The Great Resignation and What It Revealed About IT Talent

In the spring of 2021, a friend working in IT operations at a mid-size logistics company told me that six of his team's fourteen people had left in the previous three months. Three were developers. Two were in infrastructure. One was the person who had the most institutional knowledge about the company's legacy ERP, including an undocumented workaround that had been in place since 2014 keeping a critical inventory process running. When that person left, the workaround went with them. Not entirely, but enough. The team spent three weeks reconstructing what the workaround was doing, why it existed, and what would break if it stopped.

This kind of story was not unique to that company or that spring. The "Great Resignation," the wave of voluntary job departures that accelerated across the U.S. workforce beginning in 2021, hit technology and IS roles with particular force. The Bureau of Labor Statistics reported elevated quit rates across the U.S. labor market during that period, with monthly quit levels in late 2021 reaching historic highs. Technology roles were especially affected because IT skills transfer across industries in a way that, say, specialized manufacturing skills do not. A data engineer at an insurance company is also a plausible candidate for roles at a healthcare system, a fintech startup, or a retailer. Remote work made the geographic labor market effectively national for most IS positions, which meant an IT professional in a mid-size city was suddenly able to compete for roles at organizations headquartered anywhere.

What I found interesting about the Great Resignation, from an IS research perspective, was what it revealed about how organizations actually understood their own workforce. Many organizations found out they had more concentrated institutional knowledge risk than they had realized. The people who left were not just filling headcount. They were carrying specific, largely undocumented knowledge about how systems worked, why architectural decisions had been made, and who to call when something broke. That knowledge had not been written down because it was not the kind of knowledge that gets written down easily.

Nonaka's (1994) SECI model is useful here. The distinction between tacit knowledge (embedded in practice and judgment) and explicit knowledge (articulable, documentable, transferable) explains exactly why the workaround my friend described was so difficult to reconstruct. The person who built it knew how to operate it. That is tacit knowledge. Writing down how it worked would have required converting that tacit knowledge to explicit knowledge through externalization, which takes time and deliberate effort and almost never happens under normal operating conditions. As I wrote about in my post on why knowledge management systems usually fail, this is a structural problem in how organizations treat knowledge, not just a documentation failure.

The talent shortage in IS roles pre-dated the Great Resignation by years. The cybersecurity skills gap had been documented consistently in industry reports. The demand for data engineers, machine learning practitioners, and cloud architects had been outpacing supply for much of the 2010s. What the Great Resignation did was compress a slow structural imbalance into a rapid, visible crisis. Organizations that had been managing a slow IT talent gap found themselves managing an acute one.

Gartner has consistently identified IT talent as a top concern for CIOs in its annual surveys of technology leaders, and has noted that competition for technology skills is requiring organizations to rethink how they attract and retain IT professionals (see https://www.gartner.com/en/newsroom for Gartner's current releases on this topic). I am hedging Gartner's specific skills gap statistics because I have not verified exact figures from specific report pages. The directional finding, that IT talent scarcity is a strategic-level concern, is consistent across years of Gartner CIO survey reporting.

The response from most organizations was to raise salaries and offer remote work flexibility. These are reasonable short-term responses, but they address supply-and-demand mechanics without addressing the underlying structural vulnerabilities that the Great Resignation exposed. High turnover in IS roles is most damaging when knowledge is concentrated, undocumented, and non-transferable. Raising salaries retains more people in the short run. It does not automatically improve how knowledge is distributed across the team.

There is a knowledge management argument here that I think IS researchers should take more seriously. The goal of a resilient IS workforce is not just to have enough skilled people at any given moment. It is to have knowledge that is organized and shared in ways that survive normal levels of turnover. Cross-training, documentation requirements, pair work, and code review practices are all, from this perspective, forms of knowledge transfer that reduce the concentration risk of any individual's departure. Organizations that invest in these practices are not just being good employers. They are reducing the institutional risk of normal workforce dynamics.

The other thing the Great Resignation revealed was how much the geographic constraint on IT labor had been artificially suppressing wages in non-gateway cities. An IT professional in Dallas or Denton or Austin was previously constrained to the local market unless they were willing to relocate. Remote work dissolved that constraint. For employees, this was straightforwardly good: more options, more bargaining power, more ability to find work that matched their skills and interests. For organizations that had historically benefited from geographic wage arbitrage within the U.S., it was a structural change in the labor market they were not prepared for.

I do not think the labor market for IS professionals has returned to its pre-2021 structure, even as some of the quit rate elevated numbers have moderated. The shift to remote work, the demonstrated transferability of IS skills across industries, and the awareness among IT workers of their market value have all changed the baseline. Organizations that treat IT talent as a simple hiring problem, find someone with the right skills, pay market rate, hire them, are going to keep being surprised. The real challenge is building organizational conditions where IT professionals want to stay and where what they know does not leave when they do.