One of the most important roles of the management accountant is to help managers make decisions. In today’s business environment, managers can access unprecedented amounts of data. Specifically, businesses generate vast amounts of data about customer preferences, supplier behavior, and marketing operations in the course of daily operations. Managers use data analytic techniques to make predictions based on these data. The business press refers to these trends as the age of big data, machine learning, and artificial intelligence. The management accountant helps companies derive value from big data by helping managers to use data-analytic techniques to transform the company and unlock significant cost-saving and revenue-generating opportunities, as the following vignette describes.

Predictive Analytics Inside: How Intel Drives Value and Speeds Time to Market^*

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For more than 50 years, Intel has been one of the world’s leading semiconductor manufacturers. In recent years, the company’s information technology (IT) department has turned to predictive analytics to help drive revenue and get its products to market more quickly.

In 2018, Intel’s IT group delivered $1.25 billion in business value through the use of predictive analytics across the company’s sales, supply chain, and manufacturing operations. Applying analytics and artificial intelligence (AI) in its sales and marketing channels, Intel interprets marketplace data from around the world in real time to help customers configure their machines and increase customer satisfaction and revenues.

Additionally, using smart analytics, Intel improved the time to market for key company platforms and products by nearly 52 weeks. How? Intel created a machine learning platform to find potential bugs during the design phase of its products before they go into development. Testing and validation is now completed about 60 times more quickly and identifies 30% more bugs than the previous process, all before costly manufacturing begins.