Ramesh Soundararajan is an HR professional with 25 years of experience as a practitioner and consultant. An electrical engineer from National Institute of Technology (NIT), Kozhikode, Ramesh completed his master’s in personnel management and industrial relations from Xavier School of Management (XLRI), Jamshedpur. He is the co-author of “Winning with HR Analytics” the top-selling book in Amazon.in on HR Analytics.

Presently he is the founding partner of Culstran LLP, a firm focused on consulting corporates in the areas of culture, strategy, and analytics. He is also certified in analytics from IIM Bangalore and HR Analytics from Wharton Business School. He is a certified assessor on PCMM framework and CII model of HR excellence.

In all his roles, he has pioneered an analytical approach to reviewing information, integrating insights from across different functions to help the function put its best foot forward. The approach encompasses all HR domains such as performance management, learning and development, and talent acquisition and retention. His blog on analytics, “HR3by2”, is widely referred to. He is working with large corporations from developing analytics competency in HR to designing interactive dashboards. He also works with start-ups in the HR analytics space. He is a trained assessor using the PCMM and CII HR models.

What are the key aspects of employee performance that are critical to the success of HR Analytics?

HR analytics relies on hypotheses. The hypotheses can have inputs like benefits or communications or compensation. The outcomes have to track for their impact on employee retention or engagement or organization performance.

For it to be effective, then we need first of all ensure the employee performance outcomes are aligned with organization performance, so that from an analytical perspective we know that anything that improves employee performance automatically boosts company performance.

In which case it is important to ensure that the performance ratings adequately represent the actual performance and are not based on subjective opinions.

Once this linkage is established, the following can be tracked

• Goal achievement rate (What percentage of employee goals have been met?)
• Variations in individual performance ratings.
• Impact of training on a related aspect of employee performance
• Goal achievement rate of employees versus that of their business

How can HR Analytics enhance employee performance?

Analytics can help in isolating factors that provide sustained employee success as well as continuous failure. In specific

• Associate competencies with employee performance. Identify the competencies that have the most impact on different employee groups and then select/ allocate/ train accordingly.
• Associate competencies with job role performance. Someone may have a competency that is effective in sales but not in finance. Accordingly, the person with the best fit for finance should go to finance and so on.
• Predict employee goal achievement on the basis of checkpoint feedback. Is the employee likely to meet his/her goals at the current rate? If not what actions need to be taken.

What do CEOs/CHROs look for in employee performance analytics?

In service organizations, employee utilization becomes an important factor. What percentage of time goes in doing billable work? Similarly employee productivity.

For both these, employee performance analytics helps in identifying causal factors.

• What competencies/ skills/ personal attributes of employees improve billable work?
• Is there a way to systematically include and improve such causal factors in the workforce?

The same holds good for employee productivity. One of the major corporations did a study to understand the impact of training. They found that the impact of training is influenced by the timing of the training (whether it is in time or too far back in time) as well as the quality of training. Another study found that quality concerns, as well as changes in external temperature, predicted workplace accidents. Identifying such causal factors helps improve productivity.

CHROs are also equally invested in employee performance and productivity. In addition, they are also concerned with the impact performance management process has on employee motivation and morale. They are interested in subjective measures like employee satisfaction with the performance management process as well as measuring events like the number of discussions, whether rating was preceded by a discussion. Like what happened with compulsory normalization. CHROs sensed that normalization even when done effectively has an adverse impact on employee morale. Hence the changes happened in the process itself.

So CEOs and CHROs are primarily interested in performance outcomes, productivity, and impact on employee motivation in the process.

Employee engagement and retention is a key objective for all CEOs and CHROs. Fair treatment of employees is manifest in performance goal allotment, recognition, and alignment to rewards. Making performance recognition as fair as possible minus biases of gender, qualification, ethnicity is one of the biggest challenges that is currently being faced by organizations. Analytics plays a key role in identifying such biases and actions are taken to address them.

What is missing in terms of employee performance data that could make HR Analytics even more meaningful?

Even now, there is far less measurability and objectivity in employee performance data. For example, say if an average employee can make 5 widgets in a day. In traditional work, the excellent employee may make 7. However, in knowledge work, superior performers can be even 20 times more effective than the average performer. In which case, what expectations can be set for above average performance? Also, the outcomes in knowledge work are not as easily measurable as the number of widgets. Both may write 100 lines of code, but one may write code that achieves 3 times as much. A manager will know who is better, but the
measurability is not very easy.

Another could be defect rate. Conventionally one might say lesser the defects are, better the work is. However, in coding both the number and magnitude of defects play a role. Since employee corrects the defects, one has to depend on him/her for reporting the same. In a scenario like that, it is difficult to capture accurate data.

So one ends up relying on customer feedback, individual competence, manager perception etc. This leads to a balanced challenge; if one tries to make the measurement more mechanistic, it might intrude on individual freedom and vice versa.

Hence corporations are moving to push down the decision and budgets to individual managers but formalizing the discussions; Instead of the earlier approach of a formal review but informal discussions.

Can HR Analytics play a prescriptive role in helping employee fine-tune performance real-time?

It is possible and products exist today that track employee work patterns on the desktop/ laptop. They can track the active time for employees, how frequently they take breaks and what are their most productive times. Such information can be supplemented with personal productivity programs so that they can be better in control of their own time.

However, such systems also grapple with privacy concerns and questions of what if the employer uses it to spy on them? I think a clear and transparent approach will be very useful. Even youtube is now offering a counter to track the time spent on it!