Large-Scale LP in Business Analytics

Introduction

Although the definition of business analytics (BA) continues to change, BA generally involves big data and statistical and quantitative analyses to describe and investigate business performance. Results of the analyses are expected to provide new insights on future business planning by establishing several predictive models, which are also based on big data. Future business planning includes numerous operations and supply chain problems and solutions, such as demand forecasting, capacity planning, workforce planning, revenue management, inventory management, logistics analysis, and routing associated with prescription goals when the problem is optimization. Manyika, Chui, Brown, Bughin, Dobbs, Roxburgh, and Byers (2011) identified several merchandising problems, such as assortment optimization and pricing optimization. With the availability of big data, the aforementioned old-fashioned problems and solutions become new areas of research that might require the development of new and sophisticated BA approaches and methods. It is because big data generally refers to data that is so large and complex that they create significant challenges for traditional data management and analysis tools. For example, Weier (2007) reported that Wal-Mart handles 800 million transactions generated by its 30 million customers each day. Another chain store utilizes its data systems to handle a database table of more than four billion rows. Kiron and Shockley (2011) mentioned that the next big data measure after zettabyte (10²¹ byte) is yottabyte (10²⁴ byte). Billions of years is required to download a yottabyte file at current high-speed broadband speeds. If Internet traffic continues to grow at current rates, we will likely approach the yottabyte milestone before the end of this century. IBM Big Data (2013) mentioned that 2.5 quintillion bytes of data are generated every day; 90% of the data in the world today has been generated in the last two years alone. This data can be considered as a kind of big data. Hence, the ability to store and retrieve big data is believed to be only a small piece of the competitive puzzle. Through several BA techniques, such as data mining and statistical prediction models, all successful retail Web sites can suggest additional purchases at checkout. Clearly, the size of the big data of companies is not the unique key factor to distinguish the winners. One of other key factors is the ability of companies to utilize optimization methods with big data to optimize resource utilization and make decisions, and one of the optimization methods is linear programming (LP). In this chapter, we discuss the application of large-scale LP from the BA perspective.