Some organizations are expanding their use of automation to reduce the number of rote tasks that humans perform. In the process, organizations are enabling their workers to focus on more fulfilling, higher value tasks.
Unilever: Flex experiences
As the world locked down during COVID-19, Unilever, the consumer goods giant, saw its marketing, supply chain, logistics, and manufacturing divisions experience surging demand for household staples. At the same time, employees in other parts of the company were experiencing more down time than usual, as demand for their services slowed. In response, Unilever created “Flex Experiences”, an AI-powered talent management platform that connects employees with opportunities to build skills and work on different projects laterally across the company. Currently used by some 65,000 Unilever employees, the platform has helped the company unlock many thousands of hours per month in additional productivity from its workforce. The platform has also received a 95% endorsement rating by Unilever employees, who appreciate the opportunity to expand their skills.
U.S. Bureau of Labor Statistics: Deploying AI to create higher-value work
For many years, the U.S. Bureau of Labor Statistics (BLS) has conducted an annual “Survey of Occupational Injuries and Illnesses” to document workplace injuries at American companies. In the past, completing the survey was primarily a manual endeavor, one that required some 25,000 labor hours each year. In 2014, however, BLS began experimenting with machine learning (a type of AI) to help it code some of its survey data. By 2020, more than 85% of BLS’ survey data was coded using human-supervised machine learning. The result was not only improved survey accuracy, but also increased demand for human coders to oversee the AI and to resolve complex coding problems. To fill this demand, BLS focused on sourcing employees from within the organization who were willing to upskill. The win-win result: BLS employees enhanced their skills and had their “employability” needs met, while BLS enhanced the accuracy and efficiency of its data analysis and reporting.