Introduction
A human resource practitioner might think that predictive analytics is an idea not suited for workforce planning and management. Well, that is not true at all. In fact, by applying predictive analytics, companies gain a more impactful and resourceful workforce.
So, what does predictive analytics mean to the human resource department?
Predictive analytics is the use of historical and current statistical data to identify patterns that can be used to predict the future and take action to specific events. This helps policymakers address potential gaps in the workforce and other issues affecting supply and demand in future.
Application of Predictive Analytics
Predictive analytics uses algorithms that can be applied to critical areas of workforce management. These include:
Recruitment
Predictive analytics automatically searches talent, identifies and unpacks applicant resume. It also carries out a background check on the applicant through social media platforms for positive indicators or flags. Finally, it automates shortlisting of candidates; in this process it considers gender equality creating a balanced working environment. All these save the company the high cost of recruiting and brings efficiency in the whole process.
Retention
To avoid flight risk, predictive analytics monitors, alerts and create compensation plans for over-performing employees who have not been identified by the company. For security and productivity protocols predictive analytics also monitor and track employee behaviour.
Employee management
Predictive analytics plays the role of Identifying skill gaps for training, it also benchmarks and tracks performance and lastly identifies and monitor employees performance in preparedness for succession planning.
Metrics Used by Predictive Analytics
For a successful workforce, HR needs to measure these three key things: efficiency, effectiveness and outcomes. They are the most failsafe metrics for productive, robust and intelligent HR predictive analytics.
Efficiency
When doing mass recruitment or when HR is having high frequent hires, efficiency is critical. Predictive analytics calibrates future delivery criteria, current standards and previous hiring data records for better monitoring and auctioning. This gives a clear path for HR to move forward and achieve the best benchmark.
Effectiveness
Data means nothing without quality. With productivity, output, cultural fitness, and future leadership potential in mind, predictive analytics helps HR conduct regular assessments of hiring. This makes them better understand employee performance and improvise employee roles where they deem fit.
Outcomes
Predictive analytics helps an organization check the employee’s tenure compared to the company’s investment in the employee in terms of training and compensation. It also helps to check the employee’s contribution to the general performance of the company, and finally by checking the daily tasks of a team or an employee and how it influences the profitability of an organization.
All these helps HR to understand the outcome and what action to take in the future based on the previous results and analysis conducted. This means a focused and concentrated action to projects, teamwork, and collaboration and more alignment to the organization’s goal.
Use Cases of Predictive Analytics
By applying predictive analytics in workforce planning and management, HR empowers the organization leadership to understand possible talent and future outcomes. Here are key applications of predictive analytics for workforce planning and management.
Capacity training and development
Internal training has been said to be a major employee retention strategy, with predictive insight at hand, an organization can do frequent capacity building for their employees by analyzing workforce data to determine the areas of lack in skill. Furthermore, predictive analytics can be used when doing employee promotion and demotion. By having a historical performance of employees, HR can easily tell which employees to promote for their performance, what kind of training to perform and which areas they can downsize or hire.
Hiring talent
Great employees mean great success for any organization. Using predictive analytics, to check backgrounds and outline strategies can help HR predict the most suitable talent. Historical data and hiring assessment can largely help to identify fitment.
Retention
Predictive analytics can help organizations predict employee duration as dictated by the market and internal parameters of an organization. Training predictive models to identify divergent or deviant patterns of an employee can help the organization cut and save costs spent on training and retaining employees. Furthermore, an organization can use predictive analytics to identify and address flight risk. It analyzes the factors that are potential accelerators of employee flight risk thereby making the organization proactive before flight risk happens.
Deeper engagement
Companies use tools like Gusto to map out a general organization ‘happiness quotient. It uses predictive analytics to monitor and predict employee behaviour and therefore actions like employee motivations, appraisals can be done to tweak workforce practices and improve communication.
Productivity and performance
Key insights like up-skilling outcomes, employee competition, potential leadership candidates and mentorship fitness et cetera can inform HR which candidate qualifies for which program.
Predictive analytics in HR plays a crucial role in boosting performance. After identifying the most qualified candidate, HR professionals can put focus on the employee and install mentorship programs. They can be monitored by using analytics to assess progress, performance, loses and wins.
Examples of Predictive Analytics
Google predicts hire success
Google applies HR predictive analytics to estimate flight risk. One of the findings Is that new employee’s risk flight if they don’t get a promotion after 3-4 years. Laszlo Bock of People Operations (HRM), says that Google’s people operations in statistics are one of the most important instruments because in Google hiring process; the question are fully automated and fine-tuned to find the best candidate.
Best Buy predicts revenue engagement numbers
Research has it that employees who are engaged are less likely to quit, work the hardest and deliver the best quality. Buy best found out that a 0.1% increase in engagement translated to an increase of revenue by over $90,000. By measuring engagement multiple years, it enabled Best Buy to measure engagement drivers and in turn, they came up with action plans to increase engagement which in the long run increased revenue tremendously.
Conclusion
Predictive analytics is here to stay. Predictive analytics solutions have been hugely accepted by HR professionals. It has brought profound insight into workforce planning and management and contributed to the increasing value to an organization’s bottom line. Using important metrics of data to measure HR predictive analytics can change the way an employer’s plans and manages its workforce.
Topics in Predictive Analytics
- AI for Predictive Analytics
- Companies Using Predictive Analytics
- IoT and Predictive Analytics
- Predictive Analytics for Business Forecasting and Planning
- Predictive Analytics for Call Center
- Predictive Analytics for Sales Forecasting
- Predictive Analytics for Workforce Planning and People Management
- Predictive Analytics in Banking – Use Cases, Metrics, Examples and More
- Predictive Analytics in Health Insurance
- Predictive Analytics in Procurement
- Predictive Analytics Models
- Predictive Maintenance Analytics
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