People data practitioners must do a careful analysis of their personal capabilities along with their organizations’ and be selective about when and where to collect and use data to prove the value of that approach
By now, HR practitioners at most organizations are familiar with artificial intelligence (AI) or machine learning (ML) and understand the foundations that must be established before building a solid people data and analytics program.
“Organizations know they struggle with the foundational aspects of data and analytics: collection, insights and subsequent action from those insights,” said Brandon Hall Group CEO, Mike Cooke. “For organizations to make headway into more advanced uses of data such as artificial intelligence (AI) or machine learning (ML,) they must first create a base of clean, trustworthy data from a variety of sources.”
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However, it is the organizations that are holding some programs back by not providing sufficient resources to change-management services to transform their organization into an evidence-based culture.
“When looking at the current state of data sources, insights and actions taken from that data, most organizations would rate themselves as average to below average. Very few companies (less than 15%) rated themselves at the highest score”, said Brandon Hall Group Analyst, Cliff Stevenson.
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Working with data instead of using past experiences or intuition as a guide can seem like a more objective exercise, but if the proper resources aren’t engaged in cleaning, analyzing and monitoring the data, it is no better than those other methods.
Organizations report difficulty assigning resources to data issues, but this can cause systemic problems if sufficient resources are not allocated. Taking shortcuts in the initial stages will cost more time down the road, so ensure data efforts are well-planned out with ample resources dedicated to the task.
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