Library
SmartOps knows successful inventory optimization and planning comes from strong, reliable information. And that’s why we’ve created this online Library, filling it with the analyst research, case studies and white papers to help you make your most educated decisions.
SmartOps Customer Case Studies
Customers in every industry have benefited from the proven, powerful inventory optimization and planning capabilities of SmartOps. Learn a little more about SmartOps solutions from the people that use them, through our downloadable case studies.
- Bayer MaterialScience. “Making a Material Difference: The Story of How Bayer MaterialScience Supply Chain Became Lighter, Stronger and More Flexible.” Register/Login to Download
- Caterpillar. “Constructing Success: Making Complexity Work” Register/Login to Download
- Celestica. Industry: High Tech. Register/Login to Download
- ConAgra Foods. “ConAgra Foods Gains Efficiency, Saves Costs with SAP Enterprise Inventory Optimization.” Register/Login to Download
- Deere & Company. “The Two Principles That Drive Deer & Company’s Dramatic Turnaround in Shareholder Value Added (SVA).” Register/Login to Download
- Deere & Company. “Mowers, Utility Vehicles, Tractors, Aerators: The Story of How John Deere Cut $1 Billion in Inventory Has a Lot of Moving Parts.” Register/Login to Download
- Rohm and Haas. “Rohm and Haas Optimizing Inventory Management with SAP Software.” Register/Login to Download
- Unilever. “Right Time, Right Place: Inventory Optimization Success at Unilever.” Register/Login to Download
SmartOps Proof of Value (POV) Case Studies
What do customers truly learn in a Proof of Value project? Find out through six industry examples.
The six case examples described below summarize the results across a range of industries for recent customers who participated in a Proof of Value project.
Consumer Durables — Fortune 500
This manufacturer asked "how low can we go" in reducing inventory without losing a sale, given the high seasonality of their supply chain and demand uncertainty due to impulse purchasing. The SmartOps POV showed that a reduction of nearly 50% was possible and that their five-year cost-saving goals could be captured and exceeded over the next two years.
Consumer Packaged Goods — Fortune 500
This top-performing company -- enjoying nearly twice the inventory turns of its closest competitor -- used the SmartOps POV to see if there was any opportunity for improvement within one of their best-run supply chains. The results showed that they could reduce inventory by nearly 22% over the next six months for that supply chain.
Industrial Equipment — Fortune 500
This manufacturer, dedicated to Lean Manufacturing and Six Sigma practices, learned that it was possible to nearly double their total chain inventory turns, thereby reducing finished goods inventory by nearly 40%, by using SmartOps' holistic view of the supply chain to optimize the deployment of inventories. The POV also showed them a way to meet their goal of stabilizing order fulfillment to customer channels.
Pharmaceuticals — Global 500
This pharmaceuticals producer learned through a POV how they could reduce inventory for over-the-counter items by 30% in the next several months, by optimizing safety stocks and more closely aligning multistage stocking and production plans with demand.
Distribution —Fortune 500
This distributor of industrial products had dual goals of increasing inventory turns while improving service levels. The POV identified where they could achieve near-term inventory reductions ranging from 11% for distribution centers to 40% at some branches. The POV also revealed that at their current service level, 73% of the items could have lower average inventory targets.
High Tech — Fortune 1000
This networking equipment manufacturer was seeking to understand where to keep inventory (appropriate mix of components/parts and finished goods) and how much to keep on hand, in order to improve service levels. The POV uncovered opportunities to reduce inventory targets by as much as 35%, with the SmartOps solution accounting for the demand variability that was driving excess inventories.