Tribal Knowledge: The Silent Killer of Automation Projects

Process automation is the promised land. It whispers of efficiency, reduced errors, and liberated employees, free to focus on more strategic, creative work. Businesses are racing to embrace it, lured by the potential for significant cost savings and competitive advantage. But hidden beneath the surface, often lurking in the shadows of well-intentioned initiatives, lies a significant obstacle: tribal knowledge. 

Tribal knowledge, the undocumented, unwritten, and often unspoken understanding of how things really work, can act as a silent saboteur, undermining even the most meticulously planned automation projects. It’s the secret handshake, the unarticulated workaround, the unspoken assumption that separates a smoothly running process from a glitch-ridden nightmare.

This article delves into the treacherous waters of tribal knowledge and explores why it’s such a significant hurdle for process automation. We’ll unpack the challenges associated with identifying and capturing this elusive information, and examine practical strategies for navigating this obstacle and ultimately unlocking the full potential of automation.

What Exactly is Tribal Knowledge?

Tribal knowledge, also known as tacit knowledge, is the information held by individuals or small groups within an organization that isn’t formally documented. It’s the “how-to” beyond the SOP, the nuanced understanding of context, the learned experience that allows employees to navigate exceptions and unexpected situations.

Think of it this way:

• Documented Knowledge: The formal procedures outlined in training manuals, standard operating procedures (SOPs), or online knowledge bases. This is the ‘official’ way of doing things.
• Tribal Knowledge: The “real” way things are done, including the undocumented shortcuts, workarounds, and best practices developed over time by individuals or small teams.

It’s the difference between reading a cookbook and actually cooking a dish. The cookbook provides the ingredients and steps, but it doesn’t convey the feel of the dough, the sizzle of the pan, or the instinctive understanding of when to adjust the seasoning.

Examples of tribal knowledge in action:

• A customer service representative who knows which unwritten escalation paths yield the quickest resolution for specific client issues.
• A finance clerk who understands which invoice fields are frequently prone to errors and knows how to identify and correct them quickly.
• A warehouse employee who has mastered the art of squeezing the maximum number of boxes into a truck, using undocumented packing techniques.
• A software developer who knows the obscure dependencies between different modules of a legacy system.

While tribal knowledge can be incredibly valuable in the short term, allowing employees to solve problems creatively and efficiently, it becomes a significant liability when automation is introduced.

The Automation Impasse: Why Tribal Knowledge Blocks Progress

Process automation relies on predictability and defined rules. It requires understanding every process step, including the nuances and exceptions. Tribal knowledge, by its very nature, is unpredictable and undocumented, creating a significant roadblock to successful automation.

Here’s why:

1. Incomplete Process Mapping: Automation efforts typically begin with process mapping, a vital step in understanding the current state. However, if tribal knowledge isn’t captured during this process, the map will be incomplete, reflecting only the intended process, not the actual process. This leads to an automated system that doesn’t accurately reflect reality and can fail to handle real-world scenarios.
2. Unforeseen Exceptions and Edge Cases: Documented processes often focus on the ideal scenario, neglecting the countless exceptions and edge cases in day-to-day operations. Tribal knowledge is often the repository of how to handle these exceptions. Without this knowledge incorporated into the automation design, the system will stumble when faced with unexpected situations, requiring manual intervention and negating the benefits of automation.
3. Inaccurate Data Analysis: When processes are partially automated, the data generated may be skewed by undocumented workarounds. For example, suppose a report shows that 95% of invoices are processed within 24 hours, but the other 5% are manually expedited based on tribal knowledge. In that case, this hides the true bottlenecks and prevents effective optimization of the overall process.
4. System Instability and Errors: Automating based on incomplete knowledge can lead to system instability and errors. If the system doesn’t account for certain data validation rules known only by a few individuals, it may process incorrect data, leading to costly mistakes.
5. Resistance to Change: Employees with tribal knowledge may feel threatened by automation, fearing it will render their expertise obsolete. This can lead to resistance to the project, either passively (withholding information) or actively (sabotaging the implementation).
6. Increased Maintenance and Support Costs: An automated system built on incomplete knowledge will require significantly more maintenance and support. When errors occur, troubleshooting will be more complex, as the underlying reasons for the error may not be immediately apparent.
7. Difficulty in Scaling Automation: If the initial automation project is successful only because of the unacknowledged contributions of individuals with tribal knowledge, scaling the automation to other areas of the business will be difficult. Hidden dependencies and undocumented workarounds will become a barrier to expansion.

The Challenges of Capturing Tribal Knowledge

Capturing tribal knowledge is easier said than done. It’s not simply a matter of asking employees to write down everything they know. Several challenges make this task particularly difficult:

1. Unconscious Incompetence: Employees may not even be aware of the knowledge they possess. They perform certain tasks so routinely that they’ve become second nature, and they don’t realize these actions are not explicitly documented. “We’ve always done it this way” is a common phrase that masks a wealth of undocumented knowledge.
2. Difficulty Articulating Tacit Knowledge: Even when employees are aware of their knowledge, it can be challenging to articulate. Tacit knowledge is often intuitive, based on years of experience and observation. It’s the kind of knowledge that is best demonstrated rather than explained.
3. Lack of Time and Resources: Employees are often overloaded with their daily tasks and may not have the time or resources to document their knowledge. Management may also be reluctant to invest in knowledge capture, seeing it as a non-essential activity.
4. Fear of Exposure and Vulnerability: Some employees may be hesitant to share their knowledge, fearing it will expose their mistakes or make them vulnerable to criticism. They may also be afraid that their knowledge will be misused or that it will diminish their value to the organization.
5. Lack of Motivation: Documenting knowledge can be tedious and unrewarding. Employees may lack the motivation to participate, especially if they don’t see any direct benefit to themselves.
6. Knowledge Hoarding: In some organizations, knowledge is power. Employees may deliberately hoard information, believing it gives them a competitive advantage or job security.
7. Rapid Turnover: High employee turnover can lead to a significant loss of tribal knowledge. When experienced employees leave, their knowledge often goes with them, leaving a gap in understanding.

Strategies for Unearthing and Leveraging Tribal Knowledge for Automation

Despite the challenges, capturing and leveraging tribal knowledge is essential for successful process automation. Here are some strategies to help you navigate this complex landscape:

1. Embrace a Culture of Knowledge Sharing: Foster a culture that values knowledge sharing and collaboration. Encourage employees to document their processes, share their experiences, and learn from each other. Implement knowledge management systems and reward employees for contributing to the collective knowledge base.
2. Employ Observational Techniques: Don’t rely solely on interviews and questionnaires. Observe employees as they perform their tasks. Shadow them, ask questions about their decision-making processes, and document their actions.
3. Facilitate Collaborative Workshops: Bring employees from different departments or teams to discuss their processes and identify areas of overlap and conflict. Use whiteboarding sessions and brainstorming techniques to uncover undocumented knowledge.
4. Conduct Process Mining: Use process mining tools to analyze event logs and identify the actual flow of processes. This can reveal discrepancies between the documented and real processes, highlighting areas where tribal knowledge is being applied.
5. Implement “Lunch and Learn” Sessions: Organize informal sessions where employees can share their knowledge and best practices in a relaxed setting. These sessions can be a great way to uncover hidden gems of information.
6. Create “How-To” Videos and Tutorials: Encourage employees to create short videos or tutorials demonstrating how to perform specific tasks. This is a particularly effective way to capture tacit knowledge.
7. Document Exceptions and Workarounds: Create a system for documenting exceptions and workarounds. When employees encounter an unusual situation, encourage them to document how they resolved it. This knowledge can be used to improve the automation system.
8. Involve Employees in the Automation Design: Don’t design the automation system in isolation. Involve employees in the design process, soliciting feedback and incorporating their knowledge into the system. This will not only improve the system but also increase employee buy-in.
9. Provide Adequate Training and Support: Ensure employees are adequately trained on the new automation system. Provide ongoing support and address any concerns or questions they may have.
10. Iterative Implementation and Continuous Improvement: Don’t automate everything simultaneously. Start with a small pilot project and gradually expand the automation to other areas. Continuously monitor the automation system’s performance and make adjustments as needed. Regularly revisit and update the documentation to reflect process changes and tribal knowledge.
11. Incentivize Knowledge Sharing: Offer rewards and recognition for employees who actively contribute to capturing and sharing tribal knowledge. This could include bonuses, promotions, or public acknowledgment.
12. Exit Interview Goldmine: When employees leave the organization, conduct thorough exit interviews to capture any remaining tribal knowledge they possess. This is a valuable opportunity to document undocumented processes and best practices before they are lost.

Embracing Tribal Knowledge as a Catalyst for Automation Success

Tribal knowledge is not an insurmountable obstacle to process automation. In fact, when approached strategically, it can be a valuable asset. By proactively identifying, capturing, and incorporating this knowledge into the automation design, you can create a system that is not only efficient but also adaptable and resilient.

The key is to embrace a collaborative and knowledge-sharing culture, involve employees in the design process, and continuously monitor and improve the system. By viewing tribal knowledge not as a threat, but as an opportunity, you can unlock the full potential of automation and transform your business for the better. Instead of trying to eradicate tribal knowledge, aim to harness its power to create smarter, more effective, and more sustainable automated processes. The future of process automation lies not just in technology, but in the skillful integration of human knowledge and machine intelligence.