Intellectual Capital

Putting in the Legwork for Food Delivery

Corey Shull, CFA, Vice President / Analyst

Executive Summary

While visiting a food delivery company in London, T. Rowe Price investment professional Corey Shull saw a unique opportunity to go the extra mile in his research and gain a deeper understanding of the company’s potential to deliver growth for investors.

Shull looks for early stage companies that are poised to disrupt their respective industries through technological or business model innovations.

Meal delivery from restaurants has traditionally been a very manual, phone-driven process. “Even today most food pickup and delivery orders are processed by phone, which feels incredibly archaic and old-school,” says Shull. He believes food delivery is primed for technology-fueled disruption.

Delivery is the fastest-growing channel in food service and is forecast to grow 51% between 2016 and 2021.1


Delivery is the fastest-growing channel in food service and is forecast to grow 51% between 2016 and 2021.1

From Brewery Parking Lot to Concept Kitchens

Shull goes beyond the numbers when analyzing companies, heading out into the field to interview top managers and observe operations firsthand. His research led him to a London-based food delivery company, which had recently unveiled an innovative concept to complement their traditional delivery model: a decentralized network of satellite kitchens from which to launch bike deliveries in a congested urban environment. Shull flew to London to view one of the sites, an old brewery with a parking lot that had been converted into six concept kitchens.

“They were essentially storage containers converted into kitchens with modern equipment and a lean staff,” says Shull. “It’s a fully integrated model where you order from the delivery company, the orders are placed directly into these kitchens where the food is prepared, and you’ve got the delivery people picking up batched orders in these parking lots to bring to customers.”

Opening Quote We really viewed the concept as durable, differentiated, and it was the first time we had seen someone try to do this at this scale. Closing Quote

During his visit, Shull was struck by the detail-oriented approach of the company’s leadership team and their use of technology to improve speed.

“They’re trying to figure out when it’s raining in London this evening, how that will impact orders, and how many riders do we need based on historical data during the spike in consumer orders at 6 p.m., which is an incredibly complex problem,” says Shull.

The company uses machine learning to predict the time it will take to prepare a meal and ensures that delivery riders arrive at the right time and aren’t waiting for food to be prepared. Their algorithm evaluates the most efficient way of distributing orders based on the location of restaurants, riders and customers, which has led to a 20% decrease in delivery time.

“The way that their CEO was thinking about the industry, I felt that no one else had really framed it in the same way,” says Shull.

Gathering Data From the Delivery Seat

Shull decided there was more he could learn about the company’s efficiency. So, to get the full story, he hopped on a bike to see for himself.

“I’d never biked through London before,” says Shull. “My phone fell off its holder and I almost got run over by a truck, so it was kind of intimidating, but it was a great experience talking to the restaurants and understanding their relationship with the delivery company.”

Through a combination of observations while delivering orders himself, meetings with company management, and thorough quantitative research, Shull was able to get the full story on the company’s potential to deliver for investors.

Optimizing Both Sides of the Delivery Business

Today’s consumers are more inclined to eat at home and are becoming more comfortable using smartphones and tablets to place their orders. That’s making delivery the fastest-growing channel in food service, which is forecast to grow 51% between 2016 and 2021.2

Shull describes the food delivery business as two-sided. “First, you’ve got the customer side, where delivery companies are trying to show customers personalized offers at the right frequency and get them to convert on the website, which are all things that the data science teams of delivery companies are trying to figure out. You also need to have the right selection and high-quality food.”

“Then on the delivery side, you need a certain number of orders per delivery person per hour to make the unit economics work. If you only have one delivery per person per hour, and that driver isn’t getting paid enough per order, that doesn’t work as a business model.”

This research is critical to understanding the economics of food delivery. But from a practical perspective, it wasn’t until he got on a bike that Shull could confirm that the company could reasonably deliver on its promise of faster delivery times.

“We really felt that there are core urban areas where you can build enough density to really make the model not only work but be incredibly profitable,” says Shull.

Important Information

1 Source: Euromonitor International, 9/17.

2 Source: Euromonitor International, 9/17.

This material is provided for informational purposes only and is not intended to be investment advice or a recommendation to take any particular investment action. The views contained herein are those of the authors as of November 2018 and are subject to change without notice; these views may differ from those of other T. Rowe Price associates.

This information is not intended to reflect a current or past recommendation, investment advice of any kind, or a solicitation of an offer to buy or sell any securities or investment services. The opinions and commentary provided do not take into account the investment objectives or financial situation of any particular investor or class of investor. Investors will need to consider their own circumstances before making an investment decision.

Information contained herein is based upon sources we consider to be reliable; we do not, however, guarantee its accuracy.

Past performance cannot guarantee future results. All investments are subject to market risk, including the possible loss of principal. All charts and tables are shown for illustrative purposes only.

T. Rowe Price Investment Services, Inc., Distributor.

© 2018 T. Rowe Price. All rights reserved. T. Rowe Price, INVEST WITH CONFIDENCE, and the Bighorn Sheep design are, collectively and/or apart, trademarks of T. Rowe Price Group, Inc. 

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