How McDonald’s Leverages Big Data

McDonald's is a huge food service retailers which spread in almost every country in the world. their daily customer traffic is over 60 million customers, and about 75 burgers are sold every second. McDonald’s is a massive company with $ 27 billion annual revenue and has over 700.000 employees. One billion pounds of beef is consumed by only Americans at McDonald's in a year. McDonald's is obviously generating huge amount of data, lets discover together how they leverage that data?

McDonald's in the past years became an organization of information- centric that making data-driven decisions. McDonald's created a development model project were analytics forms a major aspect of the teams, but it is not the central part.

McDonald’s established teams from different disciplines, their job is discovering, developing and placing new solutions across the organization. In terms of discovery, the team's job is trying to rapidly find ideas and develop them. they have a few skill sets involved, For instance, operations, IT, analytics and engineering. In order to get the right decisions and develop and new projects, McDonald's add extra skills in development phase, such as HR, Finance and training. There are a lot of different departments have involved in development phase like, design or marketing department. According to the Director of Operations Research, Mike Cramer "advises a cross-functional approach with a business focus to achieve a great level of success, especially in the big data and analytics area"

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In the past, McDonald's had a problem which is the local stores was provided the data to the executive leaders depending on average metrics. Thus, it made it difficult to compare the stores and come up with appropriate actions that needed to take place in order to improve results.

In order to provide a lot more visions of what was happening and at which store, McDonald’s has moved to use trend analytics instead of using averages.

To better understand the cause and affect, they combined datasets and visualized it in the differences between stores. e.g. multiple graphs have combined to understand the correlation. These correlations were used to create more clear, relevant and actionable actions, resulting in saving money and time across the organization.

How McDonald's uses big data to optimize drive-thru experience is one of the interesting examples of combined metrics. There are three different factors have taken into account when they analysis and optimizing that experience. Design of the drive-thru, Information that is provided to the customer during the drive-thru and the people waiting in line to order at a drive-thru. When a single customer is waiting too long to get a coffee in the line because of the large family in a van ordering a large menu in front of him; he probably has a negative experience. Hence, McDonald's analyses the demand patterns in order to predict it.

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