23 Kellogg Insight “Who is incented to explain things in a way that allows companies to make genuinely deep, informed decisions? It turns out nobody is, because it often will get in the way of their goals,” says Hammond. “It’s easier if you find yourself in a relatively comfortable position where you know how things work and nobody else does.” This leaves executives—particularly those without ready access to data scientists—in an admittedly tough spot. But instead of going straight to vendors and expecting them to provide a candid analysis of the pros and cons of their tool and the technology that underlies it, Hammond advo - cates working backward from the business problems at hand. “You have to pull back and ask, what are the things that our business needs to accomplish? What are our business goals?” says Hammond. And then, within those goals, what are the nuanced issues that your com - pany is likely to face? If you want to build a system that can predict which individuals to hire or whether a potential client will pay back a loan, what do you want to base that system on? Do you want to mirror the rules your firm currently uses, or do you want to take a different approach? Are there historical data that are relevant, and what limitations might those data have? Do you want your system to interact directly with clients, or with your employees instead? “You can just keep asking questions, and you can build yourself up a nice set of constraints that have nothing to do with technology, but every - thing to do with what you want the business to become,” says Hammond. “Now when you talk to a vendor, you have a set of questions you can ask. And when that vendor says, ‘Oh no, this is too complex. You’re never going to be able to understand it,’ you can say, ‘Yeah, you need to be able Based on insights from Kris Hammond