KNOWLEDGE RETENTION IN MECHANICAL AND PLANT ENGINEERING: CHALLENGES & STRATEGIES 

Retaining knowledge in mechanical and plant engineering is essential to ensure a company's ability to compete and innovate. In this article, we look at the challenges and strategies required to retain valuable expert knowledge.

Contents

• The importance of knowledge retention in mechanical and plant engineering
• Challenges in knowledge retention
• Strategies for effective knowledge retention
• Use of AI-based solutions

The importance of knowledge retention in mechanical and plant engineering

Knowledge retention plays a crucial role in mechanical and plant engineering. The knowledge of employees is a key factor for the innovative strength and competitiveness of a company. Strategic expert knowledge that has been built up over the years not only ensures smooth operations, but also continuous improvements and the development of new business models.

Without targeted measures to retain knowledge, a company runs the risk of losing valuable knowledge when key personnel leave. In the worst case scenario, this can lead to production downtime, quality problems and a loss of market position/competitiveness. It is therefore essential for companies to deal intensively with this issue and find solutions, which we will discuss in more detail in the text.

Challenges in knowledge retention

Companies are becoming increasingly aware of the importance of knowledge retention. However, it is also associated with various challenges - which is why implementation is still somewhat lacking.

The problem is not identifying the knowledge holders in the company. Everyone in the respective department knows who knows their machines like the back of their hand. You know who to ask when you have an urgent repair task on a particular machine. And now imagine that this person is no longer available. For whatever reason. Let's assume a well-deserved retirement...
Who does the team ask then?

"Helmut once explained that to me!
Wait, what was that again?"

or

"The machine has its own special features.
Helmut always knew the right trick!"

Like that and similar...

A frequently mentioned challenge is the amount of time required to record and document knowledge. Many employees are so involved in day-to-day business that they have little time for additional tasks such as documenting processes.

Another obstacle is the resistance, or rather the reluctance, of employees to pass on their knowledge. This can result from a

• fear of losing power ("I don't want to be replaced by a robot and lose my job.")
• or uncertainty regarding data security.
• In addition, there is often a lack of clear responsibilities
• and suitable tools to systematically organize knowledge retention.

It is important that companies take these aspects seriously and allay their employees' fears - especially the issue of replacement by automation and job loss!

Strategies for effective knowledge retention

Targeted strategies are necessary to ensure knowledge retention in the company.

• One possibility is the implementation of knowledge management systems that facilitate the exchange and documentation of knowledge (like the Documentation HUB)
• The use of language models (such as Chat GPT, Gemini, Nvidia, Watson, ...) has long been known from websites that use chatbots to sort initial inquiries and forward them internally to the right department. Admittedly, many chatbots are not yet fully developed and, from personal experience, you can quickly become annoyed by the limitations of the bots. However, there are really good bots that fulfill their purpose. These can also be used internally to find relevant internal company information, such as repair instructions for the company's own machine.
• Regular training courses and workshops can also help to spread and deepen knowledge within the company. bitnamic CONNECT 's "Academy HUB" offers a tool for knowledge transfer in onboarding, training and further education for internal teams as well as for customers.
• Mentoring programs, in which experienced employees pass on their knowledge to younger colleagues (i.e. mixed experienced teams with different age groups) are also a tried and tested method.
• In addition, clear processes and responsibilities should be defined in order to promote and secure the transfer of knowledge.
• Just as the knowledge of long-serving employees is passed on during onboarding, this can also happen with well-structured offboarding, where the team member who leaves the company passes on / stores their knowledge.
• At best, the valuable knowledge is stored in an existing database, a "single source of truth", and thus saved from being lost.

Use of AI-based solutions

Artificial intelligence (AI) offers innovative possibilities to support knowledge retention in the company. AI-based solutions can analyze large amounts of data and extract valuable insights. These technologies can be used, for example, to identify and close knowledge gaps in a targeted manner.

AI can also be used to create automated knowledge databases that can be accessed at any time. This not only facilitates access to relevant knowledge, but also ensures that the knowledge base is continuously updated and expanded.

With numbers of a german Statista survey from 2024 “Where is AI used in your company?”: 26% use of AI in production (and 36% with planned use of AI), we are not doing too badly in Germany. However, we could use a lot more support in our day-to-day work.

Best practices include holding regular knowledge workshops and establishing an open corporate culture that promotes knowledge sharing. The integration of knowledge retention into the corporate strategy and the continuous adaptation of measures to current challenges are also crucial.

Digital pioneers combine several elements:

• Knowledge platform + semantic search + LLMs (e.g. GPT-4 with company data)
• Automatic recording of meetings/processes (e.g. with Fireflies, Otter.ai, Fathom)
• Automated generation and versioning of SOPs and documents
• Role-based access rights and data protection (GDPR-compliant)
• Continuous training with internal knowledge (retrieval augmented generation)
  
  

Companies that adopted knowledge management systems and AI-based solutions at an early stage report measurable gains in productivity and innovation. According to Capgemini Research, 84% of the companies surveyed state that AI has significantly improved their knowledge management.

“With the help of AI-based knowledge management, we drastically reduce the time spent searching for information and increase the reusability of know-how.”
- Cedrik Neike, CEO Siemens Digital Industries (Source: Siemens AI Strategy 2023)

Best practices in knowledge management include not only holding regular knowledge workshops, but also an open corporate culture that rewards the active sharing and preservation of knowledge. 

Successful companies such as Swisscom or BASF also explicitly anchor knowledge retention in their corporate strategy - for example by introducing AI-supported knowledge platforms or systematically documenting projects in knowledge databases.

The dynamic adaptation of measures is also crucial: At the Otto Group, internal knowledge management is regularly evaluated and adapted to technological developments such as chatbots or LLM integrations.

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If you have any questions about knowledge retention in your company, please do not hesitate to contact us!