Charles Kim

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On April 18, 2022, Charles Kim commented on Drowning in Data: The Incoming Tech-sunami in People Analytics :

This got me thinking about how much I struggled initially in LPA despite being highly educated (compared to the general population) and relatively quantitatively trained (relative the key term there). I also remember feeling the temptation to draw easy conclusions as we were doing our LPA assignments. Though there are many in the workforce that are rigorously trained in statistical analysis, I wonder that the trajectory of growth in the sheer volume of data and analytical jobs may quickly outpace the appropriately trained labor pool. The supply demand imbalance here has potentially dangerous implications and feels inevitable – 20 years from now, I’m sure LPA will have plenty of cases about people analytics gone wrong with grim consequences for the company and its employees. It’s important as managers to keep this in mind and ensure we have the proper talent in place first before we jump into the mountains of data at our disposal.

On April 18, 2022, Charles Kim commented on Can People Analytics Curtail The Great Resignation? :

In theory, this sounds like a fantastic tool but I wonder if there are tangible real life examples of positive applications of such predictive analytics with supporting data. Companies that invest in such initiatives will have a real competitive advantage in the new reality of the labor market that is impacting both blue and white collar industries.

On April 18, 2022, Charles Kim commented on Focus on the most impactful applications of predictive analytics :

Totally agree with you on this. The privacy concerns are obvious and will pose a big barrier to adoption. But even if that wasn’t an issue, it is difficult to see what the meaningful insights ConnectMe can pick up that will actually drive the outcome desired – employee engagement / satisfaction. Overall, this feels very much like a cool, shiny toy for HR and at best a “nice-to-have”. Definitely not worth the cost of development, implementation and lost employee trust from privacy concerns. Predictive analytics can be powerful and they may be onto something here but they need to identify a key use case / linkage to the desired outcome before pushing out broadly.