long-tail probabilistic forecasting

Range-based probabilistic demand forecasting optimized for long-tail, intermittent, and highly seasonal demand — predicting what’s predictable and preparing for the rest without ballooning safety stock.

The forecasting problem

Why Deterministic Forecasting Fails in Distribution

Traditional forecasting is deterministic — a single number per SKU, with stock set on fixed "days of coverage." That works for steady, high-volume demand. In distribution, most SKUs are nothing like that.

Probabilistic planning models the full range of demand — including the intermittent long tail — instead of one fragile number, setting inventory to hit explicit service targets at the lowest total cost. It's the foundation ToolsGroup builds on, across multi-echelon inventory optimization, network rebalancing, and agentic AI.

Featured analyst recognition

Recognized in the Gartner Magic Quadrant for Supply Chain Planning

In the Gartner® Magic Quadrant™ for Supply Chain Planning Solutions, ToolsGroup is noted for the strength of its probabilistic approach to managing demand and supply uncertainty — the core challenge facing large, dispersed B2B distribution networks with long-tail SKU portfolios.

What is wholesale distribution supply chain planning software?

Wholesale distribution planning software forecasts demand, optimizes inventory, and automates replenishment across large, dispersed distribution networks. Unlike generic ERP planning, it uses range-based probabilistic forecasting built for long-tail and intermittent demand — driving to explicit service targets at the lowest total inventory.

How does it forecast long-tail and intermittent demand?

Range-based probabilistic forecasting models the full distribution of possible demand rather than a single average, so it predicts what’s predictable and prepares for the rest — setting policies for slow-moving, intermittent SKUs without ballooning safety stock.

What is multi-echelon inventory optimization (MEIO) and network rebalancing?

MEIO optimizes inventory across every tier — DCs, branches, and regional networks — as one system instead of silos. Network rebalancing then moves stock to where it’s needed, serving more demand from existing inventory before buying more.