18 Insights from the 2019 Human Capital Analytics Conference

Our Privacy Policy has been updated! The Conference Board uses cookies to improve our website, enhance your experience, and deliver relevant messages and offers about our products. Detailed information on the use of cookies on this site is provided in our cookie policy. For more information on how The Conference Board collects and uses personal data, please visit our privacy policy. By continuing to use this Site or by clicking "OK", you acknowledge our privacy policy and consent to the use of cookies.

18 Insights from the 2019 Human Capital Analytics Conference

November 18, 2019 | Article

“I never guess. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”

Sir Arthur Conan Doyle, author of Sherlock Holmes

Better Decisions, Better Organizations, Better Results

Human resources is being transformed by data and analytics. What used to be led by best practices and guesswork can now be quantified. While that’s been valuable in establishing the importance and effectiveness of various HR policies, the transition comes with challenges. When hundreds of leaders met to talk about HCA, we took notes. Here are the highlights:

Having the data is not enough; companies today need to turn that data into insights.

Analytics can't just predict the future; they also need to offer actionable insights. For instance, knowing that attrition is high in a region or department is not particularly useful. But knowing that lateral promotions can significantly reduce attrition is an actionable insight.
Companies are starting to use machine learning and artificial intelligence to analyze and sort data–whether it’s finding trends or insights from employee surveys or identifying top candidates from a pile of resumes. The difficulty is that even when machine learning or artificial intelligence gets it right, it doesn’t always know why. Explaining why is important to garnering support. Also, be aware that using AI to automate hiring has revealed some inherent, learned biases. Algorithms can be tweaked, but teams need to know what factors