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It’s a harsh reality. The majority of employees are toiling away at their job, unengaged and lacking motivation due to the absence of a strong sense of purpose. According to research by Gallup, the majority (51%) of US workers do not feel engaged at work. Gallup has dubbed the state of affairs an “employee engagement crisis”—and for good reason. Highly engaged business units realize a 21% improvement in profitability. Engagement also has a significant impact on employee retention, with highly engaged employees being 87% less likely to leave their companies. Given these lucrative upshots, it’s no surprise that employee engagement is one of the biggest challenges confronting businesses. To tackle the problem, many forward-thinking companies are turning to AI.
Far too often, organizations and HR departments rely on “pulse” engagement surveys, often conducted on an annual or quarterly basis to assess engagement. Typically known for being lengthy and mundane, these surveys neither stimulate nor excite employees, squashing the odds of motivating the most thoughtful responses. What’s more, the surveys’ strong reliance on scaled responses (for example, “neutral”, “agree”, “strongly agree” ratings) tend to be difficult to interpret and have limited use in terms of unearthing deep insights. Moreover, given the fact that HR professionals spend weeks interpreting the data and delivering it to employees, results quickly become lagging indicators that fail to reveal the current state of affairs.
AI can move waters in terms of gauging employee engagement in real time. AI is able to leverage natural language processing and sentiment analysis to unearth employee morale and engagement. What types of language phrases do employees use in text-based conversations such as email? What types of emojis do they use on platforms such as Slack? These factors are revealing. Consider Keen, a platform that sifts through employees’ anonymized emails and uses sentiment analysis to serve up a real-time snapshot of engagement.
AI even has the potential to assess biometric data—fingerprints, eye scans, and similar data—to assess engagement. This data empowers HR professionals to engage in swift action and surface the type of personalized recommendations that could never be gleaned from traditional annual engagement surveys.
Learning and development
Organizations that provide employees with compelling and impactful learning and development opportunities have a leg up on their peers. Millennials have an especially strong desire for learning and development opportunities. A staggering 87% of Millennials state that professional development or career growth opportunities are very important. Moreover, 40% of employees who don’t receive sufficient job training subsequently leave their positions within the first year.
AI has unprecedented potential to offer targeted and personalized recommendations in terms of learning and development. AI is able to pinpoint which employees have the potential, based on hard and soft skills and motivational factors, to advance to specific leadership positions. AI is then able to suggest optimal learning that can help employees advance and reach new heights.
Research has revealed that the time spent by managers and employees in collaborative activities has ballooned by 50% or more in the past two decades. Strong performance in any work setting depends on collaboration. Too often, teams are formed with little thought as to skillets, motivational factors, and previous performance. Workers have different work styles and this needs to be accounted for when forming teams. Effective collaboration pays enormous dividends. Research has shown that companies that promote collaborative working are five times as likely to be high performing.
AI can also be a powerful force in assessing employee motivation and leveraging results to determine optimal team composition. Already, AI can determine what specific factors motivate specific employees and inform managers as to how to best motivate teams. Attuned, for example, uncovers the motivational factors impacting employees. The company has isolated 11 motivational factors that drive work culture, including altruism, autonomy, and competition.
Engagement is top-of-mind for all recruiters and companies must feel compelled to double down on their focus on AI as it relates to employee engagement. But AI adoption and embracement should not be taken lightly. Especially in the case of engagement, tools must be evaluated with a critical eye towards privacy concerns, biases, and effectiveness. Most importantly, employees should be part of the conversation in terms of whether these tools ought to be part of their workplace milieu.
July 5, 2019 at 11:53AM
Forbes – Entrepreneurs