Avoid These 3 Common Pitfalls to Data-Driven Talent Management

With the advancements in data collection and analytics, more and more HR departments are taking a data-driven approach to talent management and harnessing the power of hard facts and numbers. The reality is talent management can be very subjective, relying on gut feelings or opinions when judging future potential, leadership capability or selecting best fit candidates. Utilizing data to remove bias and inconsistency in these practices has become the new, better standard.

However, while data-driven talent management offers enormous potential in more effective people related decision making, it can pose several challenges. Here are 3 pitfalls to avoid when considering a data-driven talent management initiative:

1. Data is inconsistent or tells varying stories.  
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Data-driven decisions are only as good as the data you are analyzing. Often, organizations rely on data that is siloed or originating from a wide range of sources. This presents a challenge in interpreting insights and trying to pinpoint one, comprehensive story from the data. For example, which of the data sources do you trust?

2. Too much data. 

Ironically, too much data can be an obstacle just as too little data can be. Often, this can lead to paralysis or over-dependence as HR leaders ask for more and more data points to consider in a slightly different way. Decision-making can then become stalled or deferred as leaders seek comfort from another data point. Too much data can also distract HR leaders by irrelevant insights. For example, data analysis may point to a conclusion such as, 5 percent of high potential staff feel “disappointed” after lunch. However, what should managers do to reduce disappointment sentiment or does it even matter?

While many HR leaders advocate the collection and tracking of all talent management data, consider that this may not be practical given time and resource constraints. Remember that insights driven by data aren’t truly insightful if they don’t lead to actions to change the outcome. Instead, focus on talent management data that informs action and drives better talent and business outcomes.

3. Poor data governance.

Without good governance, data can turn into a liability. For example, if recruiters are using the applicant tracking system correctly, or inconsistently, extracting data in order to track metrics will be futile. For this reason and many others, organization’s using high amounts of data need to set guidelines and authority for data-related decisions aimed at improving data quality, data access and compliance.

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HR leaders should address this issue with the organization’s data governance team, or if that function is missing, collaborate with key stakeholders to inform the executive team of the need.

 

Forge a Smoother Path to Data-Driven Talent Management.

There is no doubt that people-related data can be HR’s most important asset. Today’s HR teams have access to large amounts of data, which brings great benefits for those who use that data intelligently. But, remember that data also brings its own unique set of potential pitfalls. For this reason, it is vital that careful data governance and address any foreseen challenges that may surround employee-related data or the implementation of any data-driven HR approach.

Topics: Performance Management, HR Analytics