Posted in Human Resources Articles, Total Reads: 776
, Published on 07 November 2015
Which profile performs the best? Which competencies drive business outcomes? Why do high performers churn? Organizations would love to have the right crystal ball that answers such questions. But who can answer these questions and how?
The Human Resources does seem a department to bank on but does it have dedicated resources to deep dive. Analytics is inherently not as associated with HR as it is with say Marketing. Organizations have not feared investments in analytics. FMCG companies like P&G, Unilever are investing crores in analytical tools and techniques as they have realized value from it. However, organizations are yet to realize value from investments in HR analytics.
What is their excuse?
1. Training and Mindset: HR is expected to perform as a supporting department to others like Marketing, Operations, and Data Management and so on. So, firstly their thinking is limited to this and lack of analytical training opportunities does not sensitize it toward analytics either.
2. Data and data variety: Typically, HR has a variety of tools for various services sourced from different vendors. And the worst part, these tools work in isolation. Even if one wants to make use of analytics, the major challenge is now to aggregate these silo systems or make them talk to each other which puts off even the determined ones.
Besides, the quality of data is not viable for use in analytics. Either the data is incomplete or does not follow a standard for uniformity and consistency.
3. Biases and fears: Conflicting demands and rising expectations as a result of data driven approaches, fear that data might reduce the human essence in problem solving personal preferences and ambiguity about analysis
While the first is an excuse that requires an organization to treat HR as any other department – lay down objectives, allow for investments, training, and define criteria for success and ROI. Not that this does not happen but associating HR with analytics would embed this further. The onus is on the organization to be inclusive. That said, people in HR are better in managing uncertainty than analysis. They typically use intuition and inductive reasoning skills to tackle issues. They are less comfortable with numbers and are biased toward qualitative ways of dealing with problems.
So, where does one get the analytically skilled people who also understand HR management? Well, people skilled in analytics could be hired and HR could drive the work. With this, all HR can focus on identifying issues and seeking insights from the analytics team (which now does the math and statistics). Besides, analytics is just a mathematical confirmation of solutions to a problem. You still need to make use of reasoning and qualitative approaches. You need the skills to build a story around the numbers as numbers alone would mean nothing.
The second excuse – This is a real challenge faced by most organizations and is a roadblock.
Systems in an organization suffer from the following
• Legacy Systems – These are old systems still running because they are important and no one cared to upgrade these.
• Incompatible technology – Inputs generated by newer systems may not work well with legacy systems or vice-versa.
• Permission issues –Sometimes data is not available for all because of security reasons. These might strangle collaborative approaches needed otherwise.
The insights that you draw of unreliable and incomplete data is obviously of no use. The onus now lies with HR to make the organization realize the need to have systems in place so that HR could deliver valuable insights besides being a support to other departments.
How does the HR prove its worthiness?
Start with a specific question that the business is seeking answers for. For example, imagine that the business is seeing a drop in sales owing to dissatisfied customers. Well, at first this might not seem a quest for HR but nonetheless, a reason good enough for investigation. Assuming the HR reporting systems are capable enough to report metrics like performance, absenteeism, turnover etc. and that this data is reliable enough, one could analyze this data region wise, branch wise, manager wise and even further. With this, a link may be established between performance and customer satisfaction and ultimately your sales. This exercise may not be fruitful at first or may bring insights less helpful to solve the issue at hand but what it does show to the business is that HR can provide insights. A few of these ad hoc exercises would generate support from the business, place value on your efforts and contribution. It could open doors to having workforce analytics in the organization’s IT roadmap. Soon, a dedicated team would be instilled which work on workforce analytics since you would have proved that insights can be generated and are valuable to the business.
How does HR build on from here?
Analytics is an ocean. One could possibly do great things with it. But it all boils down to what information you have got. The challenge really is getting value out of analytics. With existing information, one may think of burning questions that need attention. Seek answers to these questions with data at hand and present the insights to the business. A few of these smaller exercises with results to showcase will make the stakeholders see value of the data. The quality of data would then be recognized and rightfully governed. You are basically sending a message that the more clean and reliable the data, the better insights you will get and the better will be the value addition.
With an aim to change the perception of HR from backward-looking to one being analytically driven and a business contributor, analytics in HR may be looked at as a continuous investment with continuous benefits. In the long term, it could form a part of the HR capability and focus on answering key business questions.
This article has been authored by Priyanka Dewri from IIM Trichy
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