How can knowledge be effectively acquired, developed and used to benefit organizational performance?
Key Theories Types of knowledge and learning Knowledge-based theory Transfer of knowledge and absorptive capacity Organizational knowledge creation theory Organizational memory
Key HR Practices Formal learning Informal and workplace learning Knowledge transfer and creation Knowledge storage and retrieval
A big data revolution has entered every aspect of our lives, including Human Resource Management. The amount of information available from the Web, social media, from data generated from software and hardware, from cellphones and tablets, and from financial transactions is increasing exponentially each year. Managers wonder about how this abundance of information can be used to benefit organizations. How can we make sense of all this information and use it for decision-making? How can it contribute to innovative products and services? And how can all the information support the human capital of an organization? To transform information into a valuable resource that can be used for decision-making and innovations, it has to be processed and become ‘knowledge’. Unlike information, knowledge can be used to actually do things, for example, selecting the relevant information to use in strategic decision-making. Put simply, a dataset with personnel records in itself does not tell you how human capital can be improved. Only someone with the knowledge to ask the right questions for guiding data analytics will come up with a synthesis of the data that can effectively support decision-making.
Knowledge is thus a valuable asset for organizations. Organizations increasingly demand employees who know how to create, share and use knowledge in order to operate their complex technology and organizational processes. Organizations with a better educated, more experienced workforce outperform their competitors, in particular when the knowledge that is acquired and developed is specific to that organization. Since organization-specific knowledge is hard to imitate and transfer, resource-based theories predict that knowledge management can provide a unique source of sustainable competitive advantage for organizations.
Organizations stimulate knowledge development in several ways such as by investing in training and development. Worldwide training and development expenditures by organizations are estimated around 360 billion dollars a year (Bureau for Training Industry Research, 2017). Training expenditures pay off for organizations: expected returns enable better productivity, more innovation, less employee turnover and better recruitment prospects (Aguinis & Kraiger, 2009).
However, training is not the only HR practice that can support the knowledge base of organizations. Other examples are knowledge acquisition by performing tasks and mentoring or knowledge creation during projects and teamwork. This chapter delves into the core theories on knowledge acquisition, the creation of new knowledge, and the storage, retrieval and use of knowledge. To aid in the overview of theories and their applications in management, a distinction is made between knowledge at the individual level and knowledge at the organizational level. The distinction between individual and organizational knowledge helps to understand the key theories in this field.
Theory
To structure the vast amount of literature on knowledge in organizations, the text in this chapter is divided into two parts. First, knowledge and knowledge acquisition will be explained from the perspective of individual employees. The core theoretical discipline to understand learning is pedagogical science.
Thereafter, where knowledge in individuals is relatively straightforward and linked to the memory and information processing capacity of the brain, knowledge in organizations exists because it is stored in the memories of those who work in the organization, in individuals who make up the networks in which knowledge is shared. The chapter continues with organization-level theoretical perspectives on knowledge as a resource for organization performance, knowledge transfer, knowledge creation and innovation, and knowledge storage and retrieval. Many of these theories are grounded in (organizational) sociology.
Individual level knowledge
How individuals develop knowledge through learning is the core question of pedagogical science. Pedagogy is traditionally associated with learning in school systems, but found its application to adult education and human resource management. Pedagogical science provides theories on organizing learning and education, which helps to understand how individuals acquire knowledge, how they learn and what instructors (and managers at work) can do so that optimal conditions for learning are created (Bartlett & Burton, 2016). The outcome of learning is knowledge.
What is knowledge?
Although it seems easy to talk about knowledge, it is quite a challenge to find a good definition in the literature. The question of what knowledge is, has occupied generations of philosophers from Plato to Popper. Scientists in the domain of knowledge sometimes even refrain from defining it at all (Grant, 1996). Others have suggested the following definition of knowledge:
Knowledge is defined as a ‘justified true belief’ that enables individuals and organizations to do the things they do and that varies between explicit knowledge and tacit knowledge (Nonaka & Krogh, 2009).
Three elements make up this definition: The first element is that knowledge is a ‘justified true belief’. Let’s have a closer look at these three words to try and grasp what they mean. To start with the last one: ‘belief’, is quite straightforward. Beliefs can differ from one person to the next – you can believe anything you like from fairytales to life on Mars - but this is not knowledge. Some believe in global warming while others believe it does not exist. Hence, beliefs are not true until they can be checked (justified) with facts about the universe around us. Some beliefs are easily checked: “I believe it is cold outside” can easily be justified by going outside and feeling the temperature, or by checking the weather report. In this example, interaction with the environment helps to determine whether a belief can be justified as the truth. Once justified by checking, you know the temperature is low and that it is indeed cold outside. Your belief that it is cold became knowledge once you checked it with facts. This knowledge (“It’s cold outside”) enables you to act (e.g. put on a warm coat). More complex beliefs like “I believe in global warming” are not as easily checked as the outside temperature. Still, such beliefs can be justified as the truth if you find them consistent with and supported by other beliefs, like a belief in scientific reports that have checked longitudinal temperature patterns, or the belief that policy-makers know what they are talking about. This set of justified true beliefs constructs knowledge about global warming. However, a global warming cynic may use a different set of beliefs to justify the truth about the absence of global warming. Depending on your context and your own information bubble you use to check your beliefs, your knowledge can be very different from the knowledge of others. This implies that knowledge is not a sure thing, because it depends on beliefs and on the contexts against which the beliefs are checked for the truth.
This first element of Nonaka and Krogh (2009)’s much-used definition of knowledge is almost philosophical. Its practical use lies in the reflection that knowledge is different from beliefs, and also different from facts and information. When scholars talk about knowledge in relation to employees and organizations, they take the first philosophical part of the definition for granted and focus on the second part (knowledge as a source for all actions) and the third part (the different types of knowledge).
The second element of the definition points out that knowledge ‘enables organizations and individuals to act’. With the use of knowledge, individuals and organizations are able to define and solve a problem or task. Doing your job requires knowledge because this allows you to skillfully do your day-to-day routines at work and to deal with new challenges. All the ‘justified true beliefs’ that form the knowledge about how your work is done best guide you how to do your job as well as possible. If you are new at the job, you need to acquire such knowledge to be able to do the job at all.
This second part of the definition is very practical: it introduces the notion that knowledge acquisition (learning) and knowledge transfer (teaching) are required to enable you to do your job well. But how can knowledge be acquired and transferred? This leads us to the last element of Nonaka and Takeuchi’s definition.
The third element of the definition is that ‘knowledge exists along a continuum between tacit and explicit knowledge’. Explicit knowledge is easy to understand: it can be explained to others and is written down in books or on the internet. Tacit knowledge is much more implicit; it refers to knowledge we are not even aware of that we possess it and use it. Tacit knowledge explains the difference in performance between novice and experienced employees. Although both have the same diplomas and read the same books, experienced employees know better how to apply that knowledge to specific problems. Hence, experience largely comprises tacit knowledge. If you ask experienced people why they do what they do, they may not even be able to explain it exactly. This last element in the definition of knowledge, the distinction between tacit and explicit knowledge, is of significant importance to researchers and organizations (Alavi & Leidner, 2001). It raises important questions on knowledge acquisition, development and storage and retrieval. Let’s have a closer look at the theory behind tacit and explicit knowledge.
Explicit and tacit knowledge
The distinction between explicit and tacit knowledge was first proposed by the multi-talented physician, chemist, economist and social scientist Polanyi (1891–1976). Looking back at his experience in various research domains, he wondered why scientists put forward their hypotheses for their research as they do. Looking at how scientists draft their research, it appeared to him that the research proposals they wrote were not the sole result of clean analytic thinking that could be traced back only to hard observable facts. Instead, the researcher’s personal experience, the decade in which they work, the institutes in which they are employed and many other unspoken experiences interfered with the hypotheses that were tested in their research. Hence, Polanyi noted that the process of drafting a research project contains many implicit processes that involve knowledge that does not appear in manuals or journals and that scientists are not even aware they possess. He concluded in a philosophical mood that even research, with its emphasis on the logic of deduction being the high road to finding the truth, was subject to all kinds of implicit processes that in the end hinder even researchers in ‘knowing the truth’ (Nye, 2011).
Polanyi named the implicit knowledge that interferes with the knowledge that is communicated and reported as ‘tacit’. The idea behind tacit knowledge is that much of what we know cannot be put into words: “we can know more than we can tell” (Polyani, 1966). For example, we usually cannot tell how we recognize a familiar face in a crowd; we just know. However, if probed upon this tacit knowledge, we could say what information we process in recognizing the person. This shows two things: first, tacit knowledge is needed to efficiently take decisions and do the things we do. If not questioned, it remains unconscious. Second, when probed, tacit knowledge can be communicated and made explicit. These insights imply that knowledge is a continuum, ranging from explicit to tacit (Nonaka & Krogh, 2009).
Explicit (also often called codified) knowledge is knowledge that can easily be communicated to others. It can be consciously accessed and it can be expressed in words, numbers or sounds. For example, it can be formulated in sentences or visualized in drawings. Another, more practical, example of explicit knowledge sharing is lecturing. When you attend a lecture in which a professor explains a theory to a group of students, you are receiving explicit knowledge from the professor. Explicit knowledge is the type of knowledge we can share with others by telling them about it. Explicit knowledge can be further divided into knowledge about facts (know-what) and knowledge about principles, laws and theories (know-why). For example, a lecture about knowledge theory is about sharing ‘know-why’, explicit knowledge, by means of communication. Explicit knowledge in organizations can be recognized by looking at all the communication that takes place in the organization.
Tacit knowledge is (more) difficult to communicate to others and not consciously accessible because it is highly personalized, based on experience and rooted in emotions, values, procedures and/or routines. For example, imagine a lecturer who just started his/her career. None of the colleagues formally shared knowledge on how to start off a lecture effectively, but after a while the lecturer will become more experienced and ‘just knows how’ to start a lecture smoothly. This kind of knowledge is tacit because it is gained from experience, not communicated, implicit and difficult to share with others.
Tacit knowledge can be further divided into knowledge about skills - how to do things (know-how) and knowledge about others who know the things that you need (know-who). Experience combines both types of tacit knowledge: experienced employees ‘just know’ how to do things, and they also know who inside or outside the organization they need to get the resources and knowledge they need. Newcomers in organizations can bring experience in general, but lack the tacit knowledge about how things are done in the new organization and about who knows more about what they need to know. Tacit knowledge in organizations is more difficult to pin down than explicit knowledge because it is expressed in doing rather than in communication. This makes the sharing of tacit knowledge more difficult than the sharing of explicit knowledge, as the following example illustrates. Take as an example the tacit knowledge involved in driving a big truck. Imagine a situation in which an expert driver is probed to explain how she just managed to park her very big truck backwards into a narrow alley. Much of the driver’s behavior will be tacit: knowing how to steer the wheel just a slight bit to avoid the truck hitting the alley walls. However, when probed, she’ll be able to explain how she uses the mirrors, how she estimates the size of the truck in relation to the walls, and how touching the steering wheel corresponds with the amount of movement the truck makes. Sure, the precise details of the tacit knowledge will remain unspoken, but a rough indication of the procedures involved in backward truck parking can be communicated and become explicit knowledge.
This illustrates that although we can distinguish two types of knowledge (explicit and tacit), in reality knowledge is not either explicit or tacit. Rather, there is a continuum between tacit and explicit knowledge that represents a range of knowledge mixtures of relatively more tacit versus explicit and relatively more explicit versus tacit knowledge.
Acquiring individual knowledge
The knowledge that individuals possess that enables them to function effectively in their jobs has to be acquired first. Knowledge is acquired through learning. Most people associate learning with the period in life when they visited school and obtained a diploma. After finishing school, some may attend training courses or part-time educational programs to upgrade their knowledge and skills to support their work performance or to advance their careers. However, learning does not only happen in classroom settings. Incidental meetings with others may provide new insights, or working on a project with people from different units at work also contributes to the development of knowledge. Hence, learning involves the acquisition of both explicit and tacit knowledge and can happen in the most unexpected situations. In general, learning will occur whenever people feel the need to learn, when they are motivated to learn, and when they have the opportunity (Marsick & Watkins, 2001). Knowledge acquisition in organizations can take the form of three types: formal learning, informal learning and incidental learning.
Formal learning happens when individuals participate in training programs in order to achieve some pre-established learning goal, for example learning a language, or learning to use a new method. Formal learning often (but not always) happens in classrooms, led by an instructor who has a plan of what the participants should learn and how. Managers are willing to invest in formal learning initiatives because there is a clear link between learning objectives and organizational goals. The initiative for learning is often instigated by managers in organizations, as part of the organization’s strategy or as part of some organizational change program. Because it is planned, the learning experience can be adapted to the needs of organizations and its learners. Moreover, training design can significantly contribute to the experience of an effective learning event. The better the design of the training in that it applies theory-based learning principles such as involving participants in the design of the training, the trainer encourages participants to learn from errors in the classroom and activate participants during the training, the better the acquired knowledge will persist and be used (Aguinis & Kraiger, 2009).
In contrast, informal learning is usually intentional but not that highly structured. In informal learning, it is the learner who initiates the learning. An example of informal learning is an internship aimed at gaining practical experience that fits with an educational program. Other examples include coaching, networking with others, and mentoring. In informal learning, the learner takes the lead by actively searching for opportunities to acquire new knowledge. By relating the learning experience of the internship to the learner’s goals, the learner comes to understand what was learned.
Finally, incidental learning is entirely unplanned, does not typically occur in a classroom setting, and does not have a pre-established learning goal. It just happens, without the learner being really aware that the new knowledge was acquired. Such incidental learning happens unconsciously and is not directly recognized as something that was learned. It is often the by-product of engaging in something else such as experimenting to make something work or learning how to deal with others while interacting.
These three types of learning can be placed along the continuum of knowledge types (see Figure 3.1). Explicit knowledge is the type of knowledge that can be talked about in a classroom or that is written down in textbooks, so it is associated with formal learning. Incidental learning happens at the other end of the continuum: it leads to tacit knowledge without being directly recognized as new knowledge. Informal learning takes a middle position on the continuum of explicit and tacit knowledge. Although the learning may be intentional and have a clear learning goal, it is mixed with tacit and also incidental learning. Because informal learning is intentional learning, the learner may be better able to actively reflect on ‘what was learned’ in relation to why the learner engaged in informal learning, and hence make the acquired tacit knowledge more explicit than in the case of incidental learning.
Figure 1
Knowledge continuum and learning types
Training transfer
Attending a training course does not automatically ensure there will be a change in behavior at work. Transfer needs to happen in order to bring the knowledge acquired in the training into practice at work. This may not always happen automatically. Applying new knowledge invokes a process in the individual where the explicit knowledge gained during the training has to be integrated with the tacit processes at work. The trainee has to reflect consciously on what they normally do at work, and where the newly acquired knowledge fits in. This process, which starts with acquiring explicit knowledge and blending that knowledge with the tacit knowledge used on a daily basis, is called training transfer.
Positive transfer of training happens when employees take what was learned in a training with them back to work and start using it to do their jobs. In contrast, negative transfer means that employees went to a training, learned something, but find no opportunity or need to use the new knowledge in their work (Blume et al., 2010).
To make training investments worthwhile, training transfer should be properly facilitated. There are two ways to evaluate whether training transfer has occurred. First, it shows in generalizability. This means that trainees use the knowledge not only in the training, but find opportunities to apply their acquired knowledge in a whole range of different situations. Second, it shows in the maintenance of the new knowledge – the extent to which the changes caused by the training persist over time.
Knowledge at the organizational level
Knowledge is always on the agendas of both organizations and societies. For example in the nineties, the Organization for Economic Co-operation and Development (OECD) introduced the need to build ‘knowledge-based economies’ to increase the wealth of societies as a whole (OECD, 1996). Nowadays, knowledge and innovation take a prominent role in the business strategies of many organizations. Clearly, the concept of knowledge in this context does not only refer to individual learning, but also has meaning at the group level too. Looking into the research that explores knowledge in organizations, there has been a shift in theoretical perspectives. Instead of pedagogy, many of the theories on organization and country-level knowledge are grounded in sociology.
In the next part of the chapter, theories on knowledge as a resource for organizational performance, and theories on knowledge transfer, learning organizations and knowledge storage and retrieval will be explained.
Knowledge in individuals and organizations
Even in the definition of knowledge, there is an individual and a group level element: Knowledge is defined as a ‘justified true belief’ that enables individuals and organizations to do the things they do and that varies between explicit knowledge and tacit knowledge (Nonaka & Krogh, 2009). Organizational knowledge is the knowledge that individuals share with each other and that is understood as ‘common knowledge’. Explicit knowledge is easy to share because it is written down or explained. By definition, tacit knowledge is more difficult to share because individuals may not even know that they know it. Tacit knowledge usually involves a social component. For individuals to acquire tacit knowledge, they need to have social interaction with others. Therefore, although tacit knowledge is stored in the minds of individuals, it can be transferred to others and become common knowledge in a social group. These social dynamics involved in the use, transfer and creation of explicit and tacit knowledge are central in organization-level theory on knowledge.
Knowledge-based Theory
Knowledge-based theory puts knowledge to the fore and suggests that knowledge is the key leverage for organizational performance and success. This is because knowledge is the critical input needed to create products and deliver services. Without knowledge, nothing would happen in organizations. Since knowledge is so vital for organizations to realize their goals, knowledge-based theory advocates that knowledge should be considered as the primary source of value for organizations. So, knowledge-based theory is an organization-level theory about what drives production processes in organizations (knowledge) and how this contributes to organizational performance.
The theory was first introduced in 1996, when Robert Grant launched the idea that organizations are in fact no more than structures that enable individuals to use and share their knowledge. The concept structure as used in this definition is widely used in sociology. It means that groups of human beings interact and behave in a distinctive, stable way because that is ‘how it is done’ in those groups. A family is a social structure as is a school and an organization. Therefore, organizations as social structures are more or less stable environments in which people work together in a distinct way to reach a common goal. Grant’s idea rests on this sociological premise that organizations are social structures. These social structures determine how knowledge is leveraged.
According to Grant’s knowledge-based theory, the essence of knowledge is that it resides in individuals. However, no individual knows everything and each person has a unique set of specialized knowledge related to the job they perform. Moreover, every job requires a mixture of explicit and tacit knowledge to be able to perform it.
Thus, individuals in organizations each have their unique set of knowledge. Putting this knowledge to use is what enables individuals to perform their jobs. The role of organizations is to provide an environment (a social structure) that brings together the knowledge that resides in different individuals doing their individual jobs, in such a way that the goals of the organization can be reached (Grant, 1996). In an effective organization, the social structure is designed to enable individuals to work together on the common goal of the organization. If all individuals put their best knowledge to use to realize products and services, organizations will succeed in realizing their goals.
Two important questions follow from knowledge-based theory. First, what kind of organization designs facilitate the use of knowledge? And second, how can knowledge be used strategically, or, can knowledge be a resource for competitive advantage?
Organization design
The most important task for managers, according to the knowledge-based theory, is to ensure coordination between individuals in the organization so that their knowledge can be joined towards achieving a common goal. The integrated knowledge of many different individuals results in the process of producing goods and services. Managers can organize knowledge coordination by implementing organization designs that facilitate knowledge transfer.
The design question concerns the configuration of the organization (the visual representation of hierarchical levels, specialist units, or cross-functional projects, and jobs) and the organization of work (e.g. job autonomy, delegated responsibilities). Knowledge-based theory advocates organization structures that bring individuals together. Organizational configurations consisting of individuals working in teams, and with work organizations that allow individuals and teams to connect to others in the organization to ensure that the knowledge of individuals is integrated. In addition, cross-functional project teams are excellent structures that facilitate knowledge sharing. To stimulate individuals to use their knowledge, managers have to give freedom to employees by providing job autonomy so that they can learn through trial and error at work.
Knowledge as a resource
Knowledge-based theory also has implications for competitive advantage. Knowledge was already introduced in the chapter on Investing in People, as part of the human capital of an organization. Human capital comprises all the knowledge, skills, abilities and other characteristics stored in the people that work in an organization. This is because human capital meets the conditions of being a valuable resource that creates unique capabilities. This is because human capital is non-transparent (difficult to copy) and difficult to transfer (not possible to take outside the organization to use somewhere else). However, when you zoom in on knowledge alone, this logic becomes somewhat more complex.
The complexity of knowledge as a resource lies in its transferability. In contrast to human capital characteristics that are bound to individuals and cannot be transferred (like personality and intelligence and work experience), knowledge can be shared between individuals. If one individual shares knowledge with another, then two people have the same resource (knowledge). Knowledge can be endlessly shared until many have the same knowledge. It makes knowledge a resource that can be resold (shared) endlessly. So, in light of the conditions that make resources valuable assets to organizational performance (see chapter on investing in people and performance), knowledge does not automatically qualify.
To understand when knowledge can be a valuable resource, we need to again dive into the distinction between explicit and tacit knowledge. Many organizations have taken measures to prevent unique and valuable but more explicit knowledge from getting into the wrong place. They have done this by using patents or contracts with employees which prevents that knowledge from being used by competitors (Bontis, 2010). Consider for example the measures that are taken to protect knowledge on secret recipes (e.g. coca cola – world’s best kept secret knowledge?), on customer relations (e.g. accountancy firms forbid consultants to take their clients’ contact details – and the knowledge about these clients – when changing jobs to another accountancy firm) and new technology (e.g. university spin-offs carefully apply for patents that protect the copying of innovative products by other organizations). So, although explicit knowledge is sustainable and rare, it can be copied (transferred) because it can be written down or explained – it is transparent.
Tacit knowledge in organizations is the unwritten, hard to explain way of doing things. Since tacit knowledge is more difficult to share, and since it resides within the social practice of the organization (knowing how, knowing who), it qualifies more as a valuable resource than explicit knowledge. It is non-transparent because it is hard to explain in the first place and it is non-transferable because in order to use it, you need to know the specific context in which it is used. This is where knowledge-based theory and human capital theory agree: the most valuable type of knowledge for organizations is tacit, firm specific knowledge.
Summarized, explicit knowledge and tacit knowledge are both important resources for an organization’s performance. Explicit knowledge can be easily shared, which can pose a risk to organizations when this knowledge ‘leaks’ to competitors. Tacit knowledge is more difficult to transfer to another organization and is considered the core of ‘firm-specific’ human capital.
The following section addresses theory on knowledge transfer within organizations.
Transfer of knowledge
When the performance of organizations is dependent on the capability of its workforce to apply knowledge (Grant, 1996), the question of how to ensure that the entire workforce has access to knowledge becomes of crucial importance. As we have seen, a large part of knowledge is not accessible in written information, but instead resides in individuals.
Transfer of knowledge is the process by which knowledge holders share their knowledge with others, who learn from this knowledge so that they can apply it. Knowledge transfer is comparable with the concept ‘transfer of training’: the sharing of information results in a change in the knowledge the recipient can apply at work. Transfer of knowledge research focuses mostly on the transfer of tacit knowledge, because this is the most complex type of knowledge to transfer from one individual to the next. The literature on knowledge transfer zooms in on the social processes and social systems in organizations.
Organizational knowledge transfer refers to the process through which units in organizations – e.g. teams, business units, or even entire organizations – share, receive and are influenced by the knowledge of others. Knowledge transfer manifests itself through changes in the knowledge base or performance of recipients (Van Wijk et al., 2008). Therefore, effective knowledge transfer in organizations is dependent on two parties: knowledge senders and knowledge recipients.
Knowledge senders have to be able and willing to share their knowledge with others. Moreover, they have to find opportunities to share their knowledge with those who need it (Wang & Noe, 2010). Sharing knowledge with others implies that you take the initiative to do so. Not all individuals are as equally open as others to do that. Moreover, knowledge senders may be reluctant to share their knowledge in the first place because they fear that it will undermine their power base in an organization, or they may feel that their knowledge is not so important. Practically, they may not know that other individuals or business units are in need of their knowledge. So many factors on behalf of knowledge senders may keep the transfer of knowledge from occurring.
Knowledge recipients can also distort or enhance the transfer of knowledge, again through their ability, willingness and opportunities to receive and acquire knowledge. For example, knowledge recipients may question the value of the knowledge they could receive. In the complex organizational context, one’s position in the organizations’ power and politics may lead to questioning the value of the knowledge sender. New knowledge can also pose a threat to the position of the knowledge recipient. These situations of knowledge ambiguity lead knowledge recipients to disregard the value of the knowledge they receive, which will not lead to a change in knowledge or performance (Van Wijk et al., 2008). In contrast, individuals and business units that are open to finding, recognizing, assimilating and applying new external knowledge will be more capable of and efficient in knowledge transfer (Zahra & George, 2002).
Since knowledge transfer happens in exchange relations, it should be understood as a social process. In this regard it is important that senders and recipients can actually meet (have the opportunity to exchange knowledge) and that there is trust between both parties (good-quality relationships), and a recognition that new knowledge matters.
A social network visualization of organizations as a pattern of connections between individuals, and between business units provides a swift impression of the chance that knowledge holders will actually meet knowledge recipients. Figure 3.2 represents the social networks in two organizations. In organization A, there is a hierarchy in the network, where the business units are connected through one central unit only. In the other organization (B) there are many connections between all business units, which increases the likelihood that knowledge senders and recipients will actually meet.
Moreover, the figure also illustrates the quality of the connections. A thicker line indicates a better-quality relationship. So, in organization A, knowledge transfer is most likely to happen in only one of the connections. All other connections have lesser-quality relations where there may be a lack of motivation to share knowledge by knowledge holders, and an unwillingness to look for and accept knowledge from knowledge recipients. In contrast, organization B is characterized by a network of trustworthy relationships. Based on this information, it is to be expected that much more knowledge exchange will happen in organization B as compared to organization A.
Figure 2
Network visualization of the number and quality of connections for knowledge transfer between business units in two organizations
Finally, an organizational culture that emphasizes the importance of knowledge sharing and acquisition will help organization B to benefit even more from the good and dense network of relations between all business units (Zahra & George, 2002).
Organization B is characterized by a higher level of absorptive capacity, which is the capacity of organizations to face external events by bringing new knowledge to the organization and making it part of the knowledge base. By acquiring and utilizing knowledge, an organization’s ability to gain and sustain a competitive advantage is significantly enhanced (Zahra & George, 2002). Organizations that liaise with a wide array of knowledge sources provide fruitful soil for knowledge creation and innovation. This will be addressed in the following section.
Knowledge creation and innovation
Knowledge transfer is a critical part of knowledge creation. New knowledge is created when individuals or business units share what they know with others, internalize and compare it with their own knowledge and apply this synthesized knowledge to improve their performance or create new knowledge. New knowledge resonates with innovation, the process that involves the development and improvement of products, production and services that help organizations renew and stay competitive (Crossan & Apaydin, 2010). Innovation starts with the bringing together of knowledge from different sources.
Ikujiro Nonaka and Hirotaka Takeuchi, two organizational science professors at Hitotsubashi University in Tokyo, shared an interest in the process of knowledge creation within corporations. Both met and received their PhDs in organization studies in the United States, and back in Japan they combined their knowledge with observations on successful Japanese companies such as Fuji and Honda. Japanese industries had been very successful in the 80s compared to European and US industries. Nonaka and Takeuchi set out to understand the business processes contributing to this success. This resulted in a very influential book publication in 1991, entitled “The knowledge creating company: How Japanese companies create the dynamics of innovation”, with which they put knowledge as a source for innovation and business success on the management agenda (Nonaka, 1991). In particular, they claimed that Japanese firms were organized in such a way that they had procedures in place to leverage tacit knowledge by a business philosophy called Kai-Zen. The meaning of Kai-Zen is ‘continuous improvement’ or ‘change for the better’ and in business this meant a continuous focus on improving the quality and effectiveness of business processes by using the knowledge of all individuals involved in processes. By continuously being on top of quality and effectiveness, Japanese companies were better able to manufacture in a ‘lean’ way: they produced good products at relatively low prices. Kai-Zen became a leading business strategy in the 90s not only in manufacturing but also in service industries worldwide.
The core of organizational knowledge creation theory is that there is a continuous flow between tacit and explicit knowledge that results in new knowledge (Nonaka, 1994). New knowledge is created when people share what they know with each other, when they internalize it into their tacit knowledge, and apply what they have learned to improve how they work. Figure 3.3 illustrates the four flow processes between tacit and explicit knowledge that contribute to building organizational knowledge.
Figure 3
Knowledge creation processes
The figure depicts the knowledge flows between similar types of knowledge (processes A and B) and between different types of knowledge (processes C and D). Processes A and B are essentially knowledge transfer processes in which knowledge is exchanged between a knowledge holder and a knowledge recipient. The recipient learns by acquiring the tacit or explicit knowledge from the other.
The first process (A) indicates the flow from tacit to tacit knowledge. This involves knowledge transfer by means of observing the behavior of others, by imitating and practicing, or becoming “socialized” into a specific way of doing things. Tacit knowledge of experts flows to novices by simply cooperating on a task or a project. Knowledge in process A is not explicit because it is not verbalized.
Process (B) indicates the flow from explicit to explicit. Knowledge transfer in this flow involves exchanging and combining separate pieces of explicit knowledge into a new whole. For example, by bringing together different data sources to write a financial report.
Knowledge development happens in processes C and D. Process C indicates how individuals reflect on their actions and performance. Through their reflection, they become better able to verbalize their tacit knowledge and explain to others what they do and why they do it. And when they receive new information, for example by reading a book, they are able to reflect on the value of this explicit knowledge for their own work and integrate it into their daily tacit operations. Process C is the process of individual learning. Before tacit knowledge can be accessed, it has to be recognized as knowledge and articulated as such. Then, the individual’s unique tacit knowledge can be accessed and applied in creative ways. This step is an essential element of group-level learning and knowledge creation.
The last process (D) illustrates knowledge creation in groups. The flow goes two ways: from tacit to explicit and from explicit to tacit. In both flows the outcome is new knowledge. The flow from tacit to explicit indicates the verbalization of tacit knowledge in groups with the aim to improve something. In group meetings, individuals can explicate their tacit knowledge, combine it with the experience of others, discuss the value of these experiences and synthesize it in creative ways to extend or reframe a solution. The results of such discussions can lead to documented improvements in procedures (e.g. a manual with work instructions), and to innovations in products. The discussions about the various experiences of individual knowledge holders allow the information to be compared, weighted and synthesized into new knowledge. When the resulting new knowledge is documented so that others can refer to it without having to meet with the tacit knowledge holders, tacit knowledge has become crystallized: it has become ‘externalized’.
Finally, in the flow from explicit to tacit, groups reframe or interpret explicit knowledge at their availability within their own frame of reference. New policies, new technology, or organizational changes all require that the explicit knowledge is reflected upon, discussed, accepted, integrated and thereby internalized in the tacit operations of the group.
Knowledge creation in organizations happens naturally at all levels from the shop floor to the board of directors, but by creating a culture for continuous learning and improvement, management can stimulate learning and knowledge creation processes. By stimulating the learning capacity of the entire organization, the organization as a whole becomes better able to play on challenges outside of the organization (Argote & Miron-Spektor, 2011).
Knowledge storage, retrieval and use
Tacit knowledge that has not been externalized and resides in individuals is easily lost. Organizations merge, downsize, reorganize, and change clients, leaders or suppliers and so on. In all such examples, individuals with their valuable tacit knowledge disperse and their knowledge vanishes. But even documented explicit knowledge gets lost if it is stored in the wrong way or inaccessible for those who could need it.
Organizations are sometimes blamed for ‘amnesia’: having very short memory-spans because of the continuous loss of knowledge. In particular in organizations that rely heavily on expert knowledge, preventing amnesia due to individuals changing jobs or otherwise are dedicated to installing knowledge management systems to store and retrieve knowledge if needed.
The complexity of the issue becomes clear if you consider an international consultancy firm with clients all over the world. The knowledge of experts about clients is very much contextualized and therefore tacit: the specific habits and cultures, whom to address, and what was discussed with whom about what. If the consultant is not probed to explicate this tacit knowledge before she hands over the contract with the client to her successor, the client-consultant relationship may be harmed because the successor is ignorant about sensitive social issues.
The transfer of all types of tacit and explicit knowledge of individuals and teams into organizational memory is a question of knowledge management (Alavi & Leidner, 2001): about retrieving knowledge from the past, from experience and from events, into a shared or collective memory that can be accessed and used to improve today’s performance. Organizational memory contains both semantic and episodic knowledge.
Semantic knowledge is the knowledge that is documented – it is the explicit knowledge that can be easily accessed. For example, a carpet manufacturer opened a new production facility in China by exactly copying the facility it already operated in Europe. Following the exact same layout, machine building handbooks and using well-documented production manuals, engineers were able to realize the new production facility in due time. They used the semantic knowledge and were able to create a brand new copy of exactly the same production facility. However, when trial testing the new production facility, they did not succeed in producing the same quality carpets as the old production facility. From that point on, the semantic knowledge no longer helped to get the new facility running. Experts joined together and started evaluating what could have gone wrong. From there on, the project relied more heavily on the episodic knowledge of experts.
Episodic knowledge is much more tacit. It is the shared knowledge of groups in the organization that links specific events. The groups would not have this knowledge if they did not share an experience. In the example, the experts started to trace back all design steps and process documents, to inspect if anything was overlooked. In the end, they figured out that the issue was in the production process of one of the suppliers, who followed a slightly different chemical procedure that caused a difference in the resources used to produce the carpets. This specific part of knowledge was not documented and caused a short delay in the productivity of the new facility. However, if the experts holding the episodic knowledge had not been available to share their experience, the delay would have been much longer. In conclusion, knowledge management research focuses on social and IT-based systems that facilitate the transfer, storage, retrieval and use of knowledge in organizations. Knowledge management is the vehicle of knowledge use in organizations which, according to the knowledge-based theory (Grant, 1996), is what enables organizations to realize their goals.
Key research
The selected meta-analytical research that is presented in this chapter highlights some of the impressive evidence on formal and informal learning effectiveness in organizations and on the conditions for effective knowledge transfer and creation.
Formal learning effectiveness
Training design and effectiveness. Arthur et al. (2003) examined in a meta-analytic study which training design and evaluation features make training in organizations effective. They confirmed that well-designed training (using all the insights about how individuals learn) yielded the best learning outcomes. They plead that managers and HR professionals should critically judge the design of the training they purchase for their organization. Interestingly, they also found that the most used type of training evaluation (which is asking participants “did you like the training?”) was completely unrelated to the effectiveness of the training. The researchers follow Holton (2005) and prompt that training evaluations had better include a knowledge test, or ask participants if they feel efficacious in performing their new knowledge.
Transfer of training. Another big question focuses on what conditions would increase the likelihood that trainees will use the newly acquired knowledge in the workplace? In their meta-analysis, Blume et al. (2010) report three ways in which training transfer can be enabled. First, it was found that individuals who volunteered to join a training program are more likely to apply what they learned in training compared to individuals who were forced to participate. This implies that policy-makers should pay attention to motivating employees before going to the training. Second, this meta-analysis also implies that good training designs, aimed at improving knowledge and gaining self-efficacy in using that knowledge, can make a difference. Next, the work environment that trainees find themselves in when they go back to work matters for training transfer. A department climate where new knowledge is welcomed will provide a better environment for training transfer than one where colleagues and supervisors are suspicious about the new knowledge and unwilling to ‘give it a try’. In the latter case, the knowledge learned in the training will soon fade.
Training effectiveness in various knowledge domains. What type of training interventions best suit a specific learning goal? Which training interventions work best to develop leadership skills, and which work to prepare expats for their stay in a foreign country? There are meta-analytic overviews for many specific training domains like diversity training (Bezrukova et al., 2016), intercultural training for expats (Morris & Robie, 2001), stress management training (Robertson et al., 2015), leadership training (Collins & Holton, 2004), and for the training of specific professions such as surgeons (e.g. effectiveness of virtual reality (VR) simulators) (Haque & Srinivasan, 2006), to name a few. Each domain-specific training meta-analysis provides evidence about the dos and don’ts for specific learning domains.
Informal learning effectiveness
Informal learning. Cerasoli et al. (2018) examined empirical studies on the antecedents and outcomes of informal learning in a meta-analytical study. It was found that the most important conditions for informal learning to occur were support (from a coach or manager) and the design of the job (e.g. the amount of autonomy and having challenging tasks). In addition, personal characteristics like skills and experience and having a positive attitude towards one’s job promoted informal learning. Demographic differences (e.g. age, gender, education) all had a small and inconsistent impact on informal learning. This supports the view that informal learning can be stimulated by offering a workplace that stimulates learning opportunities.
A meta-analysis on the effectiveness of workplace coaching (Jones et al., 2016), a method to transfer tacit knowledge, provides additional evidence for the power of informal learning for performance improvement. In particular, informal learning was effective when individuals could work with an internal coach, often a manager or expert from within the organization.
Knowledge transfer and knowledge creation effectiveness
Organizations with higher levels of knowledge transfer show better performance and innovation scores (Van Wijk et al., 2008). The meta-analyses show that knowledge transfer at the organizational level that involves sharing knowledge between organizations in particular is important for performance and innovation. This supports the view that organizations that can better ‘absorb’ knowledge are more capable of dealing with challenges. The study also confirms that the transfer of tacit knowledge is much more difficult than the transfer of explicit knowledge.
In a meta-analysis of 104 studies on the conditions for innovation in the workplace, Hülsheger et al. (2009) found that team processes are important for groups to exchange and combine knowledge into creative solutions and innovation at work. Teams that are supported in innovative behavior, that have a shared vision which emphasizes innovation matters, and that communicate well with other units inside and outside the organization (have good-quality social ties) show the highest levels of creativity and innovation.
HR practice
The HR practices section distinguishes between practices aimed at organizing individual learning and practices aimed at organizational learning and knowledge management.
Practices for individual learning
Learning in organizations involves the question of how employees can best acquire the knowledge they need to perform their jobs well and to contribute to the team and the organization as a whole, as well as to be prepared for change and future demands. Traditionally, learning in organizations was equated with a planned, top-down process that involves the organization of classroom-based, formal learning events. More recently and in accordance with Marsick and Watkins' (2001) work on informal and incidental learning, learning in organizations was broadened to include learning that occurs when individuals perform their jobs: learning in the workplace.
Organizing formal learning: practices for knowledge creation
Formal learning in organizations is a planned process to address the knowledge gaps of employees in organizations. Planned formal learning (e.g. organizing a training) involves the following steps (Aguinis & Kraiger, 2009; Tannenbaum & Yukl, 1992):
Analyze training needs. What are the (changing) goals of the organization? Which jobs and tasks need to be performed to achieve those goals? Which knowledge and skills are needed to perform those tasks? How well are current employees able to perform those (new) tasks? Is there a gap in their knowledge and skills that can be addressed by organizing a training program?
Determine the learning goals for the training. What is it that learners will know at the end of the training? Which new skills will have been learned?
Design the training. Consider which training methods best suit the abilities and skills of the trainees. Will it be an instructor-based training with a lecturer talking in front of a classroom? Or some kind of simulation in which trainees can practice new skills? Or online modules which trainees can do anywhere?
Consider the pre-training environment. Do employees understand the reason for the training? Is some pre-training instruction needed? Do they agree on how the training will benefit their work?
Consider the post-training environment. Can the trainees apply the skills and knowledge directly in their jobs? Or is some post-training activity needed to ensure that the trainees can apply their newly acquired knowledge?
Evaluate the training. Were the learning goals of the training met? Do the trainees perform better in their jobs?
There is extensive literature on the effectiveness of each of these aspects of the planned formal learning process in relation to training outcomes.
Organizing informal learning
Workplace learning is different from formal learning in the sense that it does not happen in a designed learning environment, but in the workplace itself. A workplace is a physical location where employees perform work tasks and interact with others. The workplace is also connected to the larger organization and it is embedded in the norms, values and procedures ‘how things are done’ in organizations (Tynjälä, 2008). Workplaces can provide excellent learning environments, especially for informal and incidental learning.
Compared to training, there is much more ‘reality’ in the workplace. This makes workplaces an ideal environment to acquire tacit knowledge (Marsick & Watkins, 2001). Any challenge that the job brings, provides a learning opportunity. Through trial and error of new procedures to optimize or facilitate performance, and by reflecting on work experiences, employees’ (tacit) knowledge continuously grows. Employees who experience challenges at work will feel the need to learn and will (consciously or unconsciously) look for new knowledge. Moreover, by cooperating and interacting with colleagues and clients, employees learn continuously. Social interaction and dialogue are excellent learning opportunities.
Challenging tasks and social collaboration at work are examples of occasions for informal or even incidental learning. However, learning on the job can also be planned and formal in nature. Consider for example a formal, organized course that involves practice at work. Since employees can immediately use the knowledge they acquire, transfer of training is much less of an issue in workplace learning than in classroom trainings. Nowadays it is considered a ‘best practice’ to organize workplace learning into formal training programs.
Organizing informal and incidental workplace learning is a bit more of a challenge. Despite the fact that individuals will always learn in unintended ways, it is sometimes important and desirable to plan workplace learning. Think for example about onboarding or socializing new employees. Interaction is an excellent way to stimulate the transfer of knowledge between new and experienced employees. However, for this interaction to happen, it is a good idea to allow experienced employees some time for coaching new employees. Similarly, by creating project groups with employees with different functional backgrounds, management can stimulate workplace learning to occur. Other examples or organized informal learning activities are ‘communities of practice’ (where people with similar jobs exchange their experience, e.g. in intervision groups), study tours, advisory boards, job rotation, sharing experience in meetings and task forces. These are all examples of group work that promotes knowledge exchange and the sharing of expertise, and thus enhances individual learning.
Practices for knowledge creation
Organizations that effectively transfer and create innovation provide a work context that emphasizes the importance of learning. Learning in organizations will always happen, but it can be accelerated if it is supported by a vision, a strategy, a structure and a shared understanding that learning matters. Factors that support a focus on organizational learning include:
Role modeling behavior of senior management: leading by giving the right example in sharing, transferring, and challenging others to do the same. Through top-down promotion of the importance of learning and by continuously reinforcing learning behaviors, management can create an organizational culture for learning and knowledge development.
Work and organizational designs that enable cooperation, that provide the autonomy to experiment with innovations in work processes and where there are resources and time for learning, collaborating and experimentation.
Structural factors to facilitate learning at large, such as inviting experts on human resource development for advice, ICT and knowledge management systems, and access to networks with knowledge holders outside the organization.
Individual employees can be stimulated by making it the employees’ responsibility to keep learning and participating in knowledge transfer and creation. When it is ‘part of the job’, it can be reinforced by integrating it as an objective for employee appraisal and reward. In this way, learning, knowledge transfer and knowledge creation are an integral part of all organizational processes.
Securing knowledge storage
A relevant example of the use of knowledge storage and retrieval tools is project work. Projects are infamous when it comes to knowledge loss. Sure, the end product or report is used (or stored), but all the knowledge about the route to get to the project outcomes leaves with the members of the project team when they go back to their respective jobs. To prevent new projects from encountering the same problems, management should take action to monitor and learn from the project processes. For example, the team can meet in a closure session during which all the critical moments are reflected on. When the notes of such ‘lessons learned’ meetings are stored, future teams can use them in their start-up phase as a reference. Specific tools for effectively capturing the episodic knowledge developed in project teams are described in (Schindler & Eppler, 2003).
The value of knowledge for organizations is a specification of human capital theory. Organizations with a better educated, more experienced workforce outperform their competitors, in particular when that knowledge is specific for that organization. There are different types of knowledge. Explicit knowledge, knowledge about what and why, is easily documented and explained. In contrast, tacit knowledge, knowing how and knowing who, is not found in manuals or textbooks but is learned in practice. Tacit knowledge is subtle, difficult to explain; it just ‘is’, but without it organizations would be unable to function. Tacit knowledge is what constitutes organization-specific knowledge. Managers should be as much concerned about tacit knowledge as about explicit knowledge.
Individuals learn in classrooms (formal learning), while learning their jobs and working on projects (informal learning), and by accident (incidental learning). Transfer of what was learned in formal education to the workplace may be difficult. Good training designs will blend formal and informal learning.
Knowledge is crucial for organizational performance. Knowledge-based theory states that the function of organizations is to ensure that individual knowledge is put to use in the organization. When individuals share their knowledge (both explicit and tacit), organizations can learn and innovate. Organizational knowledge creation happens in a continuous flow between tacit and explicit knowledge by processes of socialization, reflection, combination, and internalization or externalization. Learning organizations are those that succeed in creating conditions that facilitate the sharing of tacit knowledge, explicating tacit to explicit, storing and combining explicit knowledge and reflecting on new combinations of explicit knowledge to invent new tacit knowledge (Nonaka and Takeuchi ‘spiral of knowledge creation’). Organizational features like hierarchy and teamwork facilitate the transfer of knowledge.
Despite all efforts to obtain and create knowledge, especially tacit knowledge is easily lost when organizations merge or downsize, when people leave or when projects ends. In order to prevent organizational amnesia, active management of knowledge storage and retrieval of semantic knowledge is needed.
The value of knowledge for organizations is a specification of human capital theory. Organizations with a better educated, more experienced workforce outperform their competitors, in particular when that knowledge is specific for that organization. There are different types of knowledge. Explicit knowledge, knowledge about what and why, is easily documented and explained. In contrast, tacit knowledge, knowing how and knowing who, is not found in manuals or textbooks but is learned in practice. Tacit knowledge is subtle, difficult to explain; it just ‘is’, but without it organizations would be unable to function. Tacit knowledge is what constitutes organization-specific knowledge. Managers should be as much concerned about tacit knowledge as about explicit knowledge.
Individuals learn in classrooms (formal learning), while learning their jobs and working on projects (informal learning), and by accident (incidental learning). Transfer of what was learned in formal education to the workplace may be difficult. Good training designs will blend formal and informal learning.
Knowledge is crucial for organizational performance. Knowledge-based theory states that the function of organizations is to ensure that individual knowledge is put to use in the organization. When individuals share their knowledge (both explicit and tacit), organizations can learn and innovate. Organizational knowledge creation happens in a continuous flow between tacit and explicit knowledge by processes of socialization, reflection, combination, and internalization or externalization. Learning organizations are those that succeed in creating conditions that facilitate the sharing of tacit knowledge, explicating tacit to explicit, storing and combining explicit knowledge and reflecting on new combinations of explicit knowledge to invent new tacit knowledge (Nonaka and Takeuchi ‘spiral of knowledge creation’). Organizational features like hierarchy and teamwork facilitate the transfer of knowledge.
Despite all efforts to obtain and create knowledge, especially tacit knowledge is easily lost when organizations merge or downsize, when people leave or when projects ends. In order to prevent organizational amnesia, active management of knowledge storage and retrieval of semantic knowledge is needed.
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