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This chapter is from the book

Overview of Nine Journeys

IBM has many business functions. Some of them are generic functions—including human resources, finance, supply chain, sales, information technology, marketing, and services—that can be found in most enterprises. Other functions—such as software development and hardware manufacturing—are more specific to a technology company, although analogous functions exist in other industries (for example, manufacturing cars in the automotive industry).

This book contains 31 case studies of how nine business functions have incorporated analytics to change the way they do business and to improve their business results. Each business unit’s story is told as a separate chapter, beginning with an overview of the unit’s journey to improve its business results by levering analytics, including the pitfalls and lessons learned, followed by a more detailed description of one or more significant analytics projects within that business unit. The nine business functions started their analytics journey at different times, and they’re now at different stages; they also used different approaches. Each journey is different, though we do see some common themes.

Some business units have been on long journeys, others are just starting their journeys, and others are in between. All of the business units have a history of using descriptive analytics or business intelligence. This book concentrates on predictive and prescriptive analytics and newer forms of analytics, such as social media analytics and entity analytics.

IBM’s supply chain organization started its journey the earliest and has numerous analytics solutions. You will learn how the supply chain organization is using analytics to reduce expenses and to predict quality problems before there is an impact. The supply chain organization is also using social media analytics to predict supply disruptions based on events around the world. The finance organization also has a rich history of using analytics. Examples include using analytics to reduce financial risk and to reduce the risk of an acquisition failing to meet objectives. IBM’s human resources (HR) organization started using analytics more recently and is using predictive analytics to proactively address retention and is using social analytics, big data, and sentiment analysis to take the “pulse” of what employees are thinking about various issues, such as a new HR program. IBM’s information technology (IT) organization has developed a number of applications that leverage analytics and big data, such as how to find an employee and how to answer questions about products and services from the sales force.

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