Employee-manager relationship is the glue that binds an organization. Hence estranging this vital relationship results in attrition and negative comments trending on social media platforms in no time.
Companies invest up to 6 to 9 months’ salary in replacing a salaried employee. Most important are the below costs:
- Floating advertisements on multiple platforms
- Time required for screening and interviewing new candidates
- Onboarding of new employees, including training costs and time investment
- Loss in productivity resulting from loss in engagement
Due to these factors, an average employee spends 3 to 4 months in a company before her/his contribution starts to outweigh the hiring cost.
The Center for American Progress estimates that companies invest 20% of the annual salary of a mid-senior employee to get a new candidate on board. Apart from the above-mentioned figure, the overall cost involves several intangible and untracked components.
Companies can bear the financial costs, but the reputational damage due to poor review and bad word of mouth still tarnishes their image.
So what is the way ahead? How can organizations counter this problem?
How to reduce employee turnover? Can it be analyzed and predicted?
Often the management is left clueless as to why the company’s top performers resign unwarrantedly. The question that frequently comes to their mind is “Could we have spotted anything before the employee resigned?” or “Could we have taken necessary steps to prevent such an unforeseen situation?”.
The answer is yes – it can be done through the implementation of predictive workforce analytics.
Predictive analytics is the use of statistical and algebraic techniques to identify the likelihood of future outcomes based on historical data. Predictive workforce analytics uses employee-related data, allowing leaders to improve the effectiveness of people-related decisions and HR strategies. This helps the management predict unforeseen situations, and adopt suitable workforce strategies to reduce attrition risk, resulting in longer-tenured high performing employees.
A 2015 EIU survey found that 82% of all organizations plan to either begin or increase their use of “big data” in HR over the next three years. Many companies have already adopted this trend:
- Cargill, Gap, IBM, Johnson Controls, and SAS have already adopted the use of predictive workforce analytics to select better employees while hiring, identify critical employees who are at risk of leaving the organization; and use social media to get a real-time understanding of employee engagement.
- Data from LinkedIn and other social networks have proven to be very effective for pharma and software companies in predicting ‘high-flight-risk’ employees among their high-potential staff.
- MasterCard is developing predictive models directed at improving the employee experience through a range of data sources.
CEOs are gradually recognizing the importance of using employee-related data to manage recruitment, retention, turnover, and other processes. The SHRM Foundation has identified the increased use of workforce analytics as the future trend for all types of businesses. As Elissa Tucker, Research Program Manager of Human Capital Management, APQC rightly puts it:
“It’s no longer a question of ‘if’ companies will utilize predictive analytics for workforce challenges, the question is, when”
Read more about the challenges of implementing analytics projects in
Change Management for Effective Data Analytics!
Key Applications of predictive workforce analytics
Some key applications of predictive modeling in HR include:
Forecasting recruitment needs
Forecasting recruitment needs optimizes resource utilization and sustains appropriate growth and margins, by predicting requirements for HR capacity. This helps HR managers to develop plans for recruitment, training, and infrastructure development.
Loyalty and attrition analysis of Employees
Loyalty and attrition analysis increases employee retention, by calculating an attrition risk score for individual employees, thus helping organizations to prevent the potential attrition of high-performing employees and ensure business continuation.
Employee segmentation and profiling
Accurately segmenting and profiling the workforce helps in talent management. Organizations can understand the workforce better and take initiatives tailored to fit employee requirements by segmentation of existing employee base.
Suitable recruitment profile selection
High-cost employee attrition leads to significant losses for the organization. The HR decision-makers can arrive at the right profile for each potential employee after analyzing the data for current employees, including performance and productivity indices, attrition details, and lifetime value.
Employee sentiments analysis
Employee sentiment analysis is far more effective than the results yielded in annual employee satisfaction surveys because it tracks, and analyzes topics that are most relevant to employee sentiments over a period. The analysis can later be extended to a near real-time process and promote an understanding of employees' perception of an HR initiative, policy, organizational change, or event. Internal data, as well as external data from social media platforms such as Facebook, Twitter, and LinkedIn, can be used for this analysis.
Widely used predictive workforce analytics tools
Companies see analytics tools as the way forward, as they help mitigate potential workforce troubles. Many firms make use of an assessment tool called Predictive Index (PI) that generates the behavioral profile of an employee and provides an accurate depiction of her/his work preferences among others. This helps HR departments predict, plan, justify and formulate decisions to improvise the bottom line.
It is always advisable to act rather than react. Due to predictive workforce analytics tools, organizations can easily read attrition signs in employees and gain full control of retention.
Predict accurately: Retain your employees
It is imperative for HRs to adopt analytics and predictive techniques to retain their employees, who are an organization’s biggest asset. Predictive analytics helps in two ways. On the one hand, it limits HR costs, while on the other hand, it helps develop a high-performing workforce.
As a result, it will be vital to base HR decisions on analytics in the coming times.
“The HR organization in the future will not be about administrative work; self-service and automation will take care of that. HR will be business partners that consult with the business, all based on analytics. HR will make the link between HR analytics and profitability.”
– Lynn Taper, Worldwide Director, Human Resource Operations, Global HR, Colgate-Palmolive
