Part 2: The Machine Learning Big Data Guide for HR #hrtechconf

big data, recruiters, hr

This is a two part series on machine learning and its use in human resources and recruiting technology. Click here to read Part 1. 

Leading with VUCA

VUCA is an acronym for the term volatile, uncertain, complex and ambiguous. It was first used by the United States military to discuss military preparedness. The term was later used by Bob Jansen of the Institute for the Future. VUCA is the perfect term to discuss the current state of business and the role human capital plays in the success of companies.

In the same Conference Board study mentioned in part 1 of this series, less than two-thirds of leaders said they were “highly confident” or “very confident” in their ability to meet the VUCA challenges. HR professionals echo this same feeling of uncertainty. They view their business leaders are not capable of meeting the challenges. Imagine how employees view the business leaders as well as the HR professionals who are building scalable talent management strategies. The point is that business leaders as well as HR professionals need to look towards technology that uses existing workplace data to help establish patterns of predictability.

Machine Learning in HR Starts With The Data

Even before it’s application in talent management, the field of machine learning has sought to answer the question “How can we build computer systems that automatically improve with experience? What are the fundamental laws that govern all learning processes?” The key to machine learning starts with the data. By collecting the data from users, whether it’s keyword searches, typed text via messages, online resources, classes viewed or people you are connecting with, this data helps machine learning make personalized and unique recommendations to further engage and develop yourself or a team.

I liken machine learning to the beauty subscription service, Birch Box. Paid subscribers complete information about their interests, hair color and skin tone. Based on the preference individual subscribers provide, Birch Box mails a box of sample sized beauty products like perfume, nail polish, and exfoliating cream every month. Birch Box subscribers pay a monthly fee to receive these suggested samples and are also provided a way to purchase them if they like the product they’ve been sampling. Machine learning creates a focused and specific contextual environment for the purposes of employee self-development, training, growth and learning.

The use of not just data, but actionable intelligent data, is important. Birch Box just like machine learning workplace technology use this data and preferences to customize and suggest products and/or learning opportunities that are unique to the individual, but also serve a larger audience with similar interests and characteristics. The success of Birch Box has launched an entire industry of personalized and customized product subscription services via mail. As customers and employees we are craving specialized products and environments to maximize our time whether it’s shopping for beauty supplies or completing an online learning training course offered by our company.

Machine learning uses complex algorithms to help determine what suggestions to activate you and your employees. The use of data in helping make an informed, and in this case a personalized experience, is one that resonates with business leaders. A reported 49 percent of business leaders agree that big data analysis results in improved decision-making. Only a fraction of HR teams take advantage of the treasure trove of data to help them make smarter and more predictive business decisions. Machine learning helps simplify use and application of the workplace data collected contained within a platform and environment that employees are leveraging for the purposes of knowledge share, personal information and development.

The data gathered looks at information and patterns in places we normally wouldn’t think to look. Experts like Josh Bersin are seeing companies make the connection between the importance of data in talent management. “Predictive analytics and how data can be used to help improve our focus and decision making, Bersin says. “Using resources and information we likely already have access too. It helps analyze and present the data in a way that helps to offer more than a gut feeling to a decision. Talent acquisition (and management) is finally focused on evidence based decision-making,”.

Set It, Forget It

Machine learning makes every individual team member or employee within your organization’s learning and development customized yet scalable. It operates in an environment of “set it and forget it.” The learning is ongoing and continuous relying on your own unique interests, interactions, and learning and connection points within your company.

Machine learning is the ultimate form of self-directed learning that combines with data and the knowledge of members of your company to make the best recommendations to suit your unique needs. Employees are empowered to take charge of their own learning and development instead of following a structured learning or corporate development program that is time consuming, expensive and rigid. Your employees are allowed to learn, grow and develop at their own fluid pace in a manner that is organic, time sensitive and suits their needs.

Best in class companies want a workforce that is focused, fulfilled and productive. The cost of turnover and replacing workers is an expensive one. Research from Managing Human Resources: Productivity, Quality of Work Life, Profits suggests that direct replacement of talent can cost as much as 50 to 60 percent of an employee’s salary with total costs associated with turnover ranging from 90 percent to 200 percent of annual salary.

Seamless Integration

The above referenced cost of turnover fails to address the additional millions of dollars each year employers spend on employee surveys, exit interviews and consultants in order to keep our employees happy, productive and engaged. With big data combined with machine learning technology, the answers do not solely lie with experts, but with our own employees and their interactions contained within workplace portals, systems and HR technology. With machine learning workplace technologies, business leaders do not have to choose between training or productivity. Machine learning provides the opportunity to work smarter not harder. It integrates a personalized employee learning experience into an existing workplace culture and uses existing resources to maximize your time, training dollars as well as decrease turnover at your company. The addition of machine learning improves your existing workplace ecosystem Moreover, it can be seamless integrated for t for employees, managers and business leaders alike.

This is a two part series on machine learning and its use in human resources and recruiting technology. Click here to read Part 1. 

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Jessica Miller-Merrell

Jessica Miller-Merrell (@jmillermerrell) is a workplace change agent, author and consultant focused on human resources and talent acquisition living in Austin, TX. Recognized by Forbes as a top 50 social media influencer and is a global speaker. She’s the founder of Workology, a workplace HR resource and host of the Workology Podcast.


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