What is Tribal Knowledge and why is it relevant for every manufacturer today?

Tribal knowledge in manufacturing is any knowledge(asset/process) that is not recorded or documented in any formal format/source. Subject matter experts most commonly acquire it through years of experience, knowledge & trial & error at a plant.

For Example, An operations engineer working at a power plant has to ensure that the plant is operating with frequent failures and loss of revenue due to inefficiencies. It can be as simple as how much temperature needs to be maintained for a generator not to be overheated or more nuanced like knowing when a machine is due for maintenance just by hearing how it sounds. 

These might seem like trivial things on the surface, but they can cost the manufacturer millions of dollars if not tended to in time. We still remember the catastrophes like the BP Deepwater Horizon Oil Spill and the Bhopal gas tragedy even after 50years. While people remember the failures, one should also acknowledge the countless saves that were enabled by the tribal knowledge of an experienced operator.

 

So why is tribal knowledge considered a solid threat to manufacturing today?

Around 25% of the United States population will be 50 years of age & older by 2025. A substantial part of the demographic (nearly 12 million) is a part of the manufacturing industry in the US, like senior subject matter experts, operators, supervisors who have been working with critical plant maintenance, plant operations for years. When they leave or retire, all the tribal knowledge accumulated over the years also disappears with them. The resultant knowledge or skill gap ends up flummoxing the newer workforce and causing the enterprise to lose its competitive edge, innovation & reliability. We discuss how utility leaders are addressing knowledge management with AI here.

Even if you consider the younger workforce only, the job-swinging millennials who take the acquired knowledge with them also are a huge reason for the burgeoning focus on democratizing tribal knowledge.

Capturing Tribal knowledge to make it institutional knowledge

The conundrum in front of manufacturers is to turn this ‘gut feeling’, ‘verbal tips’ into well-documented formal procedures that are available to everyone across the enterprise, enabling the same high level of performance & productivity across all shifts and plants. 

Some of the common ways adopted by manufacturers include oral training sessions, physical notebooks, online technical documentation, and digitization.

While verbal sessions & notebooks are not durable in the long-term, generally, most of these approaches depending on the written word, aren’t the most efficient or effective method or scalable. Even with digital documents, when manufacturers try to get the experts to document their tribal knowledge via crisp documents, it often ends up with the obvious aspects of the tribal knowledge but the nuances are often lost. Imagine asking an Olympic athlete to write a manual on replicating his success. We know that manuals cannot replicate the thought process, which is more complex.

While creating multimedia instructional videos to address specific issues is more effective, the problem is the lack of expertise/knowledge of the seeker to find the exact correct information when needed. Since the plant shopfloor is a dynamic environment with complex and interconnected systems, the same problem can manifest through various disparate symptoms. The operator can then get side-tracked and potentially miss a document/video critical to solving their issue.

How AI can convert tribal knowledge into institutionalized knowledge

With an AI application in the picture, the situation can be very different. A capable AI application like UptimeAI connects thousands of disparate machines, systems & processes in a scalable way, gaining a deep understanding through the past & real-time operational data. As the operator interacts with the system daily, the system tracks and learns what the operator is looking at to confirm the issue, what kind of maintenance activities are being taken and how quickly the issue is getting resolved. By labeling failures when they occur & learning & observing thousands of operators’ analyze and actions to address the issue, the system knows about why a process malfunctions and what would be the best resolution, democratizing tribal knowledge. It then can come up with the best prescriptive advice the operator should follow when such an issue reappears in the future. UptimeAI can become your virtual plant expert, by translating the operator’s tribal knowledge into institutionalized digital wisdom.

Conclusion

With SME’s retiring & brain drain from the newer workforce, tribal knowledge is the biggest threat to manufacturers to be resilient and agile today. Only when best practices of Subject Matter Experts are combined with the insights from machines & processes, can the manufacturer diagnose any issue, big or small, accurately before it occurs. Only then the plant maintenance can become the most efficient in the truest sense.

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