Balancing Act: Whole Food’s Struggle Between Data and Human Judgment

Everyone knows that these days, if you’re NOT using data and integrating tech into your company, you’re doing it wrong. On the other hand, there’s also a pretty big misconception here. Sure, we’re in the digital era, but that doesn’t mean we can just brush away the importance of human judgment. Instead of letting new technologies take over your entire business, you can use data more effectively by complementing existing human judgment and decision-making processes with it. And Whole Food’s recent merger with Amazon tells you exactly why.

Clashing of Cultures

In 2017, Amazon acquired Whole Foods. But what you have to understand is that Amazon and Whole Foods have a set of very different values. Amazon as a whole is very data-centric, implementing new technologies wherever possible to try to optimize supply chain processes, customer management, and overall efficiency. Whole Foods, on the other hand, has historically been known for relying on their employees to make any and all decisions in their own stores.

So when Amazon stepped in and started making changes, employees were not happy. Their biggest nightmare? Amazon’s order-to-shelf system. OTS was a new inventory-management system that Amazon incorporated into every Whole Foods store - it incorporated strict procedures detailing how to go about purchasing, displaying, and storing products. The unintended consequence? Employees became more worried about OTS paperwork than the thing they were best at - customer experience.

An Employee’s Worst Nightmare

OTS was more than time consuming - it was confusing for teams. What was once shelves fully stocked to the brim and employees excited to come to work everyday, became empty shelves, angry customers, and insanely stressed store employees. The problem is, almost every Whole Foods employee is hired for their aptitude in customer service and interpersonal skills and NOT in tech. They didn’t sign up to learn how to deal with complicated inventory-management systems everyday at work - they signed up to use their own judgment to decide what local needs and customer desires they should address.

So not only was the OTS system failing because no one knew how to use it, but the quality of service employees could offer suffered as a result of worsened morale. At Whole Food’s core, it’s their employee structure that made them so successful in the first place. In fact, it was only after the merger that Whole Foods dropped out of Fortune 500’s “Best Companies to Work For” list after a 2 decade streak.

To give you some perspective on what made Whole Food’s employee structure works so well, let me summarize it for you. Their whole employee concept is built on the idea of democracy and discipline - and at the core of that is teamwork. Employees’ abilities to make decisions starts as early as the hiring process where every store’s team must cohesively agree on a new hire after a 30 day trial period. This process ensures Whole Foods is hiring the best of the best not just for the role, but also the organization. Luckily, Amazon has learned its lesson and is working on a way to use data to improve operations and train employees better to handle it, while still letting employees take the wheel where need be.

Takeaway

But the point of this article is not to explain why you shouldn’t rely on data and tech. The moral of the story is that understanding and using data properly isn't possible without a touch of qualitative analysis from the human mind. Our team here at Cotera does exactly this - our goal is to complement the human mind with data so that we can help you figure out what to use data-backed insights for. Ultimately decisions are up to you and your team - but data is here to make tougher decisions easier for you.