Creating a more data-driven culture was an explicit part of Steve Easterbrook\u2019s plan to transform McDonalds when he became CEO in 2015. At the time, McDonalds was under fierce attack from the emergence of \u201cfast casual\u201d restaurants. To reinvigorate McDonalds, Easterbrook set the vision of becoming a \u201cmodern, progressive burger company.\u201d 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.<\/p>\n
Implementation<\/u><\/strong><\/p>\n 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\u2019 headquarters from a sleepy suburb to Chicago\u2019s 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.<\/p>\n 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 \u2013 from the obvious data points, such as time spent ordering, down to the nitty-gritty details of tracking customers\u2019 eye-movements vis-\u00e0-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.<\/p>\n Value Creation<\/u><\/strong><\/p>\n 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\u2019 preferences. One particularly innovative value creation technique made possible by McDonalds\u2019 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\u2019s ready faster.<\/p>\n Value Capture <\/u><\/strong><\/p>\n 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\u2019s 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.<\/p>\n Looking Forward<\/u><\/strong><\/p>\n 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\u2019t only due to data-analytics, but it\u2019s a major part of the picture. \u00a0The data revolution is at the center of McDonald\u2019s recently announced \u201cStore of the Future\u201d initiative, which aims to upgrade stores \u00a0and 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).<\/p>\n McData making for a comeback!<\/em> The major challenge I see for McDonald\u2019s 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.<\/p>\n To end on a high note, please enjoy the below infographic on U.S. McDonalds locations; it\u2019s a powerful visualization of their omnipotence in our society!<\/p>\n They are everywhere!<\/em> Sources:<\/u><\/strong><\/p>\n New McDonalds CEO Steve Easterbrook set the company on a data-driven transformation to improve its customer experience.<\/p>\n","protected":false},"author":2373,"featured_media":7678,"comment_status":"open","ping_status":"closed","template":"","categories":[130,29,947,776],"class_list":["post-7677","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-behavioral-data","category-big-data","category-consumer-data","category-data-analytics","hck-taxonomy-organization-mcdonalds","hck-taxonomy-industry-food-and-beverage","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/competing-with-data-challenge\/","yoast_head":"\n
\n![\"\"](\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2018\/04\/1x-1.png\")
<\/a><\/p>\n
\n<\/a><\/p>\n\n