The Merger of Burning Glass and Emsi: A Monopoly on People Data?
In June of 2021, the two leading data providers for labor market analytics announced that they were merging to deliver on a joint mission to “to unlock opportunity, mobility, and equity for everyone.” How likely is this?
Amidst growing interest in the Future of Work and People Analytics in the last decade, two companies emerged as the leading data providers in labor market analytics: Burning Glass Technologies and Emsi. Burning Glass Technologies is a KKR portfolio company whereas Emsi was formerly owned by Strada Education Network, a nonprofit. In June of 2021, the companies announced that they were merging to deliver on a joint mission to “to unlock opportunity, mobility, and equity for everyone.” On one hand, their merger allows them to bring together top talent and top technology in this space to better advise on talent strategy for employers, higher education institutions, and economic/workforce development professionals. On the other hand, there are concerns that their merger may create a monopoly whereby highly valuable data on labor market trends becomes too expensive for customers beyond a handful of large employers. I am less concerned about this.
I believe labor market data is becoming more and more commoditized. At their core, both scrape online job openings (e.g., from Indeed) and job profiles (e.g., from LinkedIn) and leverage AI to create actionable insights on labor demand and supply at a hyper-local level. Both companies have spent years developing the technology to gather, clean, and analyze billions of raw data points across 30+ countries in real time. However, the exponential growth in AI, the plummeting cost of computing, and the wide availability of the raw data the companies use is making it such that either (1) other competitors emerge or (2) companies gather the same data in-house if Emsi Burning Glass over-charges. After all, the largest cost as a data provider is the cost of technical talent such as data scientists and engineers.
By merging, they are better positioned to improve the quality of the data and make it more widely available, not to restrict those who have access to the data. In fact, I believe that the value of the merger is not going to be the data itself but the solutions it builds with the data for its clients. For example, I could see the merged company developing a platform to help companies with site selection, bringing together a view of the competitors for the same talent as well as the skill gaps and surpluses in a location.
With that said, I worry that, by merging, the companies will no longer represent two alternative sources of truth, who glean different insights from the same data sets. Having been a customer of both data providers through the McKinsey Global Institute, they had very different approaches to certain analyses. For example, if you asked both companies the “top emerging skills on the year,” they would come back with different answers, neither of which were wrong. Given that data is highly open to interpretation, I hope that the merger will still foster diverse perspectives on labor market trends.
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I would love to hear from others the commercial uses they say with this data!
Very cool! I have heard of Burning Galss, but haven’t looked too much into their offerings, but I think after this course I would be very interested to.
This is great to keep our eyes on – I definitely agree, it seems like the running theme throughout people analytics is this balance between efficiency and loss of detail. In class, we talk about this in relation to data analysis in individual cases but it feels incredibly relevant when we zoom out and look at differences at the platform level. I’m really interested in seeing how this could depend on whether some managers feel overwhelmed or comfortable with diversity in analytic approaches.
Thanks for your thoughts on this extremely important challenge, E.B. It’s a question that dominates big tech, pharma, and now analytics. Often in mergers synergies are overestimated. I’d be interested to see if there’s an attempt to integrate the two companies or continue to operate them as separate entities, and share learnings frequently.
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.