The state of 3PLs is fragmented along data analytics technology lines

“To look at the big 3PL picture or all 3PLs, I’d say in three words the state is fragmented, fragmented, fragmented. There’s a lot of disparity between the haves and the have nots. … Some organizations are invested so heavily in everything: in data science teams, in large-scale technical infrastructure, expensive software tools. They’re all-in on building it all themselves in-house or getting the best tools. Then, on the opposite end, we’ve got those smaller organizations that just don’t have those budgets available to them.”

“I don’t think it’s a stretch to say that as these trends continue, there’s just going to be increasing pressure on data science teams, on IT — all industries, not just transportation — to justify their analytics costs, to justify all those dollars that they’re spending on analytics.”

“If you want to use a technology like AI, I think of things in terms of table stakes and competitive advantage. Table stakes are less interesting, right? Your customers are going to tell you if there’s something you need to do that AI’s offering that they absolutely expect you to do and that they want right now and they value it. … The competitive advantage, that’s where it’s a lot more interesting but also a lot harder, because you have to do something unique. … So competitive advantage: good news, bad news. Bad news: You have to do something unique. Good news: You can use your own data to find competitive advantage, so go ahead and start combining your data that’s maybe telling you something that you can’t get from a market rate.” 

“Being truly data-driven in your organization is an ongoing process and the right road to analytic success, and it’s three things: Develop strong analytics capability, yes, but you have to — also second thing — apply an experimental approach and an experimental mindset to your business, and the third thing is keeping a strategic focus. If you deploy your analytics that way to make your organization data-driven, that’s where you see this compounding return on investment. … Give everyone the right related and targeted data insights up and down that management chain so everyone can plan that very next step better and make a more informed choice.” 

“You’re not looking for that one win. You’re looking for how to use it over and over for all the wins.”