Case 3.2 Revitalizing MacDonalds

With 62 million daily customers and an annual revenue of $27 billion, McDonalds has a virtually unrivaled amount of data at its disposal to analyze. In order to dominate the market, retain its loyal customers, and attract new customers who are skeptical of McDonalds practices and quality, it lends itself to its data, becoming an information centric organization. What does it mean to be information centric? Instead of using a fixed process of production, service, etc. as a business plan that is product driven, McDonalds uses customer data to dictate its next move as a customer-driven corporation. During the inception of McDonalds in 1940, the McDonald brothers derived a product-driven business centered around fast service and tasty food. While that method was successful before other restaurants entered the fast food market, growth was stunted due to a lack of innovation and change. So, the organization began to collect customer data as a means to monitor successful products, customer demands, and the results of marketing campaigns. This venture led to McDonalds becoming the premier fast food chain across the United States in the 1980s. Soon after becoming a customer-driven corporation, McDonalds introduced the Happy Meal so families with small children could reduce costs and waste at dinner time, released the Egg McMuffin as the most successful breakfast item of all time, equipped professionals and teenagers with free Wi-Fi to expand its customer segmentation, and provided nutrition details to become the most transparent fast food chain at the time. All of these improvements derived from McDonalds using its immense amount of data to set its chain apart from the rest. In 2008, to further improve its ability to leverage big data, McDonalds made the transition from average-based metrics to trend analytics. The issue with average-based metrics is that it is hard to compare regions and stores. A store could be growing in its sales and productivity but have the same average metrics as a store that is declining. Using trend analytics allowed McDonalds to combine multiple datasets from multiple data sources to visualize and understand cause-and-effect relationships in individual stores and regions. The correlations it found enabled its analysts to prescribe solutions to problems in sales, production, turnover, and supply chain management to reduce costs and save time. The variables it studies allows McDonalds to create a standardized experience across the world. However, analyzing local data in each store produces minor changes around the organization. For example, most McDonalds locations look the same, but each restaurant is slightly different and optimized for the local market. A great example of McDonalds big data analysis in action is its updated drive-thru system. All fast food chains have bottlenecks in their drive-thru lanes, but McDonalds average customer wait time is about 3 minutes, which is close to the industrys longest wait time of 214 seconds. One of the most prominent issues in its drive-thru was that customers going through the line for dinner, ordering large meals and searching over the menu for an extended period of time, created a negative experience for each car in line behind them. In response, McDonalds optimized the drive-thru across three components: design, information, and people. Design focused on the improvements to the drive-thru, including better speaker quality and higher resolution, digital menu boards. Information centered around what was on the menu board. In order to decrease order times, McDonalds removed about 40% of the drive-thru menu board. In its third aspect, people, the fast food chain attempted to reduce the negative experiences for those in line by creating a second drive-thru line with a designated order taker for each line, a third drive-thru window, and two production lines. Another example showing McDonalds commitment to being a customer-driven corporation is its introduction of all day breakfast, which was the highest priority for customers across the United States. Being the corporation with by far the largest share of the fast food market, McDonalds will continue to use its growing data sets to provide the best experience and food to its customers (van Rijmenam, 2016).

Questions

1. Explain McDonalds mission and responsibilities.

2. What limitation did McDonalds face in gaining data that was meaningful to decision-making?

3. Describe trend analytics.

4. Is McDonalds product oriented or customer oriented?

5. Why is the ability to identify patterns and relationships critical to McDonalds operations?