Machine Learning Can Help Executives Better Understand Their Employees

How Machine Learning Can Help Executives Better Understand Their Employees

In today’s working environment, the nature of communication is undergoing a serious shift. Some of us think that technology is driving people apart, however, according to LinkedIn’s 2018 Workforce Learning Report shows that interpersonal communication is one of the most in-demand skills. In a time where employees must collaborate with 10 or more people every day, it is no surprise that communication is the main factor in one company’s success.

Measuring and improving the way people communicate within companies can presented business owners a complexity. As a leadership and corporate learning development move online, companies can follow the digital trends and reveal leadership potential.

Organizations that use digital tools to start a structured dialogue or activate strategies as part of leadership development efforts can mine the data produced by language processing to understand influence, leadership dynamics, as well as, culture.

I’m not talking about listening to private conversations but finding a way to detect unintended consequences and make better decisions. It can help entrepreneurs to determine sentiment that clearly shows how their communications are segmented by geography or role. With over 84% of companies understanding the importance of people analytics, it is essential to understand machine learning and natural language processing technology and how it works.

Here are three reasons why:

1.It is Effortless to Set Up and Expand

machine learning outines and their daily responsibilities

One of the reasons why machine learning and natural language technology are impossible to manipulate is because they work quietly in the background while workers go about their routines and their daily responsibilities.

Unlike traditional techniques and training programs that take workers outside their comfort zone and daily routine, analytical platforms don’t affect employees’ time. Instead, it analyzes workplace behaviors, observes their habits, serves reminders on important skills and can be implemented in less than a day.

In other words, it is non-intrusive and pretty easy to deploy.

2. It Promotes Transparency

One study showed that a majority of workers believe that new digital technologies and Artificial Intelligence can give rise to a more productive and transparent working environment. Transparency means fewer office politics and more accountability which, can turn employees more effective and focused on their responsibilities.

With the help of machine learning algorithms and natural language processing technology, executives and talent management can determine clear career expectations and paths with an accurate system to access overall performance.

This kind of feedback is great because it doesn’t put employees at a disadvantage. For example, introverts who are neglected in the promotion process.

3. It Eliminates Prejudice

Communication within organizations usually reflects structural bias which results in subjective processes. Executives usually choose who they want to promote based on biases.

By adding tools that obtain insight from the personal interactions or workers using natural language processing technology, leaders can generate information of who is contributing the most effective and creative ideas, who can inspire their teams, and who casts the net of network influence. This information can help leaders engage and retain the best workers, regardless of race, gender or culture and avoid expensive turnover.

Thanks to machine learning and natural processing technology, leaders can implement better strategies and demonstrate value.

Artificial Intelligence, however, can also help leaders make better decisions.

Decision-making is one of the tests for leadership, especially in new leaders and entrepreneurs. Even experienced business owners who have a track record of fast and sound decision-making have made a poor decision that damaged their reputation.

The good news is that AI is unlikely to make it easier for leaders and decision-makers as they will be required to input judgment in the machine information and predictions. There are ways in which Artificial Intelligence is set to affect decision-making.

➢ Prediction:

Through data mining, organizations are using predictive analytics to make better business decisions. Predictive analytics allows companies to anticipate and predict events by looking at a data set and trying to guess what will happen in the future. For example, which ads should be served based on potential ROI and cost-effectiveness, how to optimize the buyer journey, how achievable are the end goals?

➢ Multi-tasking:

When making tough decisions, leaders need to look at different factors. If there is too much information to be considered, the executive might get overwhelmed, leading to bad decisions. A machine can handle multiple inputs without confusion or exhaustion. All that is needed is a set of programs that guide the machine and implement the best decision.

➢ Deciding who gets the job:

To find the best person for the job, the manager needs to go through the applicants and interview each one individually. If there are so many applicants no one has the time to do that. AI has. Soon, HR will be able to select the best workers from all applicants by automating most of the duties that make the process inefficient. Machine algorithms will go through the CVs to find the best candidate.

While machine learning and AI might not make the process simpler, it is going to contribute towards better decisions and an agile organization.

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