ARTIFICIALINTELLIGENCE [ INSIGHT ]
by Magnus Meier Global VP for Wholesale Distribution, SAP magnus.meier@sap.com | 610-661-7293
Wholesale Distributors Put AI to Work Looming above all the day-to-day business pressures that wholesale distributors face is one overarching strategic imperative: Find ways to grow profitably—without increasing staffing levels. To meet that challenge, companies must attack it from multiple angles. intelligent product recommendations and resolve more complex customer inquiries than in the past. Distributors use AI-driven robots and cobots (collaborative robots) to help
ll the labor void in the warehouse. Not only can AI-driven tools automate processes, they also can simplify and even eliminate process steps via intelligent process analysis. Essentially, in a labor-constrained industry like ours, it’s about doing less (fewer process steps) with less (labor). Once you’re comfortable with use cases like these, then you can explore AI’s more transformative possibilities, such as preventing customer loss. By analyzing customer buying patterns and behavior, it can alert sales reps to customers they’re at higher risk of losing and recommend the best counter. AI’s predictive powers can also help a wholesale distributor identify and con gure new value-added services to maximize their pro tability to the provider and the appeal to customers. Bringing AI into your distribution operation not only will help you create new value for your company and its customers, it will give your people new tools to do their jobs better. When it comes to the working relationship between human beings and intelligent technologies, as the adage goes, “It’s a duet, not a duel.” n
Having identi ed areas where AI and ML can help you solve a problem and capture new value, try solutions from multiple providers. Some may be general in application, others tailored to a speci c vertical use case. The possibilities are many. One critical area where wholesale distributors can put AI to work is in optimizing pricing. With its ability to quickly and deeply analyze customer and operational data, AI can produce highly segmented pricing recommendations that increase revenue and margin. OPTIMIZING LOGISTICS Those optimization capabilities extend to logistics, where AI can recommend optimal delivery routes, taking into account changing parameters and priorities related to the customer, the product, the route and the vehicle/driver. The bene ts—customer and driver satisfaction, and fuel ef ciency and emission-reduction—can be substantial. As generative AI apps grow more powerful, chatbots become more viable to automate and enhance the customer journey, with the ability to make
They need to get creative to develop new revenue streams around high-value services. They need to sharpen their pricing. They need to optimize inventory and logistics management. They need to deliver faster, more personalized service to boost customer retention. That’s a lot to tackle, especially during a labor shortage. Here’s where intelligent technologies— business AI, generative AI, machine learning—can play an important role. By starting small with AI and ML capabilities, then branching into other use cases as comfort with the technology grows, companies can begin to optimize, extend, and transform key facets of their distribution business, and in doing so, strengthen margin and revenue. How and where to begin? Because the insight AI models produce is only as good as the data that feeds them, rst ensure your data is clean—standardized, trustworthy and fresh. Due diligence to evaluate AI
applications and developers also is a must. Choose intelligent tools with a proven ability to solve a business problem.
48 Inbound Logistics • July 2024
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