“You take away our top 20 employees and we [Microsoft] become a mediocre company."
This statement underscores a huge problem in business today: employee turnover. Employees are the lifeblood of any company and one of the primary sources of strategic differentiation. Losing employees hurts a company in two ways. First, it costs money to acquire and train talent. Second, every employee defection results in non-tangible losses: customer relationships, new service or product ideas, and knowledge of internal processes just walk out the door.
So how do you improve the hiring process while increasing satisfaction for your top performers? Is the answer to “chip” employees, track their movement and days in the office to infer job satisfaction? I think not.
You have probably heard about predictive analytics and the highly impactful insights it can bring to strategic decision making. Now is the right time for companies to begin harnessing the transformational capabilities of predictive analytics in a line of business that often ignores advanced technology: Human Resources.
Until now, employees were hired based on in-person interviews, experience, and perhaps an intelligence evaluation like the Wonderlic test. In this scenario, with only limited data points and intuition, employees are onboarded and hiring managers assume the new employee can “probably do it” if given a chance and proper coaching. This process can be improved with predictive analytics and machine learning.
Like any line of business, Human Resources wants to drive more informed decision making. However, HR is generally not the home of data scientists and people with deep analytical skills, which inhibits the use of forward-looking analytics. But predictive analytics tools have evolved to the point where the development of models does not require a Ph.D. in mathematics and the output can be consumed by anyone.
What would it be like to ask a question in natural language, and have the analytics platform return results to you in visualizations that can be understood by people at all levels in HR, at a glance? With this approach, a company could more precisely pinpoint answers to questions like:
- Which employees are at the highest risk of leaving the organization?
- What are the drivers for job satisfaction?
- What skills are associated with the best performing employees?
- Which learning courses are likely to impact the company’s performance?
HR decisions in the areas of recruitment, benefits, training, and engagement strategies impact the performance of the entire organization. When HR can defend their decisions with analytical proof, they are seen as a trusted advisor by the leaders of that company.
The LRS Big Data and Analytics team has 20 years of experience in analytics and data warehousing, and have sold and implemented predictive analytics applications in verticals such as retail and insurance. If you are interested in understanding how predictive analytics can help you acquire and maintain a strong and engaged workforce, please fill out the form below and let us know how we can help.
About the author
Steve Cavolick is a Senior Solution Architect with LRS IT Solutions. With over 20 years of experience in enterprise business analytics and information management, Steve is 100% focused on helping customers find value in their data to drive better business outcomes. Using technologies from best-of-breed vendors, he has created solutions for the retail, telco, manufacturing, distribution, financial services, gaming, and insurance industries.