Optimize Warehouse Labor Costs with Easy Metrics’ Cost to Serve Analytics
When each customer and workflow has its own set of costs, managing to averages leaves you blind. Operations need Cost to Serve to control performance and protect margin—at scale.
Get a handle on the cost of operational labor
Globalization and the digital era have radically shifted customer expectations. They expect: fast delivery of products and services that vary in type and volume, customization suited to their needs, and competitive pricing. Globally, warehouse operations spend $350B, and that amount is growing as complexity and demand grows. Operations leaders are faced with pressure to optimize and lower costs, while complexity drives costs higher. Although operations teams would like to lower costs, most do not know what their true costs should be, and fewer still understand their cost to serve for individual product types or customers.
The keys to understanding those costs are in an operation’s data. But the data is locked in multiple, unrelated systems. There is so much data that feeds into accurate cost to serve calculations, that spreadsheets can’t handle them. Attempts to pull partial cost to serve data into spreadsheets is a frustrating experience for operations analysts, is too slow and manual, inaccurate, and quickly becomes obsolete.
Operations leaders are facing a massive upheaval that is fundamentally changing how decisions about labor and facility investments are being made. Costs are spiraling due to: high turnover of employees, a tight labor market where demand outweighs supply, and facility and equipment investments that produce negative ROI. What’s needed is a clear understanding of cost to serve, so that operations leaders can make confident data-backed decisions, tackling their biggest cost savings initiatives by order of magnitude. Download the whitepaper to learn how to gain insights in four key areas so you can make informed decisions faster.
