Tacit Knowledge Transfer in Finnish Manufacturing Companies

Practice Paper Recommended citation: Suhonen, S. J., & Kankaanpää, R. A. (2025). Tacit Knowledge Transfer in Finnish Manufacturing Companies. In Kangaslampi, R., Langie, G., Järvinen, H.-M., & Nagy, B. (Eds.), SEFI 53rd Annual Conference. European Society for Engineering Education (SEFI), Tampere, Finland. DOI: 10.5281/zenodo.17631535. This Conference Paper is brought to you for open access by the 53rd Annual Conference of the European Society for Engineering Education (SEFI) at Tampere University in Tampere, Finland. This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License. TACIT KNOWLEDGE TRANSFER IN FINNISH MANUFACTURING COMPANIES S. J. Suhonen a, 1 , R. A. Kankaanpää b a Tampere University of Applied Sciences, Tampere, Finland https://orcid.org/0000-0002-3279-3813 b SASKY Municipal Education and Training Consortium, Sastamala, Finland Conference Key Areas: Engineering skills, professional skills, and transversal skills, Continuing education and life-long learning in engineering Keywords: Tacit knowledge, Knowledge transfer, Manufacturing Industry, Workforce training ABSTRACT Tacit knowledge, which is based on individual experience and intuition, is important to operational performance in the manufacturing industry. However, this type of knowledge is difficult to articulate, capture, or systematically transfer. One of the aims of Manufacturing Academy 2.0 project, co-led by Tampere University of Applied Sciences and SASKY Municipal Education and Training Consortium, is to support manufacturing companies in developing their own strategies for recognizing, retaining, and transferring tacit knowledge. This paper explores how tacit knowledge transfer is currently practiced in Finnish manufacturing companies and how these practices relate to the SECI model of knowledge creation. The study is based on 163 company interviews conducted during industry fairs, follow-up company visits, and a co-creation workshop with stakeholders from education and industry. Results show that while tacit knowledge is widely acknowledged as important, companies vary significantly in how systematically they approach its transfer. Socialization and internalization phases are the most established, while externalization and combination remain underdeveloped. 1 INTRODUCTION Tacit knowledge refers to the personal, experience-based knowledge that individuals possess but cannot easily express in words. It includes intuitive insights, implicit 1 Corresponding Author S. J. Suhonen [email protected] skills, and context-specific practices acquired over time. In the context of knowledge management and organizational learning, tacit knowledge is recognized as a critical but elusive asset that shapes innovation and operational excellence. In manufacturing, tacit knowledge manifests in the nuanced expertise of experienced workers who, for instance, can detect process anomalies from subtle changes in machine sounds or make decisions based on long-term, situational awareness. To address the growing risk of knowledge loss due to workforce aging, the “Manufacturing Academy 2.0” project aims to promote skills and training in key manufacturing processes in Pirkanmaa area in Finland. One part of the project is to help the companies to seek, identify, document, and transfer tacit knowledge (Nikander 2023). The project is led by Tampere University of Applied Sciences (TAMK) and the SASKY Municipal Education and Training Consortium and cofunded by the European Social Fund Plus (ESF+). This paper focuses on the pedagogical aspects that facilitate tacit knowledge transfer in manufacturing. 2 THEORETICAL FRAMEWORK One of the most famous definitions of tacit knowledge comes from the philosopher Michael Polanyi, who emphasized that we know more than we can tell (Polanyi, 1966). This suggests that a large part of human knowledge is internal and subjective and cannot be easily or completely articulated. In scientific literature, tacit knowledge is often dealt with as part of knowledge management and organizational learning. It explores how such knowledge can be identified, valued, and above all, how it can be shared within an organization to improve performance and innovation. Among manufacturing workers, tacit knowledge plays a significant role. It manifests in various ways, such as the ability of experienced workers to recognize the slightest changes in the sound or operation of machines that may indicate future problems, or the skill to make quick and effective decisions during the production process, based on years of experience and observations that may not necessarily be recorded anywhere. This type of knowledge may be critically important for the quality of products and innovation and transferring it to new employees is a central challenge for organizations. Mohajan (Mohajan, 2016) emphasizes that tacit knowledge is a crucial, yet often overlooked, component of an organization's knowledge base. Since tacit knowledge is often acquired through personal experience, manufacturing companies should encourage hands-on learning through apprenticeships, mentoring, and on-the-job training programs (Muñoz, 2015). While tacit knowledge is inherently personal and context-specific, certain technologies can aid in its transfer. For instance, virtual reality (VR) and augmented reality (AR) can simulate real-world scenarios for training purposes, making it easier for workers to gain insights into tacit knowledge without the direct intervention of a human instructor. Also, AR/VR technologies can be used to capture and digitize the expertise of skilled workers (Sarhan et al., 2022). The SECI model (Socialization, Externalization, Combination, Internalization), developed by Nonaka and Takeuchi (Nonaka & Takeuchi, 1995), provides a theoretical framework for understanding how tacit and explicit knowledge interact within organizational learning processes. The model consists of four dynamic phases, illustrated in the figure 1: socialization, externalization, combination, and internalization. The phases form a continuous, repetitive cycle of knowledge transformation. The socialization phase occurs when tacit knowledge is shared informally through observation, imitation, and hands-on interaction, such as in master-apprentice relationships. The externalization phase involves converting tacit knowledge into explicit knowledge by articulating it through discussions, visual demonstrations, or documentation. The combination phase integrates different pieces of explicit knowledge, refining them into structured learning resources such as training manuals or digital simulations. Finally, the internalization phase enables individuals to absorb explicit knowledge through practice, gradually transforming it into their own tacit expertise. Fig. 1. The SECI Model of Knowledge Conversion (Nonaka & Takeuchi, 1995). Tacit knowledge = Personal, experience-based knowledge that is difficult to articulate or share. Implicit knowledge = knowledge that is understood without being openly expressed but can potentially be articulated. Explicit knowledge = clearly articulated, documented, and easily communicated information. 3 DATA COLLECTION ON TACIT KNOWLEDGE IN THE MANUFACTURING SECTOR To explore how tacit knowledge is transferred in manufacturing, data was collected using a multi-method qualitative approach. The aim was also to understand how companies perceive the value of tacit knowledge and their interest in developing ways to manage it. Initial data was gathered during the Machinery Fair 2024 (Konepajamessut) in Finland with structured interviews. This earlier data, already presented in a previous phase of the project (Suhonen, 2024), served as a foundation for understanding practices and attitudes. To enrich and deepen this understanding, additional data was later collected during the Subcontracting Fair 2024 (Alihankintamessut). Altogether the data now consists of 163 interviews during the fairs. The 163 interviewed companies represented diverse fields of expertise, primarily categorized into manufacturing activities (56%), equipment and materials sales, including imported machinery and supplies (28%), maintenance services (4%), automation (3%), engineering design (3%), inspections (2%), and others (4%). Thus, the responses predominantly reflect the perspectives of Finnish manufacturing industries and the closely related sales and support of machinery and materials, as these combined categories constitute 84% of the total responses. The size of the responding company may influence their practices and perceptions regarding tacit knowledge transfer. Typically, larger companies have more structured training processes and resources allocated explicitly for knowledge management, while smaller companies often rely on informal communication and ad-hoc approaches. However, the sizes of the companies responding to this study were not investigated. In parallel, the project team conducted on-site company visits, during which interviews were held with various stakeholders, including production managers, trainers, and experienced technicians. These visits allowed for a more contextualized and nuanced understanding of how tacit knowledge is transmitted, particularly in relation to onboarding processes, mentoring models, informal learning environments, and risk factors associated with the aging workforce. The interviews were typically semi-structured, enabling both focused inquiry and flexibility to explore companyspecific practices. At this phase, 13 companies were visited and typically 1-3 company representatives were interviewed. In addition to this data collection by interviews, a co-creation workshop was organized, bringing together representatives from both the industrial and educational sectors. This workshop enabled the collaborative examination and dialogue of tacit knowledge practices, barriers, and enablers from multiple viewpoints. Participants worked together to define practical methods for identifying, documenting, and teaching tacit knowledge. Figure 2 shows outputs from participants placed in the four quadrants of the SECI model. Fig. 2. Company representatives’ inputs mapped onto the SECI framework during a cocreation workshop. 4 RESULTS Interviews conducted with manufacturing companies revealed a widespread concern about the loss of tacit knowledge, particularly in the context of an aging workforce. Tacit knowledge. Figure 3A presents the distribution of responses to the question “How serious a problem do you consider the loss of tacit knowledge in your company?” using a scale from 0 to 5 (0 = no problem at all, 5 = very serious problem). In addition, the figure includes information on whether the company has a method for transferring tacit knowledge from one employee to another, and whether the company is interested in participating in the development and training of tacit knowledge transfer together with TAMK. Figure 3B summarizes the responses and explains the interpretation of the colors: • Dark green  = The company has a method for tacit knowledge transfer and is interested in participating in its development with TAMK and SASKY. • Light green  = The company does not have a method for tacit knowledge transfer but is interested in participating in its development with TAMK. • Grey  = The company has a method for tacit knowledge transfer but is not interested in participating in its development with TAMK and SASKY. • Red  = The company does not have a method for tacit knowledge transfer and is not interested in participating in its development with TAMK and SASKY. Based on the distribution of responses (Figure 3A), the majority of companies consider the loss of tacit knowledge to be at least some level of problem for their organization. Of the 163 companies responding, 75% (122 companies) reported having some kind of training model or practice for transferring tacit knowledge from one employee to another. Of these, about half (41 companies) also expressed a willingness to participate in the development and training of tacit knowledge collection and transfer together with TAMK. In addition, 13 companies that currently do not have any existing model for tacit knowledge transfer stated they would like to be involved in such development. The largest group (81 companies) consists of those who have an internal model for tacit knowledge transfer but see no need to further develop it or are not willing to share their expertise. Among the respondents, there are also 28 companies without a model and without interest in developing one. Some of these companies also perceive the loss of tacit knowledge as a problem (see Figure 3A). The reluctance of these companies to develop a model for tacit knowledge transfer may stem from various reasons. Lack of resources such as time, funding, or personnel. Or the importance of tacit knowledge may not be fully recognized. In smaller organizations, knowledge sharing often takes place informally through daily interactions, which may diminish the perceived need for a formal model. Also, other priorities such as growth or product development may take precedence over knowledge management. Fig. 3. A) Company responses regarding the perceived severity of the loss of tacit knowledge (A), as well as information on whether the company has a method for transferring tacit knowledge and whether it is interested in developing and training tacit knowledge transfer in collaboration with TAMK (B). The response color coding is the same in A) and B). According to the company visit interviews, tacit knowledge transfer is considered important across companies. In every company, some form of tacit knowledge is transferred, although the level of systematization varies. The retirement of experienced employees and employee turnover pose particular challenges to the preservation of this knowledge. Tacit knowledge is most often transferred through on-the-job guidance. Practical instruction and working side by side were perceived as effective methods. In the companies interviewed, onboarding typically begins with simple tasks and gradually advances to more complex stages. The duration of the onboarding process varies from 1 to 9 months, depending on the prior experience of the employee. Documentation and written records were highlighted as important parts of the onboarding process. In some companies, tacit knowledge transfer is also supported by rotating employees through different tasks and machines and by creating clear work instructions. The 13 on-site interviews also emphasized that the master–apprentice model is one of the most effective ways to transfer tacit knowledge. Learning by doing and engaging in practical tasks not only develop technical skills but also foster a comprehensive understanding of processes. However, this model also presents challenges, particularly in terms of costs and resource use. Assigning two professionals to the same task is expensive and time-consuming. Some companies have addressed this by utilizing part-time retirement arrangements. Another challenge relates to the “ownership” of knowledge: not everyone is willing to share their expertise, preferring instead to retain knowledge as a personal asset. In addition, the master and apprentice must get along and “speak the same language” for the learning process to be effective. A good mentor is able to demonstrate, encourage, and provide constructive feedback. Pedagogical skills, such as clear communication and a supportive attitude, are especially important when transferring experience-based knowledge that is difficult to verbalize. Although digital tools such as AR and VR have theoretical potential, the data revealed limited practical implementation among the interviewed companies. Barriers may include costs, lack of expertise to manage and maintain technological solutions, and perceptions that digital simulations do not fully replicate the complexity and subtlety of real-world tacit knowledge. As part of its outputs, the Manufacturing Academy 2.0 project is developing a VR simulator specifically for grinding process in manufacturing. However, the description and evaluation of this simulator are beyond the scope of this article. Companies generally recognize that systematic tacit knowledge transfer still requires further development in order to become an established part of everyday organizational routines. The retirement of experienced employees represents a significant risk for knowledge loss. This highlights the need for effective tools and processes to preserve and transfer tacit knowledge to future generations. 5 DISCUSSION The findings of the Manufacturing Academy 2.0 project provide understanding of how tacit knowledge is perceived, transferred, and managed in Finnish manufacturing companies. When interpreted through the SECI, the empirical results reflect the four phases of knowledge conversion: The socialization phase: The transfer of tacit knowledge through shared experiences is a well-established practice in many companies. Hands-on mentoring, side-by-side learning, and informal peer interaction were consistently seen as effective means of transferring knowledge. However, this phase also carries risks: without structured guidance, the master–apprentice model can inadvertently transfer flawed or outdated practices. In this regard, one clear area for development is the introduction of a “mentor” who would not only facilitate and support the master– apprentice relationship but also help validate the knowledge being transferred to ensure it aligns with current best practices and safety standards. The externalization phase: This phase where tacit knowledge is articulated and made explicit, remains relatively weak. While some companies use documentation, visual instructions, and technical illustrations, the process is often unsystematic. Knowledge is frequently captured only partially, and without contextual explanations, much of its value is lost. In addition, not all employees are always willing to share what they know. In certain cases, individuals view their expertise as a source of job security and may withhold information, especially in situations where layoffs or restructuring are anticipated. The combination phase: The integration and organization of explicit knowledge was only lightly reflected in the data. Some companies reported using documentation and written instructions as part of their onboarding processes, and in a few cases, employees were rotated across tasks and machines to support broader learning. However, the extent to which explicit knowledge is systematically organized or combined into cohesive training content remained unclear, suggesting that this phase is not yet strongly developed in current practices. The internalization phase, where explicit knowledge becomes tacit again through experience, is actively supported by many companies through task progression and increasing responsibility. The master–apprentice model plays a central role here, but its success depends somewhat on the mentor’s pedagogical skills. Retiring workers often need to communicate with much younger employees, whose learning styles and backgrounds may differ significantly. Effective knowledge transfer in this context requires the master to "speak the same language" as the apprentice, adjusting explanations and feedback to suit the learner’s needs. 6 CONCLUSIONS Based on the qualitative data collected from company interviews, on-site visits, and a multi-stakeholder workshop, the study tells that while tacit knowledge is broadly acknowledged as important, systematic strategies for its transfer are still lacking in many organizations. When analyzed through the SECI model, the results show that socialization and internalization are relatively strong, primarily supported by master– apprentice models and on-the-job learning. However, the externalization and combination phases require further development in many cases. Many companies lack structured processes for documenting experiential knowledge, and fragmented materials often prevent effective onboarding or scaling of expertise. One key risk is that the master–apprentice model, while effective, can also inadvertently transmit incorrect or outdated practices if not monitored or validated. To mitigate this risk, organizations could implement structured mentorship programs that include pedagogical training for mentors and mechanisms for validating and updating the transferred knowledge. Additionally, creating an open and supportive organizational culture, where knowledge sharing is encouraged and rewarded, is crucial for ensuring the quality and continuity of tacit knowledge transfer across generations. Looking ahead, future work should focus on developing digital and pedagogical tools that enhance the visibility and usability of tacit knowledge. Expanding cooperation between educational institutions and companies would be beneficial for ensuring that practical expertise is not only systemically preserved but also continuously developed in the companies. 7 ACKNOWLEDGEMENTS The European Social Fund plus (ESF+) is acknowledged for cofounding the “Manufacturing Academy 2.0” project.