The "final mile" benefits from the collaboration of artificial intelligence and machine learning and optimized data, says Mathew Witte, senior vice president at Ortec.

At Ortec, Witte focuses on middle- and final-mile supply chain operations, and artificial intelligence and machine learning is very much on the minds of many of his clients. “Everybody’s been talking about them for years, but they’re finally hitting the forefront today,” he says. Much of his customer base and many of the prospects he speaks to look forward to aligning the technologies with their executive strategy.

Adoption, however, is where the risk lies. Witte points to legacy systems that have been around for 40 or more years, worked well, delivered a good and quick return on investment, but then were more or less “forgotten” when it came to data management. “Data is what suffers the most,” he says. “You have to make sure that the strategies are aligned, the data is aligned, and your IT groups are aligned so that everything works effectively. That's the big challenge when it comes to adoption today.”

Witte emphasizes that need to ensure that data is cleaned. “Whatever it may be, whether it's customer restrictions, requirements, vehicle sizes, capacities or general business rules, we have to make sure those are clean to begin with before you turn on any machine learning.”

Any company can take advantage of AI and machine learning, Witte says, depending on the scope of their needs. “Obviously, there is a bigger investment the deeper you want to go, but the more robust you are, the more ready you are from an IT perspective and a company strategy perspective. But having that alignment throughout your organization means companies, regardless of size, are really the readiest to take that leap.”