What is the value of looking at the past?

Perhaps it is to recall fond memories of family and friends or help you understand historical events. An organization looks at the past to analyze its performance and make the right decisions for improving its future performance. For example, managers gather information about costs and ascertain how they behave to predict what they will be “down the road.” They also use past data to understand actions, such as preventive maintenance or inventory planning, that help reduce costs, and cost investments, such as brand building, advertising, and promotions, that help increase revenues and profits, Understanding the drivers of costs and revenues is a valuable technical skill whose importance has grown in recent years with the increased availability of new, massive datasets and cheap computing power to analyze them. The knowledge gained in this process can motivate an organization to reorganize its operations in innovative ways and tackle important challenges. We develop data analytic thinking skills in this chapter and the new chapter that follows.

Southwest Uses “Big Data Analytics” to Reduce Fuel Consumption and Costs ^*

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Southwest Airlines operates a fleet of 700 aircraft, flying about 4,000 flights per day to over 100 national and international destinations. Southwest Airlines’ second largest expense is fuel. Depending on market prices, the company spends between $4 billion and $6 billion on fuel every year. Any small percentage improvement in fuel costs represents huge savings.

Southwest Airlines uses big data analytics to drill down on countless variables—such as fuel load and outside air humidity—on its more than one million flights annually to see how each variable altered fuel use and profitability. For example, if Southwest’s analytics show that planes on a particular route consistently carry too much fuel, it will reduce fuel loads in the future to cut costs.

Thanks to available computing power, such complex analysis is done in minutes and yields significant cost savings for the company. In the first year itself, big data analytics helped Southwest save $105 million in fuel costs.

As the Southwest example illustrates, managers must understand how costs behave to make strategic and operating decisions that have a positive impact. This chapter will focus on how managers determine cost-behavior patterns—that is, how costs change in relation to changes in activity levels, in the quantity of products produced, and so on. We start with the most basic concepts and build to more modern data analytic models in Chapter 11.