The concept of tacit knowledge which can be simply put as the knowledge that cannot easily be articulated into words was first presented by Polanyi when he stated, “we know more than we can tell” (Polanyi, 2001). If a metaphor of an iceberg is used for a knowledge possessed by an individual, then the tip of the iceberg can be represented as the individual explicit knowledge and the remaining invisible part can be represented as the individual’s tacit knowledge. In recent years organizations have started to realize the significance of this type of knowledge and consider its management of strategic importance.
This post reflects on the paper by Ribeiro, (2013) on tacit knowledge management, where he investigated the utility of TK management in a pre-operational large industrial plant in Brazil. Consequently, a conceptual framework for tacit knowledge management is presented in the paper to support the pre-operational training and hiring for that plant. Some interesting observation about the paper are as follows:
- The debate about what constitutes knowledge and its nature is an old one. It was Plato who described knowledge as “justified true belief” and Ribeiro, (2013) stands with the position of knowledge being the property of a social group which constitutes the ‘form of life’ (Wittgenstein, 1976). Through this approach the essence of tacit knowledge by Ribeiro, (2013) is to fully participate in a form of life. He relates this to the collective tacit knowledge defined by Collins, (2007) and suggests acting more smoothly and to improvise in a technical culture when applying instructions and standards.
These remarks are aligned with framework presented by European Union for vocational education and training where they state that “tacit knowing view understands knowledge as experience and emphasises that knowledge is mainly practical (know-how, skills), implicit, personal and situational. Learning means making practical experience (learning by doing) and is seen as a social process that happens through socialisation in communities of practice” (Cedefop, 2017).
- The paper distinguishes the approaches followed by organizations to treat tacit/explicit knowledge/knowing into two categories, the so-called “prescriptive approach” and “practice-based approach”. The prior approach he claims emphasizes writing down standards and methods based on best practices and their proper management and reinforcements. The later however emphasizes learning through participation within communities of practice. It aims to enhance their worker’s experience and abilities to anticipate problems and deal with everyday variability more efficiently. Consequently, tacit knowledge management is defined as “managing who is going to work with whom, doing what and for how long” in the paper.
The proposed characterization of organizations’ approach towards tacit/explicit knowledge management and defining tacit knowledge management as managing questions like who, what and how put into perspective the goals of tacit knowledge management into the practice. This also gives flexibility to different organizations to decide on these parameters for themselves and formulate their own plans for managing tacit knowledge within their own organizations. For example, in the context of systems integration in the Railways industry it is more interesting to manage tacit knowledge related to functional and operational aspects of the system. In such contexts tacit knowledge needs to be classified and managed in accordance with the functional and operational error assessments techniques followed by the organization.
- It is suggested in the paper to classify experience of the experienced workers in an organization per levels of similarity. He classified their experience they had undergone in their professional lives into low, medium and high levels of similarity. This classification based on classifying their experience, previous form of life, with the current required form of life. Ribeiro, (2013) defined medium similarity for individual who had experience with working with similar equipment but with a different process like for example having experience with similar equipment with a kiln in cement plan instead of required experience in nickel plant. Consequently, the proposed unit for estimating ‘stock’ of tacit knowledge among the workforce with the total time of working experience per levels of similarity.
The proposed tacit knowledge classification and measurement method have its bases in the experience of individuals. This is aligned with the findings of Bratianu and Orzea, (2010) who regard experience as the primary source of tacit knowledge. In the context of systems integration tacit knowledge related to the environmental and human factors, which determine the human error, is more relevant. This highlights the need for constructing an adequate model for managing tacit knowledge within an organization to enhance human reliability. Cognitive models reviewed by Pan et al., (2017) for Human Reliability Analysis (HRA) are a good starting point to understand the tacit knowledge required for enhancing human reliability in an organization. Summing up, the paper presents a reasonable framework for tacit knowledge management in the pre-operational phase of a large industrial plant. Similar challenges exist in the Railways industry specifically in the pre-operational phase of train introduction. Therefore, lessons can be learnt, and insightful knowledge can be acquired from the paper for the development of tacit knowledge management framework within the Railways industry.
Bratianu, C., Orzea, I., 2010. Tacit Knowledge Sharing in Organizational Knowledge Dynamics.
Cedefop, 2017. The changing nature and role of vocational education and training in Europe. Volume 1: conceptions of vocational education and training: an analytical framework. Luxembourg: Publications Office. https://doi.org/http://dx.doi.org/10.2801/532605
Collins, H., 2007. Bicycling on the moon: Collective tacit knowledge and somatic-limit tacit knowledge. Organ. Stud. 28, 257–262. https://doi.org/10.1177/0170840606073759
Pan, X., Lin, Y., He, C., 2017. A Review of Cognitive Models in Human Reliability Analysis. Qual. Reliab. Eng. Int. 33, 1299–1316. https://doi.org/10.1002/qre.2111
Ribeiro, R., 2013. Tacit knowledge management. Phenomenol. Cogn. Sci. 12, 337–366. https://doi.org/10.1007/s11097-011-9251-x