Skip to main content [aditude-amp id="stickyleaderboard" targeting='{"env":"staging","page_type":"article","post_id":2115288,"post_type":"guest","post_chan":"none","tags":null,"ai":true,"category":"none","all_categories":"ai,big-data,bots,business,","session":"A"}']
Guest

How machine learning can make humans better managers

Image Credit: Shutterstock

Machine learning is rapidly infiltrating today’s workplace, in businesses of all shapes, sizes and industries — and it’s here to stay. In fact, so far in 2016 over 200 AI-focused companies have raised nearly $1.5 billion in funding, and equity deals to startups in AI increased 6x from roughly 70 in 2011 to almost 400 in 2015.

Large companies like Google, Microsoft, and Amazon have already begun to build their machine learning capabilities to handle large data sets and recognize patterns. But an area that machine learning hasn’t yet fully infiltrated — and one that it has the ability to transform — is people management. In fact, 55 percent of organizations still report being weak at using HR data to predict workforce performance and improvement.

[aditude-amp id="flyingcarpet" targeting='{"env":"staging","page_type":"article","post_id":2115288,"post_type":"guest","post_chan":"none","tags":null,"ai":true,"category":"none","all_categories":"ai,big-data,bots,business,","session":"A"}']

Especially as more companies begin to ride this new wave of machine learning, it won’t be long before they’re leveraging their machine learning capabilities to transform ineffective people management processes. The benefits are twofold: First, machine learning has the ability to eliminate inherent workplace biases; and second, it can help prompt managers to provide the right feedback and recognition to the right employees, helping maintain a positive culture and retain good employees.

Problems with people management today

More than half of executives today believe that their current performance management approach is not effective in driving employee engagement or high performance. Additionally, managers account for at least 70 percent of the variance in employee engagement scores across business units. Only 30 percent of U.S. workers are engaged, demonstrating a clear link between poor managing and a nation of “checked out” employees.

AI Weekly

The must-read newsletter for AI and Big Data industry written by Khari Johnson, Kyle Wiggers, and Seth Colaner.

Included with VentureBeat Insider and VentureBeat VIP memberships.

In addition to those challenges, inherent biases linked to gender, age, well-liked employees, and more continue to be a huge problem in the workplace. Earlier this year, it was reported that companies need to make retention of female employees a priority, especially with 56 percent of women in computing jobs leaving their positions at the “mid-level” point. Additionally, women are 20 percent less likely than men to say they get management feedback that helps them improve their performance.

Making humans better managers

With the use of machine learning, companies can ensure that these biases in the workplace, whether inherent or on purpose, are eliminated. Machine learning already has the opportunity to make an impact on people management. Companies like Accenture, SAP, and Deloitte are trading in their traditional performance management ratings and rankings systems for technologies that bring transparency to data around the work employees do. This creates huge opportunities to leverage data to provide the right assessment of employees and get a holistic picture of what’s driving work. As this data surfaces, so does the ability to apply machine learning to turn managers into effective coaches.

In today’s work environment, managers seldom focus their energies on coaching employees continuously. Yet feedback and recognition are most effective when they’re given instantly with appropriate context and specificity. Waiting until the end of the year introduces different biases focusing on recent wins or only well-liked employees. Instead of basing these things on the personal biases of a manager, a machine learning tool that collects data surrounding an employee’s actual work prompts managers to give that constructive criticism or praise when it’s relevant and warranted.

Machine learning can help humans become better managers by removing any biases a manager might have. With machine learning, employee performance is backed up by raw, inarguable data that shows how employees are actually performing. By taking advantage of this rich repository of data, managers can better recognize which employees are achieving important goals. In turn, they can provide appropriate feedback without relying on their personal opinions.

With its ability to eliminate bias and prompt a data-driven approach to feedback and recognition from managers, machine learning can completely transform the workplace by making coming to work an engaging experience for every employee — no matter their age, race or gender. Employees shouldn’t have to worry about the personal biases of their managers. Instead, they should focus on progressing toward their goals and improving their work. On the flip side, managers should focus on giving better feedback and recognition to guide employees toward success. People management needs to keep up with today’s fast-paced digital age, and with help from machine learning technology to make humans better managers, it won’t get left behind.

VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Learn More