Why Performance Appraisals Have to be Data Driven Instead of Being Subjective

Employees Leave Managers Instead of Organizations due to Perceptions of Discrimination

It is often the case that performance appraisals become the bone of contention between the managers and their subordinates due to differences over ratings and the resultant pay hikes and the quantum of bonuses.

Indeed, it is quite common for employees to allege discrimination on part of the managers when they receive poor ratings and bad performance reviews.

With research showing that 80% of all employees who quit do so due to differences with their managers, there is a need for organizations to take the employee performance appraisals seriously and ensure that there is transparency and accountability.

This is where performance appraisals based on data and the reason for logic play such an important role in ensuring organizational success.

Indeed, when performance appraisals are driven by data rather than subjective whims and biases, then the managers and the Human Resources managers can justifiably claim that there has been a fair approach that is data-driven.

Further, when the entire appraisal process is data-driven, the underlying metrics ensure that organizations can withstand lawsuits and other legal cases brought on by disgruntled and disaffected employees since then, organizations can justifiably claim that there has been no bias or prejudice towards the employees on gender, race, and other bases.

Performance Appraisals Cannot be Solely Data Driven

It is also the case that the entire performance appraisal cannot be fully and purely data-driven as the managerís feedback to the employees has to be based on perceptions of performance in as much as it based on data.

In other words, there are aspects such as soft skills and other parameters where data cannot be the sole criterion for the appraisals.

In addition, there are also aspects such as team player and other attributes that are based on subjective feedback and where data alone cannot suffice. Indeed, organizations run the risk of becoming soulless machines if data becomes the sole criterion.

Apart from this, the fact that the bell curve method of rankings and ratings which is based on relative performance rather than absolute numbers means that no matter how much organizations try, the performance appraisal process cannot be solely data driven.

Moreover, the fact that performance ratings are both an indicator of personal performance as well as relative performance means that there has to be an approach that combines data and relative performance without being too subjective.

Combination of Algorithm and Personal Perceptions can Help

This is where many organizations are experimenting with algorithmic driven performance appraisals wherein the combination of data-driven absolute performance is then fed into the Algorithm or the Artificial Intelligence driven software to ensure that there is a measure of both relative as well as absolute performance.

In addition, contemporary organizations are “moving beyond the bell curve system” and are trying out alternatives such as data from actual metrics and parameters as well as subjective feedback along with software and technology-driven relative ratings.

Indeed, even the Bell Curve Method uses metrics and data to measure relative performance and it is only in the “final lap” of the performance appraisal process that the determination of ratings based on the managerís final say is then the factor that goes into the ultimate rating.

This is where subjective biases come into play since the determination of the final rating is often based on the managerís call rather than anything else and this is where most employees complain that they are being discriminated against.

Indeed, employees allege discrimination only when they find that other employees and their peers and coworkers are given better ratings due to any number of reasons that are based on the employeeís perceptions.

Use Data Judiciously and Establish a Transparent Appraisal System

Hence, it would be better if the entire performance appraisal process is made as objective as possible and this is where data-driven approaches have their advantages. Indeed, when the employee and the manager record metrics throughout the period of the appraisal process, such metrics and data provide useful insights into how the employees have fared in both relative as well as absolute terms.

In other words, as the saying goes, data removes the subjective element as far as possible.

Having said that, one must also note that there are confidentiality aspects as far as revealing data about the performance appraisals are concerned and this is where organizations can ensure that they publish the ratings without actually revealing the parts where such aspects are taken into account.

Thus, what we have is a combination of how data can be used to measure performance and once the appraisals are over, then in the same manner in which professors display the grades of all students without revealing the underlying basis means that AI-driven and data-driven approaches can work in organizations as well.

Indeed, the fact that most universities in the present times use data-driven approaches extensively for grading means that organizations too can adopt such methods.

Trust is the Glue that Holds Organizations Together

Lastly, there has to be an element of trust between the employees and the managers and this is where no data-driven approach can ever replace the human element.

After all, we are dealing with real emotions and personal feelings and hence, it is essential that the social contract between the employers and the employees is upheld at all times.

To conclude, we have not reached a stage where robots conduct employee appraisals and hence, it is the case that a combination of data and personal perceptions are used to actualize a fair and transparent performance appraisal process.

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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. 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.