For Distributors, the Benefits of Artificial Intelligence Can Be Very Real

If you aren’t yet using AI to benefit your distribution business, you soon will be.

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Matt Peterson, Senior Director of Industry Solutions at ENAVATEMatt Peterson, Senior Director of Industry Solutions at ENAVATE

If you’re like many distributors, when you hear the term “artificial intelligence,” you think Amazon. But the giant of retail — and, increasingly, wholesale — isn’t alone in making the most of what artificial intelligence (AI) has to offer. Not long ago, only the largest companies with the deepest pockets had access to AI. Now companies of all sizes are taking advantage of AI – and so are individuals. In fact, most of us use it in our daily lives, whether we’re talking to Siri or summoning an Uber driver.

If you aren’t yet using AI to benefit your distribution business, you soon will be. And hopefully your competitors haven’t beaten you to it.

Basically, AI analyzes and learns from data, implements a solution and evaluates the results. Over time the system grows smarter. When they implement AI, distributors can create smarter, more intuitive, and more efficient processes. What’s more, AI can streamline the supply chain, freeing up resources and talented employees for more strategic activities.

By analyzing data regarding behavior that influences purchasing — such as whether a prospect downloaded a whitepaper — AI-driven technology can tell your sales team which customers and potential customers they should be spending time with.

And when existing customers visit your website because it’s time to re-order, AI can suggest companion products they may be forgetting, or just didn’t realize they needed.

The technology AI uses to make all this possible also reduces errors and makes it easier for your customers to do business with you – making your customers happy. The inverse is also true: If you don’t offer the convenience and speed this technology drives, you risk making customers unhappy.

Machine learning is often mentioned in the same breath as artificial intelligence. In fact, machine learning is one of many subfields of artificial intelligence, and one of the most useful for wholesaler-distributors.

Machine learning enables computers to use existing data to forecast future behaviors, outcomes and trends. In its most basic form, machine learning works by teaching the software to find patterns in the current data so that it can seek out patterns in future data. You already use machine learning in everyday life, including pricing on ridesharing apps and predictive text when you send a text message through your phone.

Other applications include:

Sales forecasting. With machine learning, businesses can incorporate a broad set of data, including weather and traffic — as well as internal data on seasonality, discounts, or promotions — to precisely predict sales in a specific time frame.

Strategic pricing. Using data compiled through price elasticity, lost sales, historic sales, and promotions, machine learning and artificial intelligence can pinpoint optimal prices.

Raising red flags. Artificial intelligence and machine learning can identify and alert business to aberrations, like fraud or abnormal equipment readings.

Optimizing collections efforts. Machine learning capabilities include scoring late customers by how likely they would be to pay if your accounts receivable team contacted them.

The digital revolution has already transformed the distribution industry, and artificial intelligence and machine learning are set to take the industry further into new realms. There are real business benefits to using AI, including growing average order size, boosting margins, and tightening customer relationships. Smart distributors will not let themselves be left behind.

Matt Petersen is the Senior Director of Industry Solutions at ENAVATE, which provides consulting and wholesale distribution-focused enterprise software solutions based on Microsoft Dynamics 365, AX and CRM platforms. Reach him at matt.petersen@enavate.com or visit enavate.com.

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