This Technology Can Help Leaders Better Understand Their Employees Natural language processing technology may be the key to making leadership development a science.
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In today's workplace, the nature of communication is undergoing a profound shift. While we often assume that ubiquity of technology is driving us apart, LinkedIn's 2018 Workforce Learning Report suggests that interpersonal communication is the most in-demand soft skill today. And in an era where workers must collaborate with at least 10 people every day to get things done, it should be no surprise that communications is a leading factor in a company's success.
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Historically, measuring and improving the way people communicate within organizations has presented executives with a Gordian knot of complexity. But, as corporate learning and leadership development move online, organizations can follow the digital breadcrumbs left behind peer-to-peer interactions spot untapped leadership potential, or gauge employee sentiment with respect to the launch of new initiatives.
The process is rooted in the advent of natural language processing technology, also referred to as "discourse analysis," which is the study of relationships between naturally occurring connected sentences, spoken or written.
Companies that utilize digital tools to activate strategies or facilitate structured dialogue as part of leadership development efforts can, for example, mine the data produced by natural language processing to better understand leadership dynamics, influence and culture. This isn't about listening in on private conversations or identifying individuals by name, but over time, patterns emerge, helping executives to spot unintended consequence, and make more informed decisions. It can help executives to unearth sentiment that shows how their communications are perceived by cohorts (e.g., segmented anonymously by role or geography) within their company. And with over 84 percent of companies embracing the importance of "people analytics," it's more important than ever to understand natural language processing and how it works. Here's why:
It fosters transparency.
A recent study showed that a majority of workers (66 percent) believe that digital technologies and AI can give rise to a more transparent workplace. Transparency means more accountability and less office politics, which can, in turn, make employees more productive. With the help of natural language processing, leaders and talent management can establish clear career paths and expectations with a precise system to assess performance. This kind of transparent feedback loop is great because it doesn't put employees -- for example, introverts, who are often overlooked in the promotion process -- at a disadvantage.
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It's non-intrusive and effortless to deploy.
One of the reasons why natural language processing algorithms are impossible to manipulate is because they run quietly in the background while employees go about their daily work. Unlike traditional training programs that take employees outside their daily routine, analytical platforms don't rob employees of precious time; instead, it observes workplace behaviors, serves gentle reminders on key skills like collaboration and can be implemented in less than a day to boot.
It eliminates bias.
Communications within and across organizations often reflect implicit and structural bias, resulting in processes that are more subjective than they are meritocratic. Leaders often pick who they want to promote based on unconscious biases. By implementing tools that derive insight from the interactions of employees using natural language processing, leaders can generate a blind view of who is contributing the most creative ideas, who casts the largest net of network influence and who has the ability to inspire their teams. The insights gleaned can help them engage and retain the best employees, regardless of gender, race or culture, to avoid lousy morale and expensive turnover.
Amid a hyperconnected workforce, the flood of new workplace communications apps provide a familiarity with the sort of communications that enable back end natural language processing, implemented strategically, will continue to demonstrate value.
