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In an exclusive interaction with APAC Media and CXO Media, Saurabh Deep Singla, CHRO, IndiaMART InterMESH Limited is of the firm belief that in the digital age, performance management is no longer just about annual reviews—it’s about real-time insights, data-driven decisions, and continuous growth. Tech-enabled performance management leverages AI, analytics, and automation to track progress, provide instant feedback, and align individual goals with business success. By moving beyond traditional evaluation methods, organisations can foster a culture of transparency, agility, and high performance, ensuring that what truly matters is measured, optimized, and rewarded.
How has technology transformed traditional performance evaluation methods in recent years?
Traditional performance evaluations, often lacking subjectivity or subject to bias and inefficiencies, are increasingly being supplemented or replaced by AI-driven systems that promise greater accuracy and fairness. Use of AI for evaluation tools can analyze vast amounts of data from various sources, such as work output, communication patterns, and even social interactions, to generate insights into employee performance. They can also help standardize the evaluation process, ensuring consistency and reducing the likelihood of biased judgments.
Another aspect is reduced reliance on traditional methods such as reviews based on subjective recall or limited data and replacing them with 360-feedback platforms. Tools like 15Five, Lattice, and Culture Amp (just examples) now enable real-time feedback, peer recognition, and frequent check-ins, fostering continuous development. Easier methods of recording data such as google forms, quarterly/monthly score sheets, rewards & recognitions throughout the year also helps in better evaluation of a candidate.
What are the risks of bias in AI-driven performance reviews, and how can they be mitigated?
Issues related to algorithmic transparency, fairness, and potential biases within AI systems are an area of concern. Additionally, employee perceptions of AI-driven evaluations play a crucial role in their acceptance and effectiveness. Trust in AI systems, the perceived accuracy of evaluations, and the overall impact on employee morale are key factors that influence the success of AI-powered performance management.
AI models are trained on historical data and can introduce or encourage a continuous bias in the system. In certain cases, a bias may be unintentional, however AI systems pick up patterns and implement them in existing processes. For instance, if an organisation has consistently promoted young women between a certain age bracket, however the decision has been made purely on the basis of their performance and not age, AI may still think age as one of the parameters and may stop/reduce recommending older women for promotion roles.
Therefore, a blend of human and AI is needed where AI can assist humans and boost the overall performance.
What are the biggest challenges companies face when implementing tech-enabled performance management systems?
Over the years, we have been working in traditional/conventional working environments. As we move into tech ways of working, there is a certain resistance from the workforce to move out of their comfort zone. We need to understand that people may need some signposting & counseling to ensure a seamless transition within the organization. As a solution, we internally rely on learning management tools that can create modules, dashboards and train the workforce to understand newer ways of working and feel comfortable in using them. This is valid for not just the performance evaluation process but tech advancements across the organization
Another issue is lack of trust on the machine-based output, a valid concern that remains. This is an issue that can be addressed over time. As more and more employees become comfortable with tech-enabled management systems and understand that it is actually making their work easier, the trust will naturally start developing.
Will AI and automation replace traditional managerial roles in performance assessment?
Yes, to a great extent, it will. A managerial role can be divided into two parts – a) transactional element and b) judgmental aspect. The transactional element can be easily replaced by AI, which means tasks such as scheduling calendars, regular updates, feedback etc. are repetitive in nature and can be managed by AI itself.
The other aspect, i.e., judgmental one, can also be divided into two parts: A) basic judgement on logic, (again movable to AI) and skills which are softer in nature. For the softer skills which a machine can’t read, we will always need human beings, and that element continues to stay today and forever.
How can businesses ensure that remote and hybrid workforce performance is accurately measured without bias?
Inclusivity is the key and that’s what we believe at IndiaMART. For a 6000+ employee organisation, we believe in equipping our workforce with adequate tools and skills to ensure that every employee, dispute in hybrid, in office or work from home mode can work in total sync and tandem with each other. That is the first part of solving a challenge and the performance evaluation comes later on.
To address this, a highly integrated in-house ERP plays a big role for us, which enables us to understand progress, focus on output and not worry about time of logging in, places from where they are logging in and deliver customer delight.
What are the key differences between legacy performance management systems and modern tech-enabled frameworks?
The legacy ways of working started with pen and paper, moved to excels and then systems capturing data. Unlike today, wherein systems are talking to each other, sharing valuable information across touch points and helping data to have seamless visibility. The newer/tech ways of working has helped increase the frequency and pace at which performance reviews were happening. The issue of limited availability of data or data being available in silos is no longer there, as technology allows us to analyse multiple data volumes at the same time.
Another aspect is the transition from KRAs to KPIs and OKR and beyond is starting to reflect in the newer ways of working. In a traditional setup, where we were only analysing candidates on the basis of past performance, a forward-looking approach has now become mandatory in newer ways now.
How can organizations future-proof their performance management strategies in a rapidly changing work environment?
Before deploying a future-proof performance management strategy, it is essential to make the workforce future ready, otherwise it won’t be the right comparison. At IndiaMART, our focus is to first move from degrees to skills, before we worry about performance. We need to reskill and upskill our workforce first, equip them with the right tech so every employee has their own career path, against which they can be further evaluated.
This includes parking 100,000 INR/person for each employee under our iLeap programme and encouraging employees to upskill themselves on company cost.
How can organizations ensure that technology does not lead to employee surveillance and micromanagement?
In the past, we have seen that technology which was supposed to be a mere chatbot ended up micromanaging the user by asking too many sensitive questions. Regular human intervention needs to be with AI, so technology doesn’t become an employee surveillance and micromanagement tool. This means having the right mix of asking questions, sharing insights with the users, followed by further questions and not using data to the disadvantage of the employee. We also need to ensure that there is enough transparency in the tool that it doesn’t end up generalizing the data or make it a trend in the organisation.
Online Coverage: CXO Media