Many organizations face knowledge-sharing challenges, but digital trailblazing leaders are driving the culture change necessary to develop organizational expertise.

When you develop AI agents, you’ll need subject matter experts to share knowledge and review results. Field operations, manufacturing shop floors, and construction job sites are all areas that require leadership, a transformative culture, and connected practices that drive continuous improvement. Teaching, sharing expertise, and challenging the status quo are often overlooked performance objectives, as many leaders only focus on quarterly results and incremental productivity gains.

The result, over many years, is a buildup of tribal knowledge, documentation debt, and rigid processes that are challenging to modernize.

Finding the root cause of tribal knowledge

We discussed this conundrum at a recent Coffee With Digital Trailblazers titled, The Real Cost of Tribal Knowledge: Why Losing Your People Can Bring Ops to a Standstill.

Bob Salaj is a principal industry analyst at Quickbase, focusing on the construction industry. He joined the episode as a special guest and shared what he asks himself and reviews when evaluating whether an organization is ready to change.  

Salaj asks, “Is the organization primed to receive feedback? What is the culture at its heart, and are leaders open to receiving employee recommendations? Or are the employees feeling reluctant to share their ideas for fear that they might be misconstrued as complaining? Perhaps they’ve actually provided feedback quite a few times, and it just goes on deaf ears, with no changes beginning to occur. So, what often happens is that a power of knowledge mentality prevails, and employees begin to hold on to what they know and have learned.”

Several speakers suggested other root causes. Change fatigue, overloaded priorities, and the perception that leaders view documentation as a waste of money were among the reasons cited.

Sharing expertise requires a culture change

“The cost of losing tribal knowledge isn’t just downtime—it’s lost innovation. AI gives us the chance to transform that hidden knowledge into a shared, compounding asset,” commented Jay Cohen, SVP of digital transformation at StarCIO. Another reason to promote knowledge sharing in manufacturing and construction is to accelerate their adoption of technology and AI that attracts top talent.

“Winning companies will make tribal knowledge obsolete by making expertise ubiquitous,” recommended Joe Puglisi, growth strategist and fractional CIO at 10xnewco. Joe suggests that leaders challenge their overuse of industry jargon and address a culture of arrogance as steps for driving change across the organization.

“Construction is starting to move forward with a lot of innovation around prefabrication and digital twins,” says Bob Salaj of Quickbase. “If you lose those people who have tribal knowledge, regardless of age, and you’re not documenting procedures and best practices, you’re going to be impacted by it.”

Below are four ways to overcome tribal knowledge and inspire developing expertise that we discussed during the episode.

1. Transform SOPs to dynamic work management

When we think of workflow and documenting standard operating procedures (SOPs), a picture of linear flows with simple if-this-then-that branching comes to mind. However, the real world is far more complex, particularly in manufacturing and construction, where weather, supply chain disruptions, and unexpected resource constraints necessitate making critical decisions on a daily basis.

Transforming to dynamic work management involves a shift in culture and mindset, as it necessitates flexibility in responding to complexity. Everyone in operations must contribute to knowledge sharing, as issues tend to repeat themselves, and there’s an opportunity to learn from past decisions. Leaders must also commit to eliminating the gray work – often spreadsheets, long-chain emails, unnecessary meetings, poor mobile user experiences, and system integration gaps – that prevent end-to-end collaborative workflows.  

2. Simplify the inputs with decision and change logs

How should teams capture knowledge? Documentation doesn’t need to be a lengthy MS-Word document, a Google Doc, a wiki, or other content management tools that require extensive writing and editing.

“I use QuickBase to create an application where we capture the dates around lessons learned,” recommended Bob Salaj.

Two of the easiest tools I recommend teams to develop are centralized decision logs and change logs. I often implement these using low-code tools and then develop automation pipelines to create notifications in MS Teams, Slack, and other collaboration tools.

Why this approach?

• Simplifying the inputs makes it easier to share knowledge.
• Centralizing captures the information with uniform metadata and categorizations.
• Pipelines deliver the information to expand consumption.  

3. Expand knowledge sharing with AI everywhere and AR/VR in the field

Martin Davis, managing partner at DUNELM Associates, shared how manufacturers ease knowledge consumption on the factory floor. “An engineer in a manufacturing plant is walking the line with a head-up augmented reality (AR) display showing them information about the equipment they’re looking at. That information is aggregated from various sources, including SOPs, small language models, and sensor data. They can review how well a machine is operating, access the previous maintenance history of that equipment, and examine the actual maintenance steps.”

The lesson here is that expertise can be optimized to the most needed information at the right time through the most useful device and form factor. Capturing and centralizing people’s expertise fuels the AI, which then tailors what people need to review to make quick, accurate, and safe decisions in the field.

4. Set leadership responsibilities and employee incentives

While all speakers acknowledged the importance of leadership, three comments stand out regarding what digital trailblazers are doing differently to drive knowledge sharing.

“We need to approach knowledge management differently,” says Joanne Friedman, CEO of RealAI. “The IT perspective is that it’s about documentation, but it’s really not. It’s about community. It’s about getting people over the notion that, if you don’t keep your knowledge to yourself, you’re going to lose your job. Communicate that knowledge sharing is the same as learning, and if we’re continually learning, we’re continually growing, and that benefits everyone.”

Changes in mindsets are best backed by aligning incentives.

John Patrick Luethe, owner of Comfort Keepers of Seattle, told the story of an employee at a large company. “Every time he finds an issue with the documentation, or he finds a better way to fix something, he writes it up, and if it gets accepted, he gets $300 to $1,000.”

Leaders can then turn to the tools and processes that simplify workflows and documentation efforts. “We see a world of AI that’s not only for building applications that really match your workflows exactly, and for mining the data, but where it also documents itself,” says Bob Salaj of Quickbase.

Listen to the full episode on The Real Cost of Tribal Knowledge: Why Losing Your People Can Bring Ops to a Standstill and learn more about centralizing work in one place.

This post is brought to you by Quickbase.

The views and opinions expressed herein are those of the author and do not necessarily represent the views and opinions of Quickbase.