Tacit knowledge is non-codifiable, and its acquisition and transfer require hands-on practice.

Knowledge Capture and Codification

According to Gandhi (2004), knowledge capture “involves the key inputs and outputs of knowledge. Key inputs may include specific data and information, verbal or written communications, and other shared explicit and tacit knowledge such as best practices. Key outputs may be [in the form of] internal documents, reports, research papers, procedures, internal benchmarks, and best practices” (p. 373). Knowledge capture is important for the success and development of a knowledge-based organization. Much of the knowledge in an organization resides in the heads of the people, and if it is not captured and stored, it is more likely to be lost when an employee leaves the organization. Therefore it is essential to identify the expertise and the skills of staff and capture it to avoid a collective loss of organizational memory.

Libraries need to develop systems to identify people’s expertise so that it may be captured, shared, and reused in the future. Formal processes of capturing knowledge include collating internal profiles of librarians and also standardizing routine information-update reports. Additionally, libraries can capture the most commonly received enquiries at the reference desk and place them within easy reach to better serve users in the shortest time possible. It is important to create databases of frequently asked questions to enable librarians to not only provide an in-depth customized reference service but also to become knowledgeable about handling different enquiries (Maponya, 2004).

Since tacit knowledge is intuitive and practice-based, it cannot easily be passed on to others. To make the best use of tacit knowledge, it must be codified into an explicit form. Once tacit knowledge is codified and converted to explicit knowledge, it may easily be stored, organized, combined, accessed, shared, and manipulated in different contexts. The codification of knowledge provides several benefits to libraries:

Codification enables libraries to secure knowledge. A library is in less danger of losing its intellectual assets, even when its employees retire or leave the organization.

Codification enables fast access and retrieval of knowledge.

Codification facilitates sharing, reuse, reflection, and ongoing learning.

The processes of codification and representation of knowledge for access and reuse are not new to Library & Information Science (LIS) professionals, as they are involved in many stages of the knowledge processing cycle. Gandhi (2004) outlined the following steps in the codification and representation of knowledge:

Identifying, acquiring, or extracting valuable knowledge from documents, discussions, or interviews, usually accomplished with the help of subject matter experts.

Refining, writing up, and editing “raw knowledge” (such as project files, presentations, e-mail messages), and turning it into “processed knowledge” (such as lessons learned, best practices, case studies).

Organizing the processed knowledge and making it accessible by adding index terms, subject headings, cross-reference links, and metadata.

Packaging, publishing, and disseminating knowledge through a variety of channels, including intranet web pages, CD-ROMs, subject-oriented pathfinders, and “knowledge portals” that are focused on particular business needs or issues.

Designing and managing the overall information architecture consisting of a set of well-defined standards and schemes for organizing, classifying, publishing, and navigating the organization's intellectual content.

From tacit to explicit

Personalised tacit knowledge can be obviously disseminated into a written document via the ‘Externalisation’ form. Therefore, externalisation involves writing. An example of this form is a business procedure explained from the experience of a practitioner. Externalisation is not an easy process. Its challenge is in how a knowledge owner can effectively convey their possessed knowledge into a written document. Some individuals disregard their knowledge and leave knowledge articulation to others, while some realise the skill, craft and experience they own but cannot make them into visible forms.

In technological terms, externalisation can play its role via online social network tools. Experts can share their knowledge in general or specific network groups. The groups can range from an organisational shared space to a worldwide network area. Moreover, an organisation can maintain knowledge lost from employees’ resignation by a recording of their knowledge in the organisation’s knowledge base, from which existing staffs can learn later.

Publisher Summary

Understanding what tacit knowledge is, and particularly how the concept is used, is important for philosophers of technology because it is now a central concept in policy discussions related to engineering. It is used to explain why knowledge production is localized, cumulative and path-dependent, and therefore why designers, design teams, firms and regions differ in their technological performance. Given the impact of public policy related to the “knowledge economy,” there is a legitimate role for philosophers of technology to investigate the foundations of these ideas in more detail. This is particularly important because the terminology of tacit knowledge is applied very widely, but is rarely explicitly explained. Just what tacit knowledge is, and how it is valuable during the development of technology, is often itself a “tacit” concept. This chapter defines engineering as the art of organizing and negotiating the design, production, operation and decommissioning of artefacts, devices, systems and processes that fulfill useful functions by transforming the world to solve recognized problems. This hopefully highlights the practical, creative nature of engineering, with a clear connection to judgments and choices about solutions that achieve a balance between potentially conflicting outcomes in terms of their aesthetic, economic, environmental, technical and other criteria.

The term tacit knowledge was first brought into the social scientist's lexicon by the philosopher Michael Polanyi. Polanyi, who wrote extensively on the role of consciousness in creativity and in the process of doing science, used the term in a manner that extended its standard, nontechnical connotations. Rather than simply having it refer to knowledge that is implied, Polanyi used it to refer to knowledge that was personal, private, and, importantly, knowledge that was not necessarily available for conscious introspection. This last meaning is the one that has had dramatic impact in contemporary psychology—although in many writings tacit has been replaced by the synonymous term implicit. However, no matter which term is used, the notion has become of considerable importance since it is now understood that a good deal of knowledge, as Polanyi suggested, is acquired and held largely independent of awareness. Moreover, the underlying neurological mechanisms that are responsible for acquisition and retention of implicit or tacit knowledge appear to be remarkably robust and to function virtually normally in individuals with several psychological and neurological disorders than compromise conscious, top-down processes.

Knowledge suppliers and users

Prusak’s definition presented in the previous section implies the existence of suppliers of knowledge (‘individuals’) and users of knowledge (‘others’), people in whose minds the knowledge is buried and people and teams who need access to that knowledge.

Knowledge is created through experience and through the reflection on experience in order to derive guidelines, rules, theories, heuristics and doctrines. Knowledge may be created by individuals, through reflecting on their own experience, or it may be created by teams reflecting on team experience. It may also be created by experts or communities of practice reflecting on the experience of many individuals and teams across an organisation. The individuals, teams and communities who do this reflecting can be considered as ‘knowledge suppliers’.

In business activity, knowledge is applied by individuals and teams. They can apply their own personal knowledge and experience, or they can look elsewhere for knowledge – to learn before they start, by seeking the knowledge of others. The more knowledgeable they are at the start of the activity or project, the more likely they are to avoid mistakes, repeat good practice, and avoid risk. These people are ‘knowledge users’.

We have introduced the idea of tacit knowledge and explicit knowledge. The knowledge can be transferred from the supplier to the user tacitly, through dialogue, or explicitly, through codifying the knowledge. Figure 1.2 shows these two approaches by looking at the two places where knowledge can be stored: in people’s heads or in codified form in some sort of ‘knowledge bank’ (Figure 1.2 is a redrafting of the SECI model of Nonaka and Takeuchi). These two stores can be connected in four ways:

direct transfer of knowledge from person to person (communication);

transfer of knowledge from people to the ‘knowledge bank’ (knowledge capture);

organisation of knowledge within the knowledge bank (organisation);

transfer of knowledge from the ‘knowledge bank’ back to people (access and retrieval).

Knowledge can therefore flow from supplier to user (from person to person, or team to team) in two ways.

The most direct (the upper left arrow on Figure 1.2) is through direct communication and dialogue. Face-to-face dialogue, or dialogue via an online communication system, is an extremely effective means of knowledge transfer. This method allows vast amounts of detailed knowledge to be transferred, and the context for that knowledge to be explored. It allows direct coaching, observation and demonstration. However, it is very localised. The transfer takes place in one place at a time, involving only the people in the conversation. For all its effectiveness as a transfer method, it is not efficient. For direct communication and dialogue to be the only knowledge transfer mechanism within an organisation would require a high level of travel and discussion, and may only be practical in a small team working from a single office where travelling is not an issue (for example a regional sales team that meets on a regular basis). This may be the only practical approach to the transfer of uncodifiable knowledge – that knowledge that cannot be written down (which Polyani would call ‘tacit’). However, it should not be the only mechanism of knowledge transfer, nor should knowledge be stored only as tacit knowledge in people’s heads. Using people’s memories as the primary place for storing knowledge is a very risky strategy. Memories are unreliable, people forget, misremember or post-rationalise. People leave the company, retire or join the competition. For example, what is the staff turnover in your team? Your division? Your company? How much knowledge is leaving your organisation in the heads of the departing people? There needs to be a more secure storage mechanism for crucial knowledge and a more efficient means of transfer than just dialogue.

The less direct flow of knowledge (the larger, lower right arrow on Figure 1.2) is through codification and capture of the knowledge, storage in some sort of ‘knowledge bank’ and retrieval of the knowledge when needed. The transfer is lower bandwidth than direct communication, as it is difficult to write down more than a fragment of what you know. No dialogue is possible and demonstrations are restricted to recorded demonstrations, e.g. using video files. Transfer of knowledge by this means is not very effective. However, the knowledge need only be captured once to be accessed and reused hundreds of times, so it is an efficient method of transferring knowledge widely. The knowledge is secure against memory loss or loss of personnel. This approach is ideal for codifiable knowledge with a wide user base. For example, the widespread transfer of basic cooking knowledge is best done through publishing cookery books. It is also ideal for knowledge that is used intermittently, such as knowledge of office moves or knowledge of major acquisitions. These events may not happen again for a few years, by which time the individuals involved will have forgotten the details of what happened, if it is not captured and stored.

These two approaches to knowledge transfer are sometimes called the connect approach (the smaller arrow), where knowledge is transferred by connecting people, and the collect approach (the larger arrow), where knowledge is transferred by collecting, storing, organising and retrieving it. Each method has advantages and disadvantages, as summarised in Table 1.1. Effective knowledge management strategies need to address both of these methods of knowledge transfer. Each has its place; each complements the other.

Table 1.1. The connect and collect approaches to knowledge transfer

5.1 Quine's Challenge

Quine challenges Chomsky's introduction of the notion of tacit knowledge by making use of the distinction between behavior that conforms to a rule and behavior that is guided by a rule. A subject can behave in a way that conforms to a rule without using the rule to guide his behavior for, as Quine (1972) uses the notion of guidance: ‘(T)he behavior is not guided by the rule unless the behaver knows the rule and can state it.’ Guidance requires explicit knowledge.

Chomsky's tacit knowledge is supposed to require less than explicit knowledge; but it cannot be equated with mere conformity. In fact, conformity to rules is neither necessary nor sufficient for tacit knowledge of those rules. It is not necessary, since the presence of tacit knowledge of rules does not guarantee perfect deployment of that knowledge in actual performance. It is not sufficient, since a tacit knowledge claim is not offered as a summary description of behavior but as a putative explanation of behavior. There will always be alternative sets of rules that require just the same behavior for conformity; but it is part of the idea of tacit knowledge that a speaker's actual behavior might be correctly explained in terms of tacit knowledge of one set of rules rather than the alternatives.

It is at this point that Quine (1972) poses his challenge. He insists that, if an attribution of tacit knowledge is an empirical claim that goes beyond a summary of conforming behavior, then it should be possible to indicate what kinds of evidence would count in favor of or against that empirical claim. He also insists that this evidence should involve the subject's behavior. To this latter point, it is reasonable to reply that there can be no a priori limit on the kinds of evidence that might be relevant to an empirical claim. So it is not legitimate to restrict evidence to the behavior of the very subject to whom the attribution of tacit knowledge is being made. But the more general point about evidence is a fair one.

2.1 Knowledge and Scientific Research

Mean for giving structure to tacit knowledge

In the context of an organisation, tacit knowledge should become explicit and objectivised. It is worth mentioning that representation tools should not be intended only as instruments to give shape to the final knowledge representation, i.e. the output of the externalisation process. They also have a constructive role within the process of externalisation where they may assume an actual maieutic value: when the nature of a representation language (determined by its internal constraints) is well tuned with the knowledge to be represented, then identifying and connecting concepts, making abstractions and reasoning are all facilitated and enhanced.

A way to ask questions and give answers

The primary way for community members to access the tacit knowledge of the organisation is through asking questions. Any community member facing a problem where they lack complete knowledge should have a means of asking the community for help and of receiving answers. In a co-located community, this can be done in regular face-to-face meetings. Communities of practice in dispersed or multinational businesses cannot meet regularly face to face. They need some virtual means of raising questions and receiving answers.

There are many web-based or e-mail-based discussion tools or question and answer forum tools that allow just this facility, and these are proven and popular tools for sharing knowledge within communities. Buckman Laboratories, for example, operate several global communities of practice, each with its own online Q&A forum, so that customer-facing sales agents anywhere in the world can access lessons from their peers by sending an e-mail asking for lessons and advice. An e-mail will be forwarded to all members of the community and anybody who can share their learning will reply. Replies are collated as a ‘threaded discussion’ on a community forum and community members can read this discussion and their own comments and learn themselves. Social networking software such as Facebook, Twitter, Yammer and SalesForce Chatter also allows community members to ask each other for help and advice.

This sort of online interaction has historically worked better for marketing than for sales, as marketers are more likely to be sitting behind a desk and in front of a screen. However, the increase in power and connectivity of handheld tools and smartphones now means that sales people can join in the online conversation from anywhere they happen to be. This is discussed further in Chapter 6.

Drawing relationships

Humans as creative animals bear a predilection to transform tacit knowledge into explicit knowledge through some means of, what has been termed, ‘graphic act’ (Gibson, 1979: 275–6). Researchers in the practices of drawing have commented how artists create a ‘thinking-space’ through their activities and imaginations, in which remote phenomena are brought to a state of presence (Garner, 2007: 110). Graphs represent the spatial arrangement of things, including their temporal dimension. Both in creativity and in logic, we draw these relationships using lines. Drawing makes use of traces of a hand’s movement over a page, and threads interweave lines to form a surface (Ingold, 2007: 60). Line-making also serves to transmit tacit knowledge and to establish a commonly held explicit knowledge, or a ‘professional vision’, in just about every area of practice.

Relating these kinds of activation through line-making to social space, the sociologist John Urry (2004) has outlined current descriptions of social arrangements as networks of people, places, materials and mobilities, and has observed how current web technologies represent the rapidity of spatial change in social landscapes. These social networks are valued by their ‘connectedness’ or ‘degrees of separation’ that reflect not physical proximity between one person and another, but a kind of symbolic proximity of, for example, ‘friendliness’ or ‘strangeness’. Hence a graph of a social network represents an authored and configured drawing of the people and artefacts that constitute and demarcate its specific social domain.

The edges of a graph are lines that represent connections among nodes such as, for example, the social, spatial or semantic relationships of a community. Graphs allow modellers to reason about these kinds of relationships in a way that is intuitively readable and computationally tractable (Chein et al., 2013). Graphs also allow any kind of agent or entity, and any of their possible relationships, to be handled conceptually. This means that even those properties of a relationship that are ‘passive’ in the real world (such as the fact of someone’s existence) can be rendered as an active component of the graph representation (Sowa, 2009).

Basic graphs represent the network entities and the characteristics of their relationships. More complex graphs also represent multiple layers of these relationships, including those that exist by inference of connections elsewhere in the network. Hence a graph can help to visualize aspects of community relationships that are not immediately apparent. For example, people’s identities can be strongly attached to where they are from and, in places of wide inequalities, they can become isolated in specific areas. Double-edged ‘socio-spatial’ inequalities cannot be seen easily by the broader urban community, leading to a limitation in the range of citizens’ sensitivities to these kinds of inequalities. Indicators of inequalities that are highly salient relate to visible urban-fabric or socio-cultural distinctions (cf. Chokor, 1991; Viega, 2012). Less salient, however, are information-based indicators such as social connectedness and access to economic opportunities (cf. United Nations, 2013: 77; Morsey, 2012).

The current availability of graph technologies, including web-based platforms, has brought about among web media participants a near-simultaneous engagement in building and maintaining these social networks. This social technology ubiquity is perhaps telling of a current step-change in media agility. People can draw or, rather, thread their social relationships using web-media platforms, embroidering elaborate identities with texts, artefacts, nodes and connectors, woven into the surfaces of media, communications and gaming platforms. Socio-spatial identities also are materialized in web-mapping, geographic information and positioning systems. Participation in digital media depends increasingly on touch-sensitive interfaces, serving to restage the gestural line as a means of digital threading. The embroidering of identifications forms as enmeshed surfaces of social domains. These surfaces are distorted and disrupted by certain attractors, they go through periods of instability and transition; they decay, only to regenerate. If social relationships can be viewed as having physics-like properties (as we discussed in Chapter 3), so this graphic interweaving of attractions, transitions and decays is perhaps suggestive of a ‘social physics’ of relativity.