Tl;dr: This case study demonstrates how predictive inventory analytics can transform manual reporting into a scalable strategic capability for manufacturing and distribution companies, reducing inventory analytics time by 75% for this client.
In manufacturing and distribution, knowing which products are at risk of stockouts or overstock can make the difference between lost revenue and efficient growth. Wells Lamont, the premier glove company founded in 1907 in Aberdeen, South Dakota, has built a reputation for durable, high-quality gloves across industrial, construction, and consumer markets. As the company scaled, inventory management became a critical lever to maintain operational efficiency while supporting growth.
Matt Crist, leading the planning team, recognized that the manual approach to inventory analytics was taking anywhere from 5 to 20 hours per week. It was inconsistent and resource-intensive. Without a structured system, spotting potential stock shortages and overstock risks was unpredictable, putting both service levels and cash efficiency at risk.
The Challenge
Wells Lamont’s leadership faced several inventory-related hurdles:
- Wide variation in time spent analyzing stock levels (5–20 hours/week)
- Difficulty identifying SKUs at risk of stockouts or overstock
- Limited ability to standardize inventory processes, reducing predictability
- Risk of tying up capital in excess inventory or missing sales on popular products
The company needed a method to standardize inventory analytics, reduce wasted effort, and gain clearer insight into stock risks.
A Smarter Inventory Analytics Strategy with Intuendi
Matt led the initiative to adopt Intuendi’s platform to transform inventory analytics into a proactive, data-driven process. With Intuendi, the team was able to:
- Reduce time spent on analytics to a predictable ~5.75 hours/week
- Gain insights into potential stock shortages before they became critical
- Identify overstock risks and adjust inventory allocation efficiently
- Standardize reporting and processes, making analytics repeatable and reliable
By embedding predictive analytics into daily workflows, Wells Lamont could focus on strategic decisions rather than manual data wrangling.
The Results
The shift to a structured, AI-supported inventory process delivered immediate benefits:
- Inventory analytics time reduced by 75% (22.5 → 5.75 hours/week)
- Improved visibility into stockout and overstock risk
- Streamlined, repeatable process allowing the team to act proactively
This approach allowed Wells Lamont to protect cash flow, optimize inventory allocation, and maintain service levels without adding headcount.
The Advantage Gained
Through forward-thinking leadership and strategic adoption of Intuendi, Wells Lamont transformed inventory analytics from a labor-intensive task into a strategic tool. The company gained predictable, actionable insights, enabling the team to prevent stockouts, limit overstock, and make more informed inventory decisions, all while freeing up time for higher-value planning activities.
