In the past couple of decades, human resource management which was originally seen more as an administrative unit has transformed into a strategic unit for every organisation. One of the biggest reasons for this shift is the increasing availability of technology solutions in this area. Today business changes rapidly, go-to-market time is short and organisations need a workforce that can adapt to change, which means the human resources also have to adapt to the different forms of engagement with humans.
If we look at today, technology is already making tremendous positive improvements to the HRM teams. Today most organisations are already on their journey to digitize and automate some of their processes like management of employee data, payroll processing, employee onboarding, streamlining workflows, talent acquisition, service requests, etc. This transition enables the HR associates to perform these administrative tasks in a faster way and pay more attention to items that need direct employee engagement.
In this journey of reengineering, digitizing, and automating their processes, the next logical step would be the adoption of digital workers, deep-dive analytics, machine learning, and artificial intelligence capabilities. Some of the potential examples of HRM that can change in the next few years aided by technology could be:
A bot can mimic what a human does with a screen and keyboard. In the future, the Human Resource (HR) associates would be supported by a digital workforce, picking up all of the administrative work from the associate, giving them time to focus on the strategic and creative part of their work.
Also, today the human workforce updates various systems because they cannot communicate directly with each other. Hyperautomation technologies allow systems to communicate effectively allowing bots to perform repetitive and mundane tasks. Besides, HR can have a chatbot for their people that is available around the clock to respond to questions and offer solutions.
Artificial Intelligence (AI) and Machine Learning (ML)
Artificial Intelligence can make a huge difference in talent acquisition. AI tools can automatically read the information from a resume, load it into a system, and also show a fitment score based on skill match or experience, or other factors, to the recruiter. So, the recruiter pays attention to the most suitable candidates.
Employee satisfaction is the key for any organization. There are different types of service requests that come to the HR teams. A machine learning model can be trained to look at service requests and take decisions or forward them quickly to the right person. That way workflows can be optimized, the resolution to queries is faster, and most importantly the employee knows that their request is being given the right priority.
There is so much useful data available within the different HR systems and outside it as well that are today not tapped into. Improved analytics systems will enable tapping into those data and getting valuable insights on the different HR processes, their effectiveness, bottlenecks, etc.
There are so many compliance rules within HRM that can be implemented as well as validated if they have insight into the data. Also, the digital workforce can process complex data around the clock and provide data on a real-time basis for effective decision-making.
For instance activities like onboarding can be streamlined by automating end-to-end processes with the suite of hyperautomation technologies like BPM, RPA, OCR, AI, etc. The employee fills in one simple online form from his/her mobile, and uploads the necessary documents, that is all. AI can automatically read their documents and gather information, BPM tools kick off the workflows, bots can update/retrieve information from other systems and add it to the workflow, and machine learning models can speed up the decision-making within workflows and the onboarding is completed.
So HR leaders will have to take note that the way employees work – where, when, why, and with who is going to completely change and we have to quickly recognize and adapt to those changes.
Views expressed above are the author’s own.
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