How AI-driven sentiment analysis can enhance employee satisfaction
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With tech talent in short supply, companies are desperate to hold onto top performers. However, many are losing ground. Employees are sticking around for much shorter periods than they used to.
What can you do? Sentiment analysis combined with artificial intelligence (AI) is being harnessed to help companies in a number of ways: Discovering how employees feel about their work environment, how effective they feel training and skill development initiatives are, and what their concerns are, and how to spot danger signs, identify signs of burnout, identify indicators of job dissatisfaction, and prevent employees from jumping ship rivals.
Retention misery
The average tenure of a U.S. employee ain’t what it used to be. Joining the firm was once almost considered a lifetime commitment. Since the 60s, though, the average length of stay has dwindled. According to the U.S. Bureau of Labor, the current average is only 4.1 years. In some companies it is much lower.
“We’re going from older generations that joined the company out of college and spent their career with us, to younger generations spending 2.8 years on average and moving on,” said Andrea Legnani, global head of alumni relations at Citi.
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A study by CyLumena found tenure even shorter among high-ranking security executives — 18 to 26 months. Multiple factors may be behind the shift. Younger generations appear to feel less loyalty to their employer. A steady diet of layoffs after every downturn hasn’t helped. Entry-level personnel, too, are happy to move around from job to job in their 20s and sometimes even into their 30s as they don’t intend to start families until they are older and need to settle down. Further contributing elements may include the Great Resignation, quiet quitting, or overwork due to operating with lowered headcounts. But burnout may also contribute, particularly in IT fields such as cybersecurity.
A recent survey from Heidrick and Struggles found that the two most significant risks chief information security officers (CISOs) face relating to their role are stress and burnout.
“CISOs cannot progress when they are stuck fighting fires,” said Yoran Sirkis, cofounder and CEO of Seemplicity, a risk management and productivity platform. “With an average backlog of more than 100,000 vulnerabilities at any given time, there is an industry-wide issue of security teams racing to catch up.”
A study by the A.Team and MassChallenge 2022 Tech Work Report surveyed almost 600 tech founders and executives to provide insight into the future of work in the tech industry. Product and engineering roles were cited by 39% of employers as the most challenging positions to fill. In addition, 62% of respondents said it took them more than four months to find the right talent to fill these vacancies. Nearly half (44%) said they had lost a significant amount of their top-performing employees to the Great Resignation.
Sentiment analysis and employees
Clearly, all is not well in the land of personnel. What will it take to fix?
“Leaders must develop a much deeper empathy for what employees are going through and pair that empathy with the compassion to act and change,” said Aaron De Smet, a consultant at McKinsey. “Only then can employers properly reexamine the wants and needs of their employees and begin to provide the flexibility, connectivity and sense of unity and purpose that people crave.”
One tool to help create that sense of empathy is AI-based sentiment analysis. HR departments and managers can use it to discover how fulfilled employees feel in their jobs and to connect organizations more intimately with the workforce.
“Sentiment analysis can help gauge how employees are feeling at any given point in time,” said Sameer Maskey, Ph.D., founder and CEO of AI talent platform Fusemachines.
Surveys can help determine how employees really feel about their workload, their career trajectory, the pros and cons of organizational culture, the teams they work with and their managers. They can be used to determine how well employees feel management responds to their concerns. With enough feedback, as well as data from other sources, historical data from within their organization as well as industry data, AI systems can predict those considering departure, those showing the early stages of burnout, and discover who is satisfied or dissatisfied with their jobs and with the company.
“AI systems can also be trained to identify words or phrases in emails, work group chats or public employee forums that express dissatisfaction,” said Maskey. “Using these insights, HR teams can stay a step ahead and launch initiatives that boost employee morale and foster engagement.”
Mercer’s 2022 Global Talent Trends Study makes it clear that employee sentiment has everything to do with how organizations are perceived. 80% of C-level executives think it is essential that organizations become open and easy to relate to.
“Companies that fail to listen to their employees and other stakeholders and perpetually adapt will lose the ability to raise capital, attract and retain talent, and stay relevant,” said Ilya Bonic, head of strategy and president of career for Mercer. “Companies could be doing more in terms of offering a holistic and inclusive well-being strategy that meets the needs of a multigenerational and diverse workforce.”
Bonic suggested that companies find ways to adapt more easily to changing values of customers, employees and investors. For example, 96% of employees expect their employer to pursue a sustainability agenda. Further tips include rewarding employees for their efforts, establishing programs to spot and limit burnout, offering to reskill employees on the company dime, and providing more opportunities for career development.
Skill development and sentiment analysis
Employees, these days, want to know that a company will look after them. One of the ways this shows up sharply is in the training and upskilling programs available.
The Skillsoft survey found that 97% of IT decision-makers agreed that certified staff add value to the organization.
The survey cited training benefits such as improved quality of work (56%), increased engagement (41%), and faster job performance (36%). While 26% said that not enough was being invested into training, the survey unearthed some contradiction. Managers stated the main reason for any lack of technical training to be the lack of a need for it. This is clearly an area where sentiment analysis can add value by understanding management reluctance and highlighting how important career and skill development pathways are to employee retention.
Additionally AI help better understand which departments indicate the strongest demand for growth and learning. Instead of broad training efforts, sentiment analysis can zero in on the areas where reskilling, training and upskilling programs will provide the most benefit. Further use cases: finding out who agrees that the company offers the chance of tangible career advancement, who feels their career has stagnated, and which employees could benefit from a bigger challenge. The insights provided by AI-based systems can be used to prioritize learning and engagement programs, plan ahead for potential areas of turnover, and keep one finger on the hot buttons within the organization.
“Management and HR can use sentiment analysis to stay one step ahead with regard to the organization’s state of employee engagement and satisfaction,” said Maskey.
Offboarding and sentiment
Offboarding is another area that can positively or negatively impact how a company is perceived. Sudden firings and layoffs, perfunctory exit interviews, immediate revocation of security privileges, rude statements from managers and treating leaving like a betrayal are all ways to leave a negative perception. Internally, colleagues may feel aggrieved about how someone was treated and may reconsider their own loyalties. Externally, word gets around about how a company treats people.
Offboarding, therefore, is due for a shake-up. It can be harnessed to create long-term value and boost corporate image and employee sentiment. A report, “Turn Departing Employees into Loyal Alumni,” unearthed the fact that 80% of former employees expressed a willingness to return and that 20% of open jobs are being filled by alumni. If this talent goldmine is tapped, jobs are filled 50% faster and the new hires get up to speed 73% faster.
“A well-managed offboarding process can turn employees into loyal alumni who become customers, suppliers, boomerang employees, mentors to current workers, and ambassadors for the firm,” said Erin E. Makarius Associate professor, University of Akron, one of the authors of the report.
He suggested that exit interviews should be used to recognize people’s contributions, provide tailored support for the transition, and brief them about programs that can keep them connected to the organization. Alumni platforms such as EnterpriseAlumni and PowerHouse can underpin offboarding with technology to manage and engage an alumni community. AI and sentiment analysis can be combined with such tools to find reasons why people left in order to improve retention, monitor the degree of engagement in the community, and discover how they feel about rejoining at some point should circumstances change.
“There is real value in maintaining a connection to former employees, whether for recruiting, referrals, sales, business development, or as brand advocates,” said James Sinclair, CEO, EnterpriseAlumni.
Financial services giant Citi, for example, maintains a close connection with alumni. “As much as people are more willing to leave, they’re also more willing to return,” said Legnani. He added that about 10% of the Citi employee base are boomerangs. That’s 20,000 employees out of the company’s current workforce of 200,000 have returned to the company after leaving for pastures new. Engagement can be further fostered by using former personnel to mentor interns and new hires. Retirees can be given consulting work. Others may want tax forms, to take advantage of learning opportunities, and find avenues for community involvement, networking, social support, partnerships or referrals.
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