The race to capture tacit knowledge
Why your firm needs to document what workers know before they leave forever
Quick summary:
Many traditional firms have been reliant upon “lifetime employment” models
The Great Resignation has seen many experienced people leaving the workforce
Tenured employees possess ‘tacit knowledge’ that is not formally documented
Younger employees may not overlap with outgoing workers, but need training
The end of the “apprenticeship model” puts firms at risk of losing expertise
New intelligent workflow systems and AI solutions can help bridge the gap
‘Old Faithful’ isn't as reliable any more
Last weekend, I had the opportunity to visit Yellowstone National Park and see the famous geyser called Old Faithful, named that because of the predictable schedule of its eruptions. I’d read about Old Faithful as a child and it was exciting to finally see it with my own eyes. However, I learned on my visit that Old Faithful is not as reliable as it was in the past: a few explanations were offered including a history of earthquakes in the area which impacts the thermal activity underground.
This loss of reliability is a predict metaphor for many traditional organizations I’ve spoken with over the past couple of years since the COVID-19 pandemic and subsequent Great Resignation. Many of these firms offer good paying jobs and generous benefits that previously attracted employees who devoted years of service in return. However, with the shifting job market dynamics today, the lifetime employment model is quickly being replaced. Younger employees aren’t as interested building a career with a single employer. Research shows that Gen Z does value training and wants to be mentored by a more seasoned employee who is not their direct supervisor. They also value the opportunity to do a variety of jobs and embrace more of a “career journey” than the traditional vertical “career ladder”. Many of these newer workers have been hired in an era of remote work, and have not had access to the type and quality of mentoring that they feel is necessary to gain confidence - making them more likely to leave organizations quickly.
The value of ‘tacit knowledge’ and why it matters
One of the main assets that organizations lose when experienced workers leave is what it known as tacit knowledge - the amount of information that is in an employee’s head but not formally documented anywhere. This type of knowledge is wide-ranging, from process steps to best practices to broader concepts such as corporate culture and being able to anticipate the needs of higher ups. Why isn’t this information captured anywhere or part of a formal training program? In the past, it was because the knowledge was passed down by word of mouth as part of an “apprenticeship model” where a more senior employee sat alongside a more junior employee and physically showed them process steps, walked them through IT systems, and explained in words “how things work around here”.
This approach has suffered a great deal during the past couple of years because of the pandemic and move to remote work. While sone mentoring took place, anecdotally it appears that much less of this sort of knowledge transfer and team building occurred. This makes sense because much of the move to remote work was quick and reactionary rather than meticulously planned out. Given that the future of work is likely a hybrid of in-person and remote work, it is time for organizations to think more broadly about how they acquire and retain talent. The way that tacit knowledge is acquired by new employees and retained within the organization when people leave is critically important. If it is not adequately captured and passed to others, you run the risk of wasted time and effort, a loss of efficiency and increase in failure rates that most organization cannot afford.
New ways can work, but don’t reinvent the wheel
So what are some ways to ensure that your organization does not suffer a loss of tacit knowledge? One way is to embrace new technologies that provide process automation and intelligent workflow solutions. In the past, many solutions were rules-based, macros or relied on fixed process steps as part of robotic process automation (RPA) that had to be updated whenever process steps changed. More modern solutions incorporate AI and can “learn” from observing keystrokes and employee behaviors without necessarily requiring significant “training” time. I call this “making dumb processes smart” whenever you can deploy AI behind-the-scenes of existing processes, then introduce automation after at the pace that’s right for your organization. Another idea is to place more emphasis on formal documentation from more seasoned employees with the idea that this should be created in anticipation that there will be gaps between employee departures and subsequent backfilling. In the past, documentation may have taking a long time to capture in written form, but more modern methods include short videos and screen captures to be more stimulating for new employees and easier to follow.
Finally, new employees have the benefit of seeing processes and systems for the first time and often find ways to make improvements that more tenured employees fail to see because they are too close to the work: they see the trees, not the forest. These initial insights are valuable and efforts should be made to capture and address them, making incremental improvements where possible. In fact, the absence of knowledge of “how things work around here” can be a benefit: it opens up possibilities that more established employees might not even consider. This instinct should be balanced, however, with the wisdom of “don't reinvent the wheel”: many initial questions about why something works they way it does have good answers that established employees can shed light on, preventing newer workers from pursuing dead ends.
Finding ways to capture tacit knowledge and ensure its wisdom is passed down throughout your workforce over time, especially encoding as much as possible in systems not people, is a critical step towards success innovation and making forward progress possible.
Does your organization have a formal process to capturing tacit knowledge? What has your approach been in the past? Are you leveraging newer technologies that enable intelligent workflows? Is your organization looking to applying AI widely throughout your operations to improve productivity and codify knowledge? Is there a risk of losing insights when incorporating AI into your operations?