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Home » AI in Distribution » How Better Intelligence Can Cut the Cost of Complexity for Distributors

Date

  • Published on: March 27, 2025

Author

  • Picture of Chandra Subramanian Chandra Subramanian

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AI in Distribution

How Better Intelligence Can Cut the Cost of Complexity for Distributors

Distributors are working harder than ever to meet customer demands: expanding product lines and selling across multiple channels. But with growth comes complexity, and without the right intelligence, that complexity can erode margins and decrease operational efficiency. 

Add in the volatility of the market and the need for agility has never been greater. 

Without the right intelligence, distributors could see: 

  • Higher carrying costs: The more SKUs a distributor carries, the more inventory is tied up in capital they could use elsewhere. Distributors need to make sure they are optimizing that inventory to minimize excess stock and lower warehousing costs. 
  • Warehouse congestion: Distributors often have to invest in more warehouse space, which comes with cost and operational challenges.  
  • Fragmented logistics: Managing multiple sales channels can result in split shipments, multiple freight carriers and increased handling costs. It may also complicate inventory placement across a distributor’s network. 
  • Greater complexity in order fulfillment: Multiple order types – such as small parcels and bulk shipments – require more complex fulfillment processes, which can increase labor and technology investments. It may also increase the risk of errors and slow down order processing. 
  • Disconnected systems across channels: It becomes harder to maintain visibility across channels when data doesn’t sync. That can lead to lost sales or excess inventory costs. It can also make it harder to accurately forecast demand. 
  • More complex customer service needs: Customers want seamless support across all channels, which requires the right teams and technologies. 

As the complexity of a distributor’s operations grows, the potential for disruption also grows. A small miscalculation – like overestimating demand for one product line – can cascade into higher carrying costs, lower inventory turnover and missed sales.  

Current approaches to planning and execution take a waterfall approach to business planning: Plan > Buy > Distribute > Sell. The reality on the ground, however, is different. Business is dynamic, rapidly changing and full of unplanned events. A customer may randomly cancel an order, or a supplier may delay a consignment. In addition, factors like tariffs or interest rates can negatively affect the business.  

Distributors need enhanced intelligence about their customers, suppliers and products to make informed decisions.  

The good news is that many distributors already have massive amounts of data flowing in from sales, suppliers and logistics networks. They also have access to external data. But data alone isn’t enough. What matters is how quickly and accurately they can leverage insights from the data to rapidly make critical decisions.  

AI will help distributors answer questions such as: 

  • What external factors are affecting my demand?  
  • What is the impact of a supplier delay on my customer service levels? 
  • Can I reallocate inventory from another location to fill unexpected demand from an important customer?  
  • What is the risk in my forecast and how much inventory do I need to stock to manage that risk? 
  • What demand should I plan for the launch of a new product?  

This shift from a static to a dynamic approach allows distributors to anticipate changes before they happen, optimize inventory positioning and prevent costly inefficiencies. 

For years, distributors have relied on traditional methods that weren’t built for today’s level of complexity. The result? Excess stock in some areas, stockouts in others and a reactive approach to managing supply chains. AI and machine learning change that, bringing real-time intelligence that helps distributors forecast demand, optimize inventory and avoid costly miscalculations.  

The returns speak for themselves. For example, an industrial distributor we worked with decided to optimize their safety and security product category. Using AI and ML-based tools, they saw a 40% reduction in back orders and 5% reduction in overall inventory. That resulted in happier customers and lower costs. 

Distributors need to make sure products are available where their customers need them most – without increasing inefficiencies and costs due to operational, logistic and procurement constraints. 

Those who continue relying on outdated, rules-based systems to do this risk falling behind in an increasingly unpredictable market. 

Distributors who embrace AI-powered intelligence will stay agile and resilient in a rapidly changing market. Will your business be ahead of the curve or playing catch-up? 

Chandra Subramanian
Chandra Subramanian

Chandra Subramanian is the CEO of Deda AI North America, a seasoned technology executive, and an active investor in early-stage startups. At Deda AI, he focuses on democratizing decision intelligence for distributors and manufacturers —bridging human expertise with machine learning to enable smarter, faster enterprise decisions. With over 25 years of experience at the intersection of AI, enterprise systems, and financial services, he combines deep technical expertise with a strong track record of strategic leadership. He has led global, cross-functional teams and managed multi-million-dollar P&Ls in senior management roles at companies such as Koopid, Semantify, Indra, and Quinnox. He is known for building and scaling AI-powered platforms that drive business transformation. Chandra holds a bachelor’s degree in physics and a master’s in computer applications.

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