How Automation Can Help the Performance Appraisal Process Become More Efficient
How Automation Leads to Transparency and Accountability in the Appraisal Process
It would be an understatement to say that technology would be a game changer for all Human Resource Management (HRM) Processes. By automating the routine tasks and using data analytics as well as big data, HR Managers can ensure that the end to end HR value chain can scale up and actualize synergies from the integration of disparate and discrete tasks.
For instance, by automating the Performance Appraisal process, HR Managers can derive the benefits from the economies of scale wherein they have the capability of processing the appraisal activities on a mass basis.
Indeed, the fact that once automated, the performance appraisal system can scale up or in other words, cater to any number of employees means that there are time and effort savings through automation.
Further, automation of the performance appraisal process ensures that all employees are covered as well as a record or log of the activities of both employees and managers is maintained leading to accountability.
To explain, automated performance appraisal tasks ensure that there is an audit trail or audit log of the activities which helps make the concerned employee or manager accountable. Further, through automation, there is an element of transparency wherein senior managers, and the HR managers can step in cases of disputes or disagreements and find out the root cause of the dispute by logging in to the HR portal and checking who has noted what and when and where. In addition, the employees can also log in and check the record for themselves thereby introducing transparency into the process.
Moreover, in cases of lawsuits and legal cases, the entire history as well as the archive that contains the activities in the HR portal can be used as evidence by the organizations in courts of law. Apart from this, the fact that third parties can also be given access to the HR portal means that in cases of internal inquiries, the automated performance appraisal system can prove to be valuable for the investigators to check and determine the culpability or otherwise of the various parties.
This means that automating the performance appraisal system does indeed make the entire process more efficient given these benefits.
How AI and Big Data can Make the Appraisal Process Free from Human Bias
Apart from that, technology can also be a game changer for the performance appraisal processes as by using data analytics and Big Data, HR managers and the line managers can assign the grades and the ratings on a scientific basis instead of subjective attributes.
For instance, automation can help the HR managers and the line managers to sift through the appraisals of all the team members and use analytics to determine the ratings.
How this works is by ensuring that the combined performance metrics are available and once they are so, they can be fed into the analytics software or the AI or Artificial Intelligence enabled tool to determine who ranks where and who is higher or lower in grades relative to the others.
One of the most common complaints in organizations during the performance appraisal process is that the biases of the managers are making them assign bad grades and low bonuses and pay hikes for those team members who are not their favorites.
Thus, this problem of human biases creeping into the appraisal process can be eliminated or even minimized by using data analytics and AI to sift through the feedback and the comments and determine the ratings in an objective and unbiased manner.
This would help the organizations to introduce more efficiency as well as transparency in addition to removing the element of subjectivity and bias which makes many employees often quit the organizations.
Remember that employees often leave due to their immediate managers rather than for any other reason and this fact has been validated by research which confirms this aspect. Thus, organizations can ensure that they retain their employees by convincing and proving to them that the entire performance appraisal process is free from human bias and subjectivity.
Making the Appraisal Process Data Driven can Help All Stakeholders
The point to be noted here is that through automation, the entire performance appraisal process can be data-driven which makes it scientific and rigorous in its methods. As the legendary founder of the Indian IT (Information Technology) company, NR Narayana Murthy is fond of saying, In God We Trust, and the Rest Have to Come with Data.
Thus, what this means is that by making the performance appraisal system automated, organizations can ensure that the data-driven methodology and the AI-powered rating system can make all stakeholders happy and free from doubt.
It is also not the case that automation would completely solve all problems with the performance appraisal process.
Indeed, AI and Big Data Analytics are still yet to evolve into such capabilities where they can replace human decision making elements.
Moreover, by programming the software and configuring it, the person who is doing this can introduce his or her own bias into the software. Thus, the key here is to ensure that the person-machine interface and the human AI interactions do not drag the entire process down to the initial level which as we have discussed is the problem that led to automation in the first place.
To conclude, using technology with due diligence and care and caution can indeed usher in a new chapter in the way organizations undertake and conduct the performance appraisal process as well as the rating system.
Authorship/Referencing - About the Author(s)
The article is Written By Prachi Juneja and Reviewed By Management Study Guide Content Team. MSG Content Team comprises experienced Faculty Member, Professionals and Subject Matter Experts. We are a ISO 2001:2015 Certified Education Provider. To Know more, click on About Us. The use of this material is free for learning and education purpose. Please reference authorship of content used, including link(s) to ManagementStudyGuide.com and the content page url.