What Do it Best Does

Do it Best Corp. is a member-owned hardware, lumber, and building materials cooperative headquartered in Fort Wayne, Indiana. Founded in 1945, it serves thousands of independent retailers across the United States and over 50 countries. The company operates as a wholesale distributor, providing its member-owners with a vast inventory of products, marketing support, and operational services. Its core function is to aggregate purchasing power and streamline logistics, enabling small, locally-owned hardware stores to compete effectively against large national chains. With a workforce in the 1,001-5,000 range, Do it Best manages a complex supply chain involving seasonal goods, bulky items, and diverse regional demand patterns through its network of distribution centers.

Why AI Matters at This Scale

For a mid-market cooperative like Do it Best, operating efficiency is paramount. Its business model hinges on minimizing costs in the wholesale channel to maximize value for its member-owners. At its current scale, manual processes and traditional forecasting methods struggle with the complexity of servicing a fragmented network. AI presents a transformative lever to optimize this entire system. It can process vast amounts of data from member sales, weather, local economics, and inventory turns to uncover patterns invisible to human planners. This isn't about futuristic applications; it's about using machine learning to solve fundamental business problems—reducing capital tied up in inventory, improving service levels, and enhancing member profitability—which directly strengthens the cooperative's value proposition and competitive moat.

Concrete AI Opportunities with ROI Framing

1. Hyper-local Demand Forecasting: Implementing machine learning models that synthesize point-of-sale data from members, regional economic indicators, and even local weather forecasts can dramatically improve forecast accuracy. This reduces costly expedited freight for stockouts and minimizes deep discounting to clear seasonal overstock. A 10-20% reduction in inventory carrying costs across a multi-billion dollar inventory represents a direct, substantial contribution to the bottom line and member rebates.

2. AI-Optimized Warehouse Operations: In distribution centers, AI and computer vision can optimize warehouse slotting, dynamically route pickers, and plan optimal truck loading sequences. This increases throughput and reduces labor hours, which are a significant expense. For a company with several large DCs, even a 5-7% gain in operational efficiency translates to millions in annual savings and faster order turnaround for members.

3. Personalized Member Insights Portal: An AI-driven dashboard for members could analyze their individual sales data against peer performance and local market trends. It could automatically recommend product assortments, promotional strategies, and pricing adjustments. This service increases member loyalty and stickiness, driving higher purchase volumes through the co-op. The ROI is in strengthened network effects and increased share of wallet.

Deployment Risks Specific to This Size Band

Do it Best operates in a challenging middle ground: large enough to have complex data but often without the vast IT budgets and dedicated AI teams of Fortune 500 companies. Key risks include integration complexity with legacy ERP and warehouse management systems, which can make real-time data access difficult. Data quality and standardization across a decentralized member base is a persistent hurdle. There's also a talent gap; attracting and retaining data scientists is difficult in the Fort Wayne market, making strategic partnerships with AI SaaS vendors crucial. Finally, the cooperative governance model means new technology investments must demonstrate clear, equitable value to the member-owners, requiring careful change management and proof-of-concept pilots to build consensus before full-scale rollout.