Human capital is one of a company’s most valuable assets – and likely its largest operating expense. Business leaders are keen to ensure their organizations retain employees to maximize productivity and profitability while minimizing costs associated with employee turnover.
According to Gartner's research, a departing employee costs an organization an average of $18,591, including recruiting and onboarding their replacement. Despite this reality, many organizations struggle to pinpoint why employees decide to stay or go. But there is a solution: partnering with HR leaders to use data analytics can provide unique insight into the factors influencing employee retention. As a result, financial leaders can better strategize around improving this critical area of organizational structure.
The Importance of Partnering with HR
Gone are the days when HR was merely seen as a transactional function of the business, with CFOs and CHROs operating in silos. With the digital transformation underwar, CFOs and CHROs are evolving their relationship to become more symbiotic than ever before.
According to Forbes, the great majority of finance leaders see collaboration with HR as key to enterprise strategy, although just 55% say the level of collaboration meets their ideal expectations, meaning there is room to grow this area of organizational partnership.
Today, savvy HR professionals leverage data analytics for their human resources information systems (HRIS) to make smarter, more strategic, data-backed talent decisions. By partnering with HR to use those analytics, CFOs can gain valuable insights into employee turnover that will help them improve their retention rate and optimize the performance of their workforce.
Using Data to Understand Employee Turnover
Understanding why employees are leaving and who is most likely to take flight can be a major asset for employers. Recognizing these patterns can help organizations better understand employee motivations and create effective strategies to meet needs. With thoughtful analysis and proactive approaches, companies can ensure that their employees remain invested, engaged and committed for the long haul.
Let's look at a few questions data analytics can help answer.
Why Do Employees Leave?
HR often collects data on employees' reasons for leaving during exit interviews. If employees cite low pay, no opportunity to advance or lack of flexibility, this understanding can allow CFOs to make changes that will improve retention.
Additionally, data analytics identify common trends related to resignations, such as employees leaving within their first year of employment or employees recruited from specific competitors.
Do We Have High Turnover Departments or Regions?
Data analytics helps pinpoint areas of the organization with high levels of turnover. For example, a specific department or geographical region may have exceptionally high turnover rates. Executives can look for the root causes, such as a manager whose approach should be addressed, or compensation that doesn't align with the local market.
What Future Trends Should We Be Aware Of?
Predictive analytics, which uses current and historical data to provide insight into future trends, can provide a powerful tool for organizations looking to forecast future hiring and retention challenges.
For example, predictive analytics might evaluate which employees are most at risk of leaving or help narrow down job candidates to people most likely to thrive in a particular position. This allows CFOs to identify potential issues early, assess short- and long-term labor needs, and plan for risks and opportunities.
Making Improvements Based on Data
As CFOs become aware of the differences in employee experiences and the root causes of why they stay or go, they have a unique opportunity to embrace change to sustain their organizations moving forward. By teaming up with HR leaders, CFOs can help create tailored retention strategies to bolster employee loyalty.
Those data-driven improvements might include:
Making Better Hiring Decisions
People analytics can assist in identifying and recruiting the right talent for an organization through algorithms that evaluate candidates based on various factors, including their performance on past job interviews, educational background and skills. Using these algorithms, employers can increase the accuracy and consistency of their hiring decisions, ultimately identifying top talent — and talent that's more likely to stay.
Offering Competitive Compensation
Many organizations rely on compensation surveys to determine appropriate employee salaries. However, during the Great Resignation, historical salary data quickly became outdated. In fact, according to ADP, Americans who changed jobs during the Great Resignation saw their pay climb by 16.1% on average — a trend few salary guides could have predicted.
Basing salary offers and raises on historical data alone can lead to gaps between employees' worth and their existing compensation, which creates an opportunity for competitors to lure talent away.
By leveraging data analytics, organizations can better understand the current market rate for certain positions and make more informed decisions about employee compensation and performance-based incentives, such as bonuses or commissions.
Improving Work Culture and Workplace Environment
Finally, CFOs can also use data analytics to identify other factors impacting retention rates, such as the quality of the office environment or overall company culture. Through surveys and focus groups with employees, they can better understand what's working well and what areas need improvement, helping to create a more positive and productive work environment.
Developing Training Programs Tailored to Individual Needs
Pulling data from employee surveys, performance reviews and other sources can help organizations identify gaps in skills, knowledge or overall performance. They can use this data to design their learning and development programs accordingly.
By proactively addressing learning and development, organizations can improve overall workforce performance and profitability and enhance the ability to attract and retain highly skilled employees.
Helping Reach the Organization's Diversity, Equity and Inclusion Goals
Data analytics can also allow employers to gain valuable insights into the composition of their workforce and identify areas where diversity, equity and inclusion are lacking.
For example, by analyzing data on hiring patterns, employers can identify areas where their recruitment process may inadvertently exclude certain groups from applying for open positions. They can then take steps to address these biases and improve the diversity of their workforce.
Organizations are increasingly turning to data analytics to better understand and predict employee behavior. By partnering with HR and utilizing data-driven insights, CFOs can improve their organization's ability to identify and recruit top talent and design more effective retention strategies. If you need help collecting or interpreting that data, connect with a member of our team.
Copyright © 2023, CBIZ, Inc. All rights reserved. Contents of this publication may not be reproduced without the express written consent of CBIZ. This publication is distributed with the understanding that CBIZ is not rendering legal, accounting or other professional advice. The reader is advised to contact a tax professional prior to taking any action based upon this information. CBIZ assumes no liability whatsoever in connection with the use of this information and assumes no obligation to inform the reader of any changes in tax laws or other factors that could affect the information contained herein.
CBIZ MHM is the brand name for CBIZ MHM, LLC, a national professional services company providing tax, financial advisory and consulting services to individuals, tax-exempt organizations and a wide range of publicly-traded and privately-held companies. CBIZ MHM, LLC is a fully owned subsidiary of CBIZ, Inc. (NYSE: CBZ).