Smart Knowledge Management

How Can Plants Capture Tacit Knowledge

Andreas Eschbach, CEO and Founder

Who holds critical knowledge in your organization—and what happens if they leave? As experienced workers retire or move on, they take important institutional knowledge with them. Without a concrete plan for capturing, preserving and disseminating that knowledge, much of it could be lost forever.

Safe and efficient running of plant processes depends not only on documented procedures and explicit training, but also on the tacit knowledge gained from experience on the job. A smart knowledge management system can capture both kinds of knowledge and make it usable for workers.

Explicit, Implicit and Tacit Knowledge: What’s the Big Idea?

In a complex environment such as a process manufacturing plant, workers need both explicit and implicit knowledge to do their jobs well.

  • When workers start a job, they are provided with explicit knowledge in the form of easily documented processes and manuals, which guide most of their daily activities.
  • With training and experience, workers develop the implicit knowledge to help them get things done. Implicit knowledge is what lets us get through our days without checking a guidebook for every task or decision.
  • A lot of implicit knowledge is tacit knowledge—in other words, knowledge and skills gained solely through hands-on experience or socialization and not formally documented.

Long-time employees in process plants often hold tacit knowledge that keeps plants running smoothly and enables better troubleshooting and decision-making. For example, a production staff may observe unusual, wetter conditions and can remember times when it exhibited a particular behavior and what worked to resolve the problem.

Where is knowledge held in your plant?
Where is knowledge held in your plant?

Where is knowledge held in your plant? Explicit knowledge—such as training materials, standard operating procedures (SOPs) and documented data—is objective, reusable and fairly easy to collect. Tacit knowledge, gained through hands-on experience or socialization, is the deeper knowledge that guides much of the daily activities and decisions in the plant.

Capturing Tacit Knowledge with AI

With an experienced workforce, transfer of tacit knowledge usually happens organically: “Hey, Bob, what do you think about these numbers?” “Mary, can I get your advice on this formula?” But what happens when Bob and Mary leave? Where will new workers go to find answers to questions that aren’t spelled out in the manual?

A lot of critical insights are hidden in documents such as shift handover logs, emails, equipment inspection notes, and ad hoc communication between employees. They can be preserved through a centralized digital Plant Process Management (PPM) system.

But collecting data is only step one in an effective knowledge management solution. Employees also need to be able to extract it on demand. This is especially important when something unexpected happens, such as an equipment failure or an unexplained product quality problem. Most issues have precedents that can be used to guide effective responses. However, sifting through shift logs and historical data can be extremely time-consuming—especially if you’re not sure what you’re looking for.

This is where AI tools like Natural Language Processing (NLP) can help. NLP is a form of AI that allows people to query a system using plain human language (e.g., “When was the last time Mixer A experienced overheating?”). A Smart Search system powered by NLP can understand the questions people ask and return the answers that are most relevant and useful. This saves significant time over traditional keyword-based search engines, which may require the user to sort through a large number of results to find relevant information. With AI, a Smart Search system can exclude irrelevant results and put the most relevant ones at the top of the search.

AI-powered search systems may even be able to synthesize and summarize information from multiple sources to answer the question directly. The ability to synthesize information from historical logs could lead to Solution Suggestion systems to power better problem solving. Similar to online product recommendation systems, these systems will rank optimal solution strategies based on similar scenarios and their resolutions found in logbooks. This will vastly reduce troubleshooting time by pointing employees to the solutions that have worked in the past.

Preserving Institutional Knowledge

Creating a centralized knowledge management system capable of capturing tacit knowledge will be increasingly important in the future. Many plants are facing a loss of institutional knowledge as long-time employees retire or leave the industry. It takes up to five years for new employees to get fully up to speed with both formal processes and procedures and informal knowledge held within the history of the plant and their team. At the same time, trends in automation mean that there are fewer people within the plant to hold this tacit knowledge. That makes it vitally important to capture the knowledge of today’s workforce and make it easily available for future employees.

Now is the time for plants to be addressing the knowledge problem. Smart Search, Solution Suggestion and other forms of AI assistance will help tomorrow’s workforce get up to speed quickly and optimize both plant performance and their own.

Learn more about how AI and Natural Language Processing are transforming plant process management.

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