How Google uses technology to help its employees decide to eat better

Not all technology is, nor should it, be focused on increasing consumption and fattening the owner’s bill.

Technology also serves to make people decide for themselves to eat better. It’s a challenge that Google took up and shared at an event a few months ago in London.

Based in London, Jim Glass is one of three food service managers in the EMEA region supporting Google’s food program.

The program as a whole has the indispensable role of planning meals for 200 cafes around the world serving more than 106.000 users in 56 countries. This means serving more than 159.000 meals daily with each meal as an opportunity to push employees to consume more nutritious foods.

Enabling employees to make better food choices is a top priority for the Google Food Program, and data plays a crucial role.

The importance of data for food

The data is not only used for quantitative applications in planning, but also to inform the team on how to optimize the layout and design of their coffees to drive healthy eating behavior.

For example, a 2013 study by Wansink & Hanks shows that the food on the first tray in a buffet line is occupied by 75% of diners. The food from the first 3 trays in a buffet line ends up being the majority of what’s on the plate. Armed with this knowledge, Google can drive healthier eating behavior by placing more nutritious foods as the top 3 offers.

Prepared plates are also an effective strategy. Cafe crews can fill plates with more veggie-based options, effectively taking the decision-making process out of the hands of diners and making the best choice the easiest!

The proof is in the pudding, or let’s say data, as Jim shares that only London cafes detected a 10-20% change in behavior towards a healthy meal when pre-prepared instead of a self-serve station.

Other areas in which Google’s food team has leveraged data for decision making include shared desserts, better options in sight, and implementing the ‘out of sight, out of mind’ concept, as with Project M&M. .

Project M&M was an operations force made up of PhDs in behavioral sciences, surveying patterns of snacks, collecting data on the proximity of the containers of M&M chocolates to any given employee.

What if the company kept the chocolates hidden in opaque containers, but displayed dried figs, pistachios, and other healthy snacks in glass jars where the chocolates were displayed? The results: In the New York office alone, employees consumed 3,1 million fewer calories from M&M over seven weeks. That’s a decrease of nine M&M vending machine packages for each of the 2.000 employees in the office.

The Google Food Team continues to innovate and evolve, relying on sound and well thought out design to develop strategies around: How do you enable your employees to make better food decisions? By leveraging data to inform decisions, they have been able to positively influence their employees to make better decisions for themselves. It all comes down to making the best choice the easiest option.