Technology Innovation

Unleashing Efficiency: Bridge Knowledge Gaps with Automation

Knowledge is power. Companies rely on their accumulated knowledge to drive processes, innovation, and growth. In this article, we talk about the impacts and causes of inadequate knowledge management and how our "Automation Thinking" approach can offer a solution.

October 2023
min read
Tim Pensel
Senior Innovation Consultant at Motius
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In today's rapidly changing world, knowledge is power. Companies rely on their accumulated knowledge to drive processes, innovation, and growth. Effective knowledge management forms the foundation for efficient operations, informed decision-making, and sustainable growth. Particularly due to implicit and thus person-specific knowledge, there is a significant challenge in knowledge management for company processes. I have taken this as an opportunity to write about the impacts and causes of inadequate knowledge management and how our "Automation Thinking" approach can offer a solution.

Knowledge Management & Process Know-how

But first, let me briefly explain what knowledge management and process know-how are. Knowledge management involves the capture, organization, and utilization of institutional knowledge within an organization. This also includes implicit knowledge, which is information and procedures that are inherently unspoken and tied to individuals themselves. Also, process know-how refers to a comprehensive understanding of work procedures, methods, and best practices that describe business operations.

Inadequate Knowledge Management & Its Consequences:

This process know-how is often implicit knowledge, meaning it's not formally documented. Let's first examine the consequences of insufficient knowledge management:

Operational Inefficiencies: A lack of well-structured knowledge repositories can result in time wasted searching for information, leading to delays and inefficiencies in critical processes. We’ve observed this in nearly every company.

Barriers to the Learning Curve: New employees face flatter learning curves when crucial process knowledge isn't readily available, hindering their ability to contribute effectively. This is very common in areas with recent restructuring or cross-functional nature, such as strategy or product/project management.

Stagnant Innovation: Limited process know-how can hinder innovation as employees struggle to access and leverage existing knowledge to drive new ideas. Innovation departments often struggle to systematically document knowledge, such as from past projects, to purposefully advance technologies and projects.

Risk of Errors: Without proper process knowledge distribution, employees may inadvertently deviate from established protocols, leading to errors and quality issues.  We’ve seen that especially in companies with high integrity regulations and inappropriate process know-how - "better safe than sorry" mentality as no one wants to be a black sheep.

How These Knowledge Gaps Occur

No one wants poor knowledge management, yet it is the reality in many companies. Why is that? In our experience, these are the most common reasons for inadequate knowledge management:

Unstructured Knowledge Repositories

What we often see are incomplete or disorganized knowledge repositories, e.g., unstructured knowledge storage and data repositories, inadequate or hard-to-access process descriptions, knowledge repositories without adequate search functions, no consolidation of insights from past projects. This fundamentally leads to knowledge gaps and makes it difficult for employees to access precise information.

Employee Turnover

A second aspect we often see is when experienced employees leave without transferring their expertise, the organization faces a significant loss of the aforementioned implicit knowledge. The lost knowledge often includes not only process know-how but also implicit, long-standing experiences that are not documented, such as considerations for a complex manufacturing step to minimize waste.

Lack of Documentation

Another crucial aspect is an organization's ability to document established processes and best practices. The weaker this capability, the lower the chance that employees receive clear and updated instructions. When it's unclear what needs to be done, existing knowledge gaps are exacerbated.

Deliberate Information Silos

Departments hoard knowledge within their sphere of influence (their silos) to assert themselves against other individuals or areas. Of course, this limits the distribution of critical process information across the organization and therefore, it is very toxic. Although such egoistic behavior is a disadvantage for the collective sum of the company, this is widely seen in big corporates.

Dynamic Changes

The final aspect is less connected to behavior and more connected to external factors. In our current world, markets, competition, and technologies are rapidly changing. These rapid changes condense in internal processes or their offered products/services. This may lead to quickly outdated knowledge which makes existing know-how obsolete.

Closing Knowledge Gaps and Increase Efficiency

The weak spots should now be evident. Let's focus on the important matter: How can the resulting knowledge gaps be effectively bridged? With new technologies such as Machine Learning (ML), Language Models (LLMs), Chatbots, or Knowledge Graphs (KG), information can be structured and understanding of existing data can be improved. This enables more advanced forms of data analysis and the development of knowledge and its (more effective) distribution.

At Motius, we believe that automation can bridge the gap between implicit information and established knowledge. For better understanding, I have listed some examples of improved knowledge management below:

  1. Centralized Knowledge Management: Implement process automation tools to centralize knowledge repositories, ensuring that up-to-date information is accessible to all stakeholders.
  2. Automated Onboarding and Training: Utilize automation to deliver personalized onboarding and training materials, easing the learning curve for new employees.
  3. Intelligent Knowledge Capture: Deploy automated procedures to capture insights from experienced employees before they depart, preserving valuable process know-how.
  4. Real-time Updates: Automated notifications ensure that employees are informed about process changes in real-time, reducing the risk of outdated knowledge.
  5. Collaboration Enhancement: Automation tools foster collaboration by connecting employees with relevant experts, promoting knowledge sharing across departments.
  6. … there are so many more potential benefits!

Now What? Ask The Right Questions

Poor knowledge management and limited process know-how present significant challenges to companies striving for efficiency and innovation. Automation Thinking can offer an approach to scrutinize the process landscape and identify potential solutions to address these challenges.

Here is an overview of the technologies in terms of their level of automation and their placement in the value chain:

By automating knowledge distribution, centralizing knowledge repositories, or enhancing collaboration, companies can close existing knowledge gaps and effectively support their employees. We are already in the age of increasing automation. It is evident that companies focusing on improved knowledge management through automation can continuously enhance their competitiveness by optimizing operations, reducing costs, and improving decision-making.

Time to ask some hard questions, like:

  • Which automation approach do you want to take?
  • What processes to look at?
  • Which knowledge sources should be centralized?
  • Which processes are appropriate for automation?
  • Which departments can support?

In our Automation Thinking Workshop, we work in collaboration with ROI-EFESO to provide precise answers to these questions. We offer tailored consultation for company-wide automation. Combined with our extensive expertise in technology and design thinking, we enable a holistic perspective. Motius has years of experience in the fields of data management and analysis, robotics, and drones, as well as modern AI tools like chatbots, LLMs (Large Language Models such as ChatGPT), and knowledge graphs. In our Automation Thinking Workshop, you can access this expertise.

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