Artificial intelligence and machine learning are optimizing warehouse operations, says Chad Zollman, chief sales officer at TGW Logistics Group.

Labor scarcity tops the list of issues facing supply chain managers in the last couple of years, especially in light of the increase in e-commerce. Zollman says automation is the answer, but what’s the right amount of investment — and precisely what needs to be implemented?

“We saw the customer base asking how they can add automation to their supply chain portfolio,” he says. “Where's the right investment for their operations?”

As customers scrutinized volumes, order profiles and business models during the pandemic, many felt they needed to automate, but weren’t sure how to plan for that. That’s a serious discussion for any company, Zollman says, because it’s unclear if developments over the pandemic years will flatline and continue as they are, continue a growth spurt, or revert to something like pre-pandemic levels. Where are volumes going to be in the next five years or so? What will a given company’s capacity going to be? “These are long-term conversations and discussions as it relates to ROI models.”

Attacking the problem with a digital lifecycle solution is imperative, Zollman believes. First, one must look at a customer’s history and trends, trying at the same time to measure sensitivity change in its business. AI and machine learning follow. Nevertheless, it’s a matter of understanding how much a company should automate its business.

At the end of the day, a company needs to work with a provider that can measure its business, examine alternative scenarios and ensure that the business model is predictive about an uncertain future. Zollman says that’s the only way to create a solution that can accommodate changes to the business and make the given asset deliver on ROI.