McData: underdog McDonalds using data to defy its naysayers
New McDonalds CEO Steve Easterbrook set the company on a data-driven transformation to improve its customer experience.
McDonalds is the behemoth of the fast food industry, but its reputation has endured a battering in the last decade. It’s scale, however, creates massive amounts of data that could be mined to mount a comeback. With over 37,000 worldwide locations, daily customer traffic of over 60 million people, and sales of more than 75 hamburgers every second, McDonald’s stood to benefit enormously from more insightful analysis of the vast data generated by its operations.
Setting the Vision
Creating a more data-driven culture was an explicit part of Steve Easterbrook’s plan to transform McDonalds when he became CEO in 2015. At the time, McDonalds was under fierce attack from the emergence of “fast casual” restaurants. To reinvigorate McDonalds, Easterbrook set the vision of becoming a “modern, progressive burger company.” This vision hinged on quality improvements (such as using antibiotic-free chicken and fresh beef), operational changes (such as menu/pricing innovations), but also more fully embracing the data revolution.
Embedded inside the wider vision of transforming McDonalds, Easterbrook made specific operational decisions to accelerate the implementation of his data-plan. He announced the relocation of McDonalds’ headquarters from a sleepy suburb to Chicago’s urban West Town neighborhood, an area of hot restaurants and bars to attract millennial employees. He then grew the McDonalds Digital Team from 3 to 130 employees in eighteen months, laying the human capital foundation for the data-driven future.
Previously, McDonalds only received average metrics from its different locations. This made it hard to compare across storefronts and draw meaningful insights. In order to shift to trend-analytics, McDonalds started capturing much more granular raw-data across its portfolio. Using sensors and video, McDonalds started capturing data on just about everything you could imagine: operations in the kitchen, customer purchase decisions with cashier attendants and at automatic kiosks, and customer behavior at the drive-thru and in seating areas – from the obvious data points, such as time spent ordering, down to the nitty-gritty details of tracking customers’ eye-movements vis-à-vis the menu. It also pushed out a highly-resourced mobile app with an accompanying loyalty program to gather more information on its customers and their habits.
The foremost value creation of this data-led transformation has been a significantly enhanced customer experience. To offer just a few examples: kitchen-data has been used to perfect cooking methods for taste and temperature; drive-thru data has been leveraged to restructure the flow for faster completion; in-store data has been mined to make new iterations in layout and design of the store; mobile-app data has been analyzed to send targeted discounts based on loyal customers’ preferences. One particularly innovative value creation technique made possible by McDonalds’ new data-trove was to use geo-tracking data from the mobile app to locate customers as they approached a McDonalds store and preemptively start cooking their favorite food items, so that it’s ready faster.
McDonalds uses this data-driven process to capture value through long-held fast food industry goals: increased ticket size per order and higher frequency of visits by customers. It’s easy to see how data-analytics helped achieve these goals. A couple of examples: targeted calls-to-action make it more likely customers will purchase an additional item or two at McDonalds, and an quicker drive-thru experience makes it more likely a customer will come back again soon. One particularly innovative value capture technique used by McDonalds involved A/B testing on their digital menus to determine how factors like product placement, image/video selection, and number of items could be manipulated to maximize profitability.
The data-driven transformation has benefitted McDonalds tremendously. Same-store sales have gone through the roof after several lackluster years (see below). Obviously, this isn’t only due to data-analytics, but it’s a major part of the picture. The data revolution is at the center of McDonald’s recently announced “Store of the Future” initiative, which aims to upgrade stores and set the company on a new path to relevance with young consumers. One major opportunity for McDonalds is to use data-driven insights to massively expand its newfound delivery capability formed through a partnership with UberEats (announced late last year).
The major challenge I see for McDonald’s data-driven future is its franchise model. The insights and recommendations McDonalds corporate gleans from data can translate into major capital expenses for franchise-owners, who are already under financial pressure from increased wage demands from employees. If McDonalds wants to use data to fully build out the stores of the future, it may need to subsidize franchisees to make the necessary changes materialize.
To end on a high note, please enjoy the below infographic on U.S. McDonalds locations; it’s a powerful visualization of their omnipotence in our society!
Student comments on McData: underdog McDonalds using data to defy its naysayers
Thanks for the post. Really liked the infographic at the end – great way to visualize the power of scale. Has McDonald’s implemented these digital changes across its entire global footprint or only in select geographies? I wonder if/where most of the sales increase is coming from – is it mostly from new geographies, certain new products or just increased purchase volume overall. I also think of Domino’s pizza and their success with implementing fast, convenient delivery. Given the anecdotal poor performance of UberEats, I wonder if a build strategy might be better for McDonald’s as the “fast” aspect of “fast food” seems to be increasing in importance. I also wonder if their data has helped with the nutritional changes in the product (I’m thinking of the “Super Size Me” documentary). Has McDonald’s been able to make a meaningful move toward healthier ingredients more quickly as a result of their data?
Very interesting, Austin! The menu in McD s are very different across the countries. For example, in Indonesia, McD is known for its crispy fried chicken and not its Big Mac. I am thinking about how this data can also inform McD creates different strategies for placing new franchises, selecting menu placement across geographic in the wide United States to maximize its profitability. What would you think about that?
Thank you for your post Austin!
I think it is very interesting that a company as big as McDonalds was able to roll-out a digital initiative in such a successful way. As we have seen in class, there can be significant resistance to data-driven changes, and I wonder if that was an issue for McDonalds. Other than the significant economical costs of this to franchisees, I assume there is a significant loss in independence and higher accountability and I wonder how much push-back the company had.
As you mentioned, this has had significant consequences in their customer experience, and it be interesting to see if customer satisfaction has increased accordingly.
Great post! I love your examples of how data has transformed McDonalds performance in recent years. Will be interesting to see how the company will upgrade their store and dial up data usage to increase customer satisfaction. One thought would be to start customizing menu for its loyal clients based on their preferences or past purchases. This would not mean changing the whole menu across all the franchises, but rather suggesting the items that would match customer preferences. This can increase both loyalty and ticket size. On other hand, given McDonalds dense penetration, at least in the U.S., I am curious to find out how the “digitalization” of the stores will be realized in the rural areas, where customers are not that sophisticated and might resist the change as it will make their preferred fast-food chain too complex.
This is a very interesting post. I am also concerned on how quickly McDonalds will be able to capture the value of this data driven approach as they push the costly initiative to franchisees. I wonder if they need to test things in one region with a few top-tier franchisees before rolling this out across all storefronts. Furthermore, McDonalds needs to focus on menu change and providing healthier options to customers in addition to utilizing data to increase sales, if they want to remain relevant in the long-term.
Great post Austin! To your point about the implementation challenge under the franchise model, I agree that initially McD might have to fund the required Capex but as they validate that the data-deiven approach yields better performance franchisees will be more open to adopt the model and fund the additional expenses. Ideally, McDonalds should have objective metrics such as sales per sq foot and use those them as a selling point.
Super interesting post – I feel like I learned so much about McD! My biggest question after reading your post is related to the concern you raised about the franchise model. I love the efforts from the CEO to collect so much more data, but I wonder if the stores themselves will be able to glean insights from the data and put the changes into effect without some hand holding from corporate. The flipside of that of course is that all of this rich data is collected but never put to good use. However, the graph you included is hard to argue with given the tremendous progress they have seen to date!
Having used UberEats to order McDonalds within the last week, I was delighted to see your post, Austin! Very interesting to see McDonalds use straightforward data analytics to turn around their recent multiyear decline. It will be interesting to see how they are able to sustain this turnaround as public sentiment continues to turn against unhealthy fast food. Perhaps they could find a way to develop new healthier options informed by data-driven insights?
Love the omnipotence visualization! Thanks for the post! As I was reading your post, my thoughts went to data regarding post experience feedback. Does McDonald collect any end of cycle feedback on customers experiences? It would be fascinating to try and create any data capturing tool outside of the boring satisfaction surveys at the end of the purchase, but rather after consuming the meal.
(Probably best to do so quick and not 24 hours after – I know I’m usually filled with McDonald Guilt for at least a month LOL)
Interesting post, Austin! I can only imagine how difficult it would be to forego a milkshake when the McD’s mobile app remembers that I ordered one last time and is incessantly encouraging me to order one again! It’s quite surprising to me that McD’s wasn’t capturing and analyzing some of this data before. It’s a good thing that they’ve started because I feel like the company will need all the advantages it can find to fight what will likely be a continued decline in customer traffic. Really interesting about the eye-tracking menus. Would love to see that in action!
Thank you, Austin. This is remarkable that McDonald is using big data to innovate brick and mortar retail store. What was even more interesting was the shift in the company DNA. I find it very impressive that McDonald could leverage A/B testing to quickly leverage data gathered, experiment on it, and roll it out on a larger scale. I would love to hear more about how the company manage the people aspect in implementing this strategy.
Interesting read. Thanks for sharing. I wonder if McDonalds could offer some sort of loyalty program similar to what many retailers do so that they can get more information on the customer level. Although they capture loads of information based on ticket sizes, same store sales etc, they aren’t able to glean any insights based on my behavior as a repeat customer and I’m guessing they’re missing out on some useful take-aways. I know its tough for a fast-food restaurant to incentivize consumers to sign up for any kind of data-sharing promotion but could be interesting. Possibly if they tie it into the McDonalds promotions. Food for thought.
What an amazing post, Austin. Kudos from a fellow Section Geeer.
Your blogpost reminds me of Jeff Bezos’ 2016 letter to the shareholders, where he underscored the importance of decision-making velocity in addition to decision-making quality. From your description, I got a sense that McDonald has echoed Bezos’ philosophy of maximizing decision-making velocity by aggressively shortening the cycle time of experimentation and learning through a variety of lean methods.
Fascinating read. Thank you.
I’m especially intrigued by the usage of sensors and video as an insight-extraction tool. However, I’m curious as to the impact, if any, that this level of surveillance has on employee morale and turnover. From an employee motivation perspective, I would hope that employees are included in the debriefing process and are given the opportunity to co-create higher operational standards alongside management. Unfortunately, I imagine that more often than not, employees are simply told that the data shows they’re doing something wrong, and changes are decided by the top without buy-in from front-line workers.
Thanks for the post Austin! I have not been to a McDonald’s in several years and I assumed they were continuing to struggle. Your post totally changes my perception of both the restaurant and what areas data science/ analytics can be applied to. The rate of implementation you highlighted was extremely interesting and I wonder how it was initially received by employees, store managers, and franchise owners. Does McDonald’s have a few test centers where it conducts R&D and rolls out new initiatives? This would be a great change management case to study, especially given the age and culture of the company.