Cost-to-Serve: The Missing Link Between Labor Data and Warehouse Profitability

Labor drives 50-70% of warehousing costs. Rising order variability makes that labor harder to plan and cost-to-serve harder to pin down. This new research from Supply Chain Insights, conducted in partnership with Easy Metrics, surveyed supply chain leaders to find out how companies actually measure, trust, and act on labor data.


New Research from Supply Chain Insights and Easy Metrics Reveals Why Most Warehouses Still Can’t See Their True Cost to Serve

Labor drives 50-70% of warehousing costs. Rising order variability makes that labor harder to plan and cost-to-serve harder to pin down. This new research from Supply Chain Insights, conducted in partnership with Easy Metrics, surveyed supply chain leaders to find out how companies actually measure, trust, and act on labor data.

The findings are candid. Only 25% of respondents actively manage labor. Fewer still call their cost-to-serve capabilities mature. Data trust is inconsistent. Leadership and warehouse teams often see performance very differently. This report breaks down where the gaps are, and what closes them.

In this report, you’ll learn:

  • Why cost-to-serve stays immature. See why three decades of labor management haven’t translated into mature cost-to-serve practices.
  • Where alignment breaks down. Compare how senior leaders and warehouse managers rate day-to-day performance, and understand the gap between them.
  • What the maturity model measures. Use a four-part framework covering measurement, use, insights, and interoperability to benchmark your own operation.
  • Why data trust and latency matter. Review the research on how long it takes warehouses to get labor data, and how much of that data teams actually trust.
  • Where AI fits, and where it doesn’t yet. Find out which use cases respondents rank highest for AI in labor management, and why fundamentals still come first.

Cost-to-serve isn’t optional anymore. Download the full report to see the complete maturity model, the data behind it, and seven recommendations for turning labor data into a profitability advantage.