Introduction
Machine learning has changed the way businesses plan, work and breathe! It’s been here for quite some time now, and the estimated boost in productivity with its implementation has already touched 54%. While it ostensibly risks many jobs, it is here to give. Machine learning and automation are helping industries (healthcare, logistics, and more) gear up for digital transformation more enthusiastically than ever – and it still looks like the beginning. HR automation is one of the buzzwords in the business world that’s been headlining with machine learning for quite some time now. In research, companies that switched to HR automation said it saved 90% of their time in administrative functions. It’s for real. But how? Keep reading to know.
Table of Contents
HR Automation Using Machine Learning
Human resource management, famously known as HRM, used to be associated with shortlisting and payroll processes. With time, it accelerated the pace toward improving employee experience and retention. They then entered automation with machine learning that fueled the HR department to make almost everything faster and accessible.
HR automation refers to the practice of automating and streamlining HR tasks that are generally performed by human resources. This practice has dramatically improved how many HR activities were in motion. From the entire recruitment process to employee care, machine learning is giving a hand to HR by speeding things up.
How can Automation Make HR Efficient?
The human resource management department can save time and quickly wrap up essential or complex tasks by automating HR tasks. Automation serves a tremendous purpose in terms of efficiency and consistency. Automation can boost efficiency in HR management in the following ways:
- Faster Decision-Making: HR automation simplifies fetching, maintaining, and tracking data across different functions. It enables organizations to monitor and understand various processes more feasibly. It helps shortlist resumes, create reports, analyze employee experience, and make data-driven decisions in relatively minimum time.
- Transparent Processes: Automation in HR functions can enhance clarity between staff members and employees. It also promotes transparent communication across different HR processes of the organization. Moreover, automating workflows allows employees to modify or submit requests or documents more efficiently.
- Streamlined Workflow: One of the most significant advantages of HR automation is that every nook and corner of the workflow turns more organized, reducing the scope of error and lack of clarity. Automation allows the management to work systematically and maintain order, saving time and resources.
- Enhanced Productivity: By automating various processes involved in HR, management gets more time to devote to intricate tasks. Since employees can apply for leaves, raise a query, track attendance, and perform various tasks with automation, the need for manual efforts also reduces.
7 HR Processes that can be Automated
Here are the 7 notable use cases in HR processes that can leverage ML and AI systems:
1. Recruitment Procedure
The hiring process is one of the most significant aspects of HR management. HR automation with machine learning can boost this process tremendously by refining data per predefined requirements for a particular job role. According to Nucleus Research, companies that use HR automation made the onboarding process 67% faster.
Source: Lucid
Since this robust technology utilizes a database to store the profiles of candidates that the HR teams shortlist, it eradicates the need for paperwork. It helps hire top talent and saves time by automating communication about the interview status. Moreover, artificial intelligence in HR can also gear up the maneuvers of various formalities for onboarding new employees. From providing access rights and account creation for new hires to offer letters, it eases the entire onboarding process.
2. Payroll Functions
Source: UBSapp
Payroll is a common but not to mention, critical task involved in the HR department functions. After all, it is about processing payments and maintaining records in an organization, which demands keen-eyed attention to detail. No matter how demanding this activity may be, it is tedious and repetitive.
Payroll processing requires massive data entries regularly, which gets mundane in the end, and then it demands attention as it can lead to manual errors. Artificial intelligence and machine learning can prevent blunders by establishing a connection between different systems, such as accounts payable, employee data, attendance, etc., to collect data relatively streamlined manner.
3. Employee Data Management
Source: Jotform
Employee data management is one of the most crucial segments of HR management operations. It involves maintaining various databases, including employee perks, documents, and other records. Moving around databases and keeping track of them demands consistency. HR with AI and ML can give a hand in making the whole process of data management plain sailing. By automating these activities, the management can mark a reduction in common errors like data inaccuracy, further preventing reworks.
4. Attendance and Time-offs
Source: Mitrefinch
Tracking attendance is yet another eminent area in HR departments where machine learning and HR automation can serve a purpose to count on. Automation tools allow the option to cross-check the employee attendance reports against total work hours and significantly ease down the task of monitoring employee working hours. Apart from that, the management can also leverage automation in determining the need for resource allocation in case of an employee’s absence to maintain the workflow.
5. Expense Management
Source: Endeavour Technologies
Calculate shift allowance, track travel expenses, and do all things that translate to maintaining a record of expenditures! Yes, another monotonous and time-consuming task to mark territory in the calendar of HR departments. The worst and scariest side to this activity is all those scenarios of delayed expense submissions, missing receipts, no track of spending, and the list can go on.
The human resource department can save time with artificial intelligence, machine learning, and HR automation. Automation extracts crucial data from receipts and repeatedly wipes off the need for glaring into expenditure reports. It captures the information and makes the job get done faster. Moreover, it also saves time in the manual process of automatically generating shift allowances by fetching data from the backend.
6. Performance Management
Source: Spine Technologies
Performance management is no joke. It is an area of HR functionality wherein the department has to analyze and review an employee’s goals, targets, progress, and achievements. The department uses this examination to make essential calls on further developing an employee’s tenure, plan assessments and metrics, and calculate incentives and rewards. Employee performance management automation can make HR processes easier by performing tasks like reviews, analysis, and calculations. It frees up time by eliminating the need for manual work from the picture.
7. Employee Exit Process
Source: Freshworks
Several HR activities are to be performed at the time of an employee’s exit. It includes relieving documentation, completing and final settlement, and revoking access. Even a minute error can lead to collateral issues. Thus, the exit formalities require unmissable attention to everything for a smooth and orderly process. HR automation with machine learning can organize and streamline the off-boarding process. Automation helps the department monitor every task involved in the process and notifies the concerned teams of the steps that need to be fulfilled from their end. On top of it, automation also extracts the necessary information from the backend and, again, saves manual effort.
7 Applications of Machine Learning and Artificial Intelligence in HR Automation
Here is some common application of machine learning for HR activities that companies are either successfully implementing or on their way to make it a hit:
1. Workflow Automation
Source: Technology Advice
Automation of workflows is a primary and one of the initial applications of machine learning and artificial intelligence in HR. ML has unlocked immense ease in various functions, including screening, scheduling interviews, communication with potential employees, and performance reviews. Scheduling and tracking tasks are typically time-consuming and tedious. HR automation combats these challenges by streamlining operations, which unloads a reasonable amount of time for the HR department. It results in fleet-footed efficiency and remarkable consistency that allows the people in the department to devote their time and effort to the tasks that require more attention.
2. Hiring Top Talent
Source: Jobsoid
Artificial intelligence and machine learning are helping HR professionals check a major to-do off the checklist: spotting the perfect candidate. Many companies worldwide have already kickstarted the ML application for recruiting suitable candidates. Such candidates match the head-to-toe of their job description. LinkedIn exemplifies this application just right. Its use of machine learning helps recruiters refine their searches and help them make effective hiring decisions, thanks to the algorithms.
3. Decision-Making and Planning
Source: Studious Guy
Machine learning with HR automatically offers valuable insights that help the department assess the current standing, identify trends, recognize barriers, track employee progress, and many other tasks. With the help of predictive analysis through automation, the HR department can catch the lingering issues and challenges and remedy them on time.
4. Employee Training
Source: Walk Me
Machine learning and HR automation can be leveraged to strengthen the workforce and make it more qualified by introducing suitable training programs. Employee training is one of the most fitting examples of machine learning applications in HR. Machine learning algorithms help employees navigate advanced courses that best match their requirements. As the list narrows, it shows the courses that include the skills that can help the employee develop desired skills and achieve professional goals, which also improves employee engagement. So, employees don’t have to struggle to find that one course in a buffet of internal and external training material.
5. Accuracy and Efficiency
Source: CheckHub
There are many tasks in the HR department that take up a lot of time. Recruiting is one of them. By implementing predictive analysis, machine learning systems can help eliminate the ‘time’ issue. It not only speeds up the process but also provides accurate intel. Since machine learning can track and collect information from the applications, it reduces the scope for manual error to zero, which saves both time and effort.
6. Attrition
Source: Medium
Retaining top talent is as essential to the company as hiring them. While employee retention cannot solely work at the fingertips of HR, it enables the department to analyze, predict, and manage attrition through usable insights. These predictions allow HR teams to make informed decisions before any challenge occurs.
7. Employee Engagement
Source: AIHR
Employee engagement is a buzzword in today’s corporate culture, and it is for all the right reasons. A happy and active employee translates to efficient and top-notch work. Machine learning helps the HR department approach employee experience by measuring and understanding how much an employee is engrossed and happy about it. Payroll software also plays a key role by ensuring timely and accurate compensation, which can positively impact employee satisfaction. The insights generated with the help of automation can give a hand in planning activities and designing an environment that keeps the employees’ headspace clutter-free and calm.
Conclusion
The impact mentioned above, use cases, and applications of ML and AI technology applications in human resource management echo the future of HR automation aloud. While it may look like a snatcher of the jobs of millions of HR professionals, the truth is that it is here to simplify their to-dos. HR teams can make the most of automation by avoiding repetitive tasks and focusing on the big-size areas that await their endeavors, such as candidate experience, employee retention, engagement activities, etc.
AI and machine learning have already begun making sure that HR teams have more productivity as several tasks get streamlined. Many companies, including Amazon, are implementing these emerging new technologies. From onboarding new hires to performance management and real-time updates, it’s a win-win both for the HR department and the potential/ existing employees.
The machine learning market has worked no less than magic on many business functions globally. It is projected to stand at around US $302.62 billion by 2030. On the other hand, machine learning now has its expanse of job opportunities, which won’t come without attractive pay. Curious to know more? Learn the many folds of machine learning, deep learning, robotic process automation (RPA), and a lot more with Analytics Vidhya. that are here to stay and even to give the career of many wings.
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Frequently Asked Questions
Q1. How is machine learning used in HR?
A. Machine learning is robustly shaping HR management functionality. The technology enables HR activities to work more efficiently and effectively by streamlining data and performing predictive analysis, reducing manual work significantly.
Q2. Is machine learning the future of HR?
A. Considering the buffet of benefits and efficiency catered by AI and machine learning, it’s safe to say that these technologies have the potential to revolutionize the HR management workflow.
Q3. What are the applications of machine learning in HR?
A. Machine learning helps the HR department streamline tasks such as screening, onboarding, employee exit formalities, and employee engagement. It extracts valuable information from various databases and provides accurate information, speeding up the decision-making and planning process.
