Great insights, Sofía. I liked how you built an argument on caution on a too accelerated shift to AI in hiring when there is a need for more data analysis training in HR, which is truly an area that is deemed dependent on soft skills and empathy.
Hi Meghna, this is a great article as it gives context and clearly articulates your point. I would like to dig deeper into the role of academia as gatekeepers of mobility data. In countries where governments and public institutions are weak, academia can serve the role of gatekeepers, as when a truly independent and accountable committee of universities is assembled.
In the US, I would be interested to understand if any conflict of interest arises when an institution such as Harvard stands as a gatekeeper. Could Harvard’s endowment or funding be dependent in some way on corporations that use such data? Meanwhile, as it counts on world-class academics ready to build standards and do research on how to manage such data, Harvard has, at least, the leverage to play a role in establishing a proper framework on this issue.
Happy to hear your thoughts!
Interesting post! I liked the way you framed criticism around this important issue, as the boundaries between control and structure seem to be blurred in Amazon’s initiative.
Starting with the business strategy in mind is an excellent practice to define the pillars of people analytics processes. As you say, it will potentially increase its buy-in within the company. As Michael mentioned, this would facilitate the definition of a skills matrix, their evaluation mechanism, and their data collection for later analysis.
Thanks for this great post. A data-driven culture needs to be internalized in the healthcare sector, which I see as a challenge, especially in developing countries. There is an opportunity to partner with academia, so programs and graduates can know beforehand what the industry needs and is expecting. I’m full of hope that both scenarios, the healthcare industry and higher education, can realize this, as there can be cultural factors potentially undermining this process.
Thanks for sharing this opinion, Sam. It is important to keep a critical stance on the use and value of data and refine the way we train our teams not only in the technical but also in the critical aspect of data analysis, to ensure we are able to see beyond initial conclusions and provide better value.
Thank you, EB, for generating conversation around this important event. I would be interested in understanding how to prevent both companies from using their new influence to define how people analytics data is analyzed, interpreted and communicated to clients, potentially arbitrarily, as their expertise will grow by combining talent from both companies, and as their scope of action will make them more influential. As regulation usually follows Innovation, concerns regarding employees’ privacy should be made a priority. The role of academia here is key.