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Taking decisions based on data has always been a best practice, but the problem till recently has been ‘lack of data’ or ‘not enough data’ to enable good decisions. With quantification of talent management practices taking centre stage, the need for the right data has become paramount. With every HR professional gearing up for a data-driven HR practice and with the explosion of data analytics processes, there is a need to pause and consider the need to manage data properly and be mindful of problems due to data overload.

A small example (unrelated to HR but still relevant) is with reference to career planning. A middle school student till about 10-15 years back only knew about a few career options (even though there were plenty of options available) and suffered from a ‘lack of information’ syndrome. Today with Google and other search engines, the amount of information available on career options is mind boggling. When you talk to parents, teachers and students, they see a huge problem here; with so much data, the confusion gets compounded. The effort needed to sift through oceans of data and identify what is relevant to one’s particular need/context is becoming a key challenge today.

Back to the problem of data management and HR. It is a fact that even leading organizations feel overwhelmed and have difficulty making decisions with the mass of information available. One of the biggest challenges is drill down the data to gain meaningful insights, but if there is no clarity, it can become a big challenge too.

So what are the key issues one can think of with reference to management of talent data? I am outlining a few below and encourage readers to share their perspectives and experiences as well.

• Human error: Human error is natural, and there is a tendency for people to go searching for data that supports their beliefs and biases and not the other way around.
• Confusion over data ownership: Lack of clarity on ownership of talent data is a huge problem that affects HR Practioners. With some much data being collected real-time, if there is no clarity on who owns talent data, it can lead to a huge ‘opportunity loss’.
• Lack of right talent and processes: If you have a lot of data but don’t have the right people and tools to make sense of the data, then you can be sure that the data will not get transformed into meaningful insights.
• Over reliance on data: A lot of managers and decision makers feel the urge to try everything possible with data. But with so much data and limited time and resources available, it takes away the focus from critical issues if not properly prioritised.
• The infrastructure conundrum: If an organization’s technical infrastructure is not up to speed to accept and interpret multiple sources of data, then there is little hope in managing or analysing the data for actionable insights.
• Analysis Paralysis: The biggest problem of all is doing nothing with the data organizations have spent time, money and resources collecting.

With talent data becoming the hub for much of enterprise reporting, the talent analytics function has to be geared to support requests from all areas of the company: legal, finance, planning, payroll as well as HR. As demand for reports and analytics is growing, there is a definite need to focus on the right talent, processes and technology that would augment the HR team in managing talent data well to provide strategic inputs linked directly to the business priorities.

Management challenges talent management data management HR