Case Studies
In this case study, we showcase how we worked with one retail location operated by The Northwest Company to improve inventory, freight, and operational efficiency.
The Northwest Company
One retail location operated by The Northwest Company in Northern Ontario was experiencing consistently high labour and freight costs caused by inefficient delivery scheduling, inconsistent staffing allocation, and poor SKU management. The operational structure and store layout were similar to a Safeway-style grocery and general merchandise environment, requiring efficient inventory movement across multiple product categories while serving a remote community market.
Inventory levels were not properly aligned with customer demand patterns, resulting in excess backroom stock, inefficient replenishment, and unnecessary handling costs. The store was carrying too many overlapping SKUs and excess sizing variations of similar products, limiting its ability to offer a broader and more effective product mix to customers.
Freight operations were also becoming increasingly expensive due to poorly coordinated deliveries and underutilized pallet space. Since the store relied on multiple suppliers and long-distance freight logistics common in Northern Ontario operations, inefficient LTL (Less-Than-Truckload) shipments and inconsistent delivery scheduling were significantly increasing operational costs.
These inefficiencies affected labour productivity as well. Staff spent excessive time organizing overstock, moving inventory between storage areas, restocking shelves repeatedly, and handling inefficient pallet picking processes. Backroom congestion and inconsistent inventory flow further increased operational pressure on staff and management.
The same operational challenges and SKU inefficiencies later became one of the key inspirations behind the inventory analytics and operational optimization systems being developed through UMSHAi. By applying the same SKU management principles, freight optimization strategies, and demand forecasting methods through technology-driven analytics tools, UMSHAi focuses on helping businesses better understand inventory movement, reduce operational waste, improve ordering accuracy, and optimize profitability through data-backed decision-making.
As a result, the store faced:
High labour costs
Increased freight expenses
Excess inventory handling
Poor SKU efficiency
Lower pallet utilization
Reduced operational productivity
Limited product variety
The business required a more data-driven inventory and operations strategy that could improve efficiency while supporting long-term profitability growth.
Solution
To address these operational challenges, I analyzed purchasing trends, freight schedules, SKU performance, and customer demand patterns specific to the Northern Ontario retail environment. Using EOQ (Economic Order Quantity) principles, estimated delivery timelines, and demand forecasting based on local shopping behaviour, pay periods, and seasonal demand fluctuations, I restructured the store’s inventory and ordering strategy.
A major focus was reducing unnecessary duplicate SKUs and excess product sizing variations while increasing the diversity of products available to customers. This created a more streamlined inventory flow and improved product assortment without unnecessarily increasing inventory carrying costs.
The operational logic and SKU optimization strategies used during this process later became foundational concepts behind UMSHAi’s retail analytics and inventory intelligence systems. Through UMSHAi, these same methods are being expanded into scalable digital tools capable of analyzing sales trends, forecasting demand patterns, optimizing replenishment strategies, identifying underperforming SKUs, and improving supplier and freight efficiency for retail operations.
Freight operations were optimized by consolidating deliveries across multiple suppliers and improving pallet utilization at receiving and docking stations. By scheduling fuller and more efficient shipments, the store significantly reduced LTL freight inefficiencies and improved overall delivery cost management — an especially important factor for remote Northern Ontario operations where transportation costs have a major impact on profitability.
The operational improvements also reduced labour inefficiencies. With lower excess inventory and improved inventory organization, backroom storage became easier to manage and shelf replenishment required fewer handling attempts. Reduced overstock and simplified pallet movement lowered the amount of labour required for picking, restocking, and inventory management tasks.
As a result of these combined improvements
Shrinkage was reduced
Product variety increased
Labour efficiency improved
Customer service levels improved
Freight costs decreased through better shipment consolidation
Inventory turnover became more streamlined
Overall store profitability increased by 13% within the same year
This project demonstrated how operational analytics, inventory optimization, freight consolidation, and demand forecasting can significantly improve retail efficiency and profitability, particularly within complex remote supply chain environments such as Northern Ontario — and how those same principles are now being applied through UMSHAi to help modern businesses improve operational performance through technology-driven analytics solutions.
