'Did you capture the right metrics which show the HR value - add?' - is one of the most common questions heard in the HR corridors for long now. Dashboards, data decks and reports generated from information systems are being incorporated in the HR departments’ reports since last decade or so. HR facts like headcount, attrition, productivity, hiring and demographics are some of the popular areas of HR reports. While these forms of analytics did exist in the HR world earlier as well but now it is important to exploit data explosions through advanced analytics so as to provide more insightful and actionable answers. With HR analytics gaining traction in recent times, it is a great opportunity for organizations to capture and measure the value that the Human Resources department can create for the business. Yet the basic question still remains the same or with a slight modification – "are we capturing the right metrics?" With the possibilities of analytics, should we come up with new metrics to gain deeper insights so as to augment people related decisions?
As humans, we have a tendency to measure what is easy for us and not what should be measured. We need to move forward from just fact-based reporting to a more forward looking and predictive mode to capture impact- based data. This progression will help HR professionals improve their decision making abilities using analytics.
Let us take a common example – attrition. Measuring attrition or turnover is an HR metric that has been used a lot. Different companies have been capturing attrition across various dimensions based on their priorities. But what is the level of depth or correlations attributed to real business issues. For instance, is it enough to capture the annualised or monthly or weekly attrition in the organization? We need to dig a little deeper to capture data which can help resolve issues that make huge business impact. It might be important to analyse the attrition of star performers or Hi-Pots who were contributing x% of revenue generation. Or, to find out if there is a trend of new joinees leaving in the first 3 months, 6 months, 1 year of joining? Also, can we foretell which employees would be leaving so that we can retain the valuable ones? Should we also look at other factors like last role change, performance over time, and work-life balance to do a turnover modelling? Furthermore, a detailed analysis of ‘reasons’ could also reveal unknown or unacknowledged facts about attrition. It could also disprove common perceptions that exist around them.
- Are we asking the right set of questions? This is important to identify the business issues and address them from a people’s perspective
- Are we capturing the right metrics which drive business results? Unless the right data points and parameters are looked at, the issue might not be addressed at the core
- Do we have the right capability in the team to identify the trends and opportunities and to use data to make ‘people based’ decisions? While data analysts and data scientists are required to develop the models and to mine the data from various sources, the HR team needs to have the capability to engage with business to identify opportunities and look at new ways of solving business challenges
In my earlier article 'Leveraging People Analytics for Enterprise’s Competitive Advantage', I have mentioned how people analytics can be used for competitive positioning and how beginners can embark on this journey. When organizations are setting up their analytics unit and figuring out their requirements, it is important to lay a strong foundation. This would help them in both experimenting as well as providing room to build on what works best for them. The advancement in data technologies provides great scope for HR leaders to use data for various people related strategies and interventions. However, it is critical to see that the right set of business issues are identified, the right set of questions asked and the right data points gathered and made use of for creating true value. Also, with data, one needs to keep these basic principles in cognizance:
- Data should be 'relevant' : addressing the right business issue
- Data should be of 'quality' : quality of the data is important
- Data should be 'effective' : data analysed should help in making better people related decisions
AND - The dots must connect: HR should collect the ‘right’ data points from the voluminous data available for analysis; work with the analysts to build a storyline by connecting the dots and present this data with a case to overcome business challenges.
So, it’s time to tap into your people data, think beyond HR employee life cycle and see what they can tell you! Wear your analytical leadership hat and build capabilities to capture the right metrics.