Ask any supply chain consultant what separates top-performing companies from the rest, and you'll get a consistent answer: disciplined execution of proven practices. Regular parameter reviews. Exception-based management. Active dead stock programs. The playbook is well-documented.
Yet when mid-market companies try to implement these practices, they consistently fall short. Not because the practices don't work—they do. But because every one of these practices requires something most mid-market companies don't have: dedicated analytical capacity.
The data on this capability gap is striking—and it explains why inventory performance at mid-market companies continues to lag despite having access to the same tools as large enterprises.
The Four Practices That Work
Research from Netstock's benchmark studies consistently identifies four practices that distinguish top performers:
- Regular parameter reviews — Recalculating safety stock, reorder points, and forecasting parameters based on actual demand variability
- Exception-based focus — Concentrating attention on the 20% of items driving 80% of the problem
- Active dead stock management — Formal processes for identifying, escalating, and liquidating slow-moving inventory
- Dedicated analytical capacity — Resources focused on inventory optimization as a primary responsibility, not a side task
These aren't secrets. They're in every supply chain textbook and consulting deck. The question is: why can't mid-market companies execute them?
In smaller-sized firms, the amount of work available for this specialist is simply too low and he will get bored and leave the company.— EyeOn White Paper on Demand Planning Organizations
1. Regular Parameter Reviews
What top performers do: Quarterly (or more frequent) reviews of safety stock levels, reorder points, and forecasting parameters. Dynamic adjustment based on changing demand patterns and supplier reliability.
What mid-market companies actually do: Set parameters once during ERP implementation and rarely touch them again.
The Static Parameter Problem
According to Netstock: "ERPs have static safety stock levels for items. These systems ignore demand volatility and supply unreliability when calculating safety stock."
The data on mid-market technology adoption is sobering:
- •82% of small businesses rely on manual processes for inventory management
- •67% of supply chain managers use Excel spreadsheets
- •43% of small businesses don't track inventory at all or use outdated manual systems
- •Only 22% use dedicated inventory management software
Even companies with good ERP systems face the same challenge: someone needs to actually review and update the parameters. That requires time, analytical skills, and dedicated focus—resources that mid-market operations teams simply don't have available.
2. Exception-Based Focus
What top performers do: Automated alerts and AI-driven prioritization that surfaces the items requiring attention. Focus energy on exceptions rather than reviewing every SKU equally.
What mid-market companies actually do: Manual review processes that either try to cover everything (and cover nothing well) or operate on autopilot until problems become crises.
| SMB Planning Behavior | 2024 | 2025 |
|---|---|---|
| Insufficient forward planning | 56% | 62% |
| "Autopilot" ordering despite changing conditions | 20% | 27% |
| Disciplined, proactive planning | 30% | 22% |
Source: Netstock 2024-2025 Benchmark Reports. Data covers 2,400+ SMBs.
The trend is moving in the wrong direction. More companies are falling into "autopilot" mode, and fewer are maintaining the disciplined, exception-based approach that drives results.
3. Active Dead Stock Management
What top performers do: Formal programs for identifying aging inventory early, escalation protocols, and established channels for liquidation or redistribution.
What mid-market companies actually do: Wait until inventory becomes a problem, then run promotions or write it off.
The Cost of Dead Stock
Dead inventory costs an average of 30% above its value to maintain, plus another 15% in opportunity costs. For a mid-market company with $15M in inventory and 10% dead stock, that's $675,000 per year in pure waste.
The Netstock data shows this is getting worse, not better:
- ↑Companies with dead stock >10% of inventory: 12% → 17% (42% increase)
- ↑Companies holding 20%+ excess stock: 48% → 55%
- •Only 29% use warehouse redistribution to manage excess
- •69% rely solely on promotions to move excess inventory
Active dead stock management requires continuous monitoring, early intervention, and disciplined execution—exactly the capabilities that require dedicated analytical resources.
4. Dedicated Analytical Capacity
What top performers do: Full demand planning teams with data scientists, dedicated inventory analysts, and continuous improvement resources.
What mid-market companies actually do: Assign inventory optimization as a side task to operations staff already stretched thin by day-to-day demands.
The Core Problem
As AWS notes: "We often hear from small and medium businesses that their supply chains face challenges such as demand planning, forecasting and a widening supply chain talent gap. This leaves them exposed to challenges that larger enterprises can more easily address through the sheer size of their companies."
The research is consistent across sources:
McKinsey on SME talent gaps: "SMEs often face challenges in attracting the right talent" for procurement and supply chain roles. "Procurement managers at SMEs spend most of their time dealing with supply disruptions" rather than strategic optimization.
Deloitte/McKinsey on skills shortage: While over 90% of industrial companies cite digital as "critical" to competitiveness, fewer than 30% say their workforce is prepared. Skills gaps in "data analytics, AI operations, and cross-functional supply chain fluency" are the top barrier.
Industry reality: "SMBs don't have dedicated data science teams or IT departments. They need solutions that work out of the box without requiring high-level expertise to implement and maintain."
The Real Gap
The capability gap between enterprises and mid-market companies isn't about tools or technology. It's about capacity. Every best practice requires someone to do the work—and mid-market companies don't have that someone.
| Practice | Enterprise Approach | Mid-Market Reality |
|---|---|---|
| Parameter Reviews | Quarterly reviews with dedicated analysts | Static settings, 67% use Excel |
| Exception Focus | Automated alerts, AI-driven prioritization | Manual review, 62% insufficient planning |
| Dead Stock | Formal programs, redistribution networks | 69% rely on promotions only |
| Analytical Capacity | Full demand planning teams | Zero dedicated staff—it's a side task |
The result is predictable: mid-market companies pay 20-30% higher carrying costs than enterprises in the same industries. They hold more excess inventory, write off more dead stock, and lose more to stockouts.
The Opportunity
The capability gap isn't destiny. Mid-market companies don't need to build enterprise-scale teams to get enterprise-level results. They need focused analytical capacity—whether built internally through strategic hires and training, or accessed externally through specialized partners.
The practices are proven. The gap is clear. The question is how to close it.
Sources
- Netstock 2025 Supply Chain Planning Benchmark Report
- Netstock 2024 Inventory Management Benchmark Report
- Avancim Small Business Inventory Management Study (2,500+ SMBs surveyed)
- McKinsey: How Medium-Size Enterprises Can Better Manage Sourcing
- AWS: SMB Supply Chain Management Challenges
- Supply Chain Dive: BluJay/AdelanteSCM Survey on Excel Usage
- EyeOn White Paper: Demand Planning Organization
- Forbes: Bridging the Industrial Talent and Technology Gap (citing Deloitte/McKinsey)
Founder, Précis Flux
Industrial executive with a strong background in engineering and applied mathematics, and 20 years of experience across the industrial value chain—from R&D to P&L management. Having worked on inventory optimization and demand variability analysis in his executive roles, Gunnar founded Précis Flux to help mid-market companies release trapped working capital through data-driven methods.
Close the capability gap
You don't need to build an enterprise-scale team to get enterprise-level inventory results. Our Working Capital Calculator can help you estimate the opportunity. Or, let's discuss how focused analytical support could help your organization execute the practices that drive results.