From the course: Data Analytics for Business Professionals (2022)

Business leaders and data analytics

From the course: Data Analytics for Business Professionals (2022)

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Business leaders and data analytics

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- In my experience, business leaders don't always understand the extent to which they need data analytics. They often understand that data can be powerful, but they often don't know how to leverage it. That said, some top companies are unleashing the power of data in some very creative and valuable ways. Here are a couple of examples. Xerox recently decreased its rate of call center employee attrition by 20% through data analytics, by pairing information from their hiring process, with the employee background and personality types. In doing so, they found a big surprise in the data. That relevant prior experience did not lead to a longer tenure at the company. Rather, personality type was a significant predictive factor. Specifically, they recognized that those with creative personality types had longer tenures than those with inquisitive personality types. As a result, Xerox introduced personality tests in their hiring process, which led to a 20% reduction in employee attrition. Another analytical success story is UPS, a package shipping company which revamped its root optimization software. The company believes that this software grants a competitive advantage, while simultaneously saving hundreds of millions of dollars. A one mile reduction on each driver's daily route saves UPS $50 million annually. The benefits do not stop there, as the reduction in fuel consumption has helped to reduce UPS's carbon footprint. These are only a few examples of how modern companies are adapting to the digital age. A study on the future of jobs by Boston Consulting Group finds that the shortfall in jobs related to computers and mathematics could reach as much as 6.1 million by 2030. could reach as much as 6.1 million by 2030. This course is designed as a first step to using data to help you become data smart in order to fill and succeed in those positions. There are different types of data analytics. Descriptive analytics, predictive analytics, and prescriptive analytics. Each type answers a slightly different question. Descriptive analytics answers what has happened in the past. Predictive answers what might happen in the future. While prescriptive analytics attempts to answer the toughest question of all, what should we do going forward? Most of this course will focus on descriptive analytics, as it is the foundational building block for predictive and prescriptive analytics.

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