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Volatility Speeds Digitization of Supply Chain

Buffeted by volatility in the supply chain and the economy at large, more supply chain executives at original equipment manufacturers (OEMs) are adopting solutions that include artificial intelligence (AI) and machine learning (ML).

With these tools, executives can look beyond their aftermarket products’ sales histories, which may have little relevance to the current situation, and take more factors into account.

“If somebody is planning inventory or pricing parts based on a spreadsheet, they realize that the state of the art has progressed beyond that,” Nate Corder, vice president of global solution consulting and value engineering at Syncron, told PYMNTS. “They realize that there’s an opportunity there.”

Adding a Forward-Looking Indicator

Syncron offers solutions that help OEMs optimize the inventory and pricing of replacement parts for a variety of applications, including aerospace, agricultural and medical equipment, in their own warehouses and those of their dealers.

The company uses AI and ML throughout its platform, including in aftermarket inventory planning, parts pricing, warranty management, field service and predictive analytics — predicting when a part will fail.

In the inventory planning space, Corder said, people have historically done forecasting of spare parts by looking at historical sales. The problem with this method is that the planner will always be lagging. When demand goes up, they’ll have availability issues, and when demand goes down, they’re going to have excess inventory.

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With AI, on the other hand, forecasting can take into account things like weather, customer buying habits, shipping route volumes and other factors. For example, if there’s a forecast of an exceptional hurricane season, that may affect the demand for some parts.

“The way people are using AI in inventory planning is really to filter history but add in a forward-looking indicator,” Corder said.

Developing Multichannel Pricing

In the pricing area, AI can help determine customers’ buying habits and what they’re willing to pay. Years ago, manufacturers would release a price book that included a list price for everybody in the market.

Today, with AI, they can come up with much more focused pricing. Every OEM has multichannel pricing, in which a part is offered to the market in four or five different ways and different price points.

“They’re starting to group customers based on customers’ buying habits and customers’ willingness to pay,” Corder said.

In the warranty space, warranties were previously thought of as simply claims processing. Today, with AI, companies are better equipped to audit warranty claims and get a deeper look at the claims that come through. This is important because warranty is a huge cost center for OEMs.

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Recognizing the Potential of After-Sales 

On the macro level, Corder said, OEMs used to focus only on how to make manufacturing processes more efficient. The after-sales portion of the business was more of an afterthought, even though it was a huge profit generator. Today, they are seeing that the upside is in service.

“People are really just recognizing that the service business is probably one of these big potential areas where they can really move the needle for the company,” Corder said.

Syncron’s solutions are offered as Software-as-a-Service (SaaS), generally with quarterly upgrades and annual payments. With these frequent updates, Corder said, the company is “fulfilling the SaaS promise.”

“We’re constantly working with our customers, we’re looking at their data with them and we’re helping them become better,” Corder said. “Ultimately, we’re making sure that they get continuous value and that we’re really helping them improve their business.”

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