Competing With Data & Analytics
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At The Coca-Cola Company, pulling together useful data sets is a particular challenge. Coke’s distribution model involves a network of hundreds of independently operated bottlers around the world that use the Coke concentrates to make and bottle Coke drinks (as well as other non-Coke affiliated beverages). Those bottlers send data to Coke, and Coke’s job is to put those data streams into a common system and use it to look back on how things have gone and project how things might be.
Complicated — to say the least!
Just how complicated can be underscored by a few statistics: Coke is the world’s largest beverage company, with more than 500 brands and 3,500 products sold worldwide. In 2013, the company had $46.9 billion in net operating revenues, and a net income of $8.6 billion. It has about 250 bottling partners with 900 bottling plants, and employs over 700,000 system associates worldwide. In addition to its flagship Coca-Cola products, the company’s brands include Minute Maid juice, Fanta and Sprite soft drinks, and Dasani water.
Mathew Chacko, Coca-Cola’s director of enterprise architecture, and Remco Brouwer, the company’s director of business intelligence, spoke with Sam Ransbotham, an associate professor of information systems at the Carroll School of Management at Boston College and the MIT Sloan Management Review guest editor for the Data and Analytics Big Idea Initiative about the challenges of integrating so many data sets, the ways the company is moving toward a predictive analytics model, and the value of visualizations to convey complex information.
When did Coca-Cola first start thinking about analytical approaches, and how did that first get started?
Mathew Chacko: Analytics at Coke actually has a very long history. An important area of analytics is in our volume and sales reporting and forecasting that spans both the company and our bottler franchisee system. In our sparkling drinks business, the Coca-Cola Company makes the concentrate, and then we sell it to bottlers who are not necessarily owned by us.
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