History of KM



Note: Please use the following source referencing:
Minonne, C. 2007. Towards An Integrative Approach For Managing Implicit And Explicit Knowledge: An Exploratory Study In Switzerland, Doctoral Dissertation, University of South Australia (UniSA)

 

The respective scholarly and practitioner contributions in related fields of KM is quite broad and offers various theoretical perspectives from which to regard the management of knowledge related assets as the central role.

While defined in many different ways, KM generally refers to how organisations create (learning processes), disseminate (knowledge sharing), and measure knowledge related assets, also known as intellectual capital measurement (Argote 1999; Edvinsson ad Malone 1997; Huber 1991, Sveiby 1986, 1997).

The study of ‘knowledge-sharing’ has emerged from the field of organisational learning. The literature suggests that successful knowledge sharing involves extended learning processes, as new knowledge related to innovation needs to be integrated into new products, services, or business processes (Nelson and Rosenberg 1993).

Raub and Rüling (2001, p. 114) argue that while research on business strategy has been occupied with outlining a comprehensive knowledge-based theory of the firm, other disciplines have contributed their views on how to analyse and manage knowledge as an organisational resource. The conclusion drawn by the review of the respective literature is that the contributions pertaining to the management of knowledge can be divided into the following three main streams:

  • Intellectual Capital Management (ICM)
  • Organisational Knowledge Management (OKM)
  • Organisational Learning Management (OLM)


Although the review of the respective literature shows that these three concepts lack a unifyingvision,  they all relate to each other, by informing one another, and are a means to an end of a knowledge-based orientation of strategic management (Barney 1991; Conner 1991; Hamel and Prahalad; Wernerfelt 1984).

Between the early 1970s and the late 1990s no serious attempt was made to combine organisational learning with intellectual capital or organisational knowledge management theories. The impression arises that this phenomenon exists because of the different practical as well as theoretical roots and affiliations of the various contributors. Whereas organisational learning theories were mostly developed by people with a professional background in basic social sciences, i.e. sociology, psychology (e.g. Argyris, Bell, Giddens, Hedberg, Levitt, March, Senge, Schön, and Weick), intellectual capital theories were dominated by practitioners and academics with a strong background in financial accounting and monitoring of organisational performance (e.g. Bukh, Edvinsson, Kaplan, Lev, Malone, Norton, Stewart, Sveiby). Oganisational knowledge management theories were developed by both, people who show a strong interest in strategic and human resource management (e.g. Barney, Conner, Davenport, Gibbert, Hamel, Nonaka, North, Prahalad, Prusak, Probst, Raub, Romhardt, Takeuchi, Teece, Wernerfelt) as well as by experts focusing on information management systems (e.g. Alavi, Baets, Boland, Koenig, Leidner, Mertins, Ponzi, Tenkasi, Venugopal).

Interestingly, from time to time, the terms intellectual capital management (ICM), organisational knowledge management (OKM) and organisational learning management (OLM) are used interchangeably (Schneider 2005). Today’s literature still reflects these orientations to a high extent, although many scholars and practitioners seek to conduct their research or implement new intra-corporate knowledge management practices by trying to combine the three conceptual orientations and thus taking a more unified approach (Huber 1991; Probst et al. 2001; von Krogh 1998).

However, it is the enablement of such an ‘integrative’ view that practitioners are interested in, to be able to define and implement new organisational KM practices for managing an organisation’s knowledge-assets. Hence, this inference looks for an interdisciplinary approach regarding a combined or integrative management of implicit knowledge and explicit knowledge-objects of organisations, by combining the ‘WHAT do we know’ gained from  the field of intellectual capital management (ICM) and organisational knowledge management (OKM) theories and practices, and the ‘HOW can we do’ of organisational learning management (OLM) theories and practices (Easterby-Smith 1997; Easterby-Smith and Lyles 2003; Fiol 1985; Hedberg 1981; Levitt and March 1988; Senge 1990).

Below, the three different conceptual orientations are discussed, by relying on a historical exploration of the key scholarly and practitioner contributions.



Intellectual Capital Management

Many scholars in the intellectual capital management (ICM) field appear to have developed their theories based on Polanyi’s (1966) epistemological position and philosophical thoughts (e.g. Sveiby, Edvinsson, Itami, Sullivan, Stewart). Polanyi seems to be perceived as the father of the ‘Tacit Knowledge’ theory, who realised that: ‘We know more than we can express.’
In 1966, Polanyi published ‘The Tacit Dimension’, a book that refined the epistemology articulated in his previous book ‘Personal Knowledge (1958)’. In ‘The Tacit Dimension’ (1966) he illustrated more carefully the structure of implicit knowledge (described as ‘tacit’). Almost one decade later, his last book ‘Meaning’ (1975) was published with the collaboration of the American philosopher Prosch, one year before Polanyi’s death.
Although there is a certain acknowledgement in the intellectual capital management (ICM) community that this field of research started to take shape as an independent discipline between the late 1980s and early 1990s when the two Swedish practitioners Sveiby and Edvinsson highlighted the inadequacy of traditional financial measures of corporate assets, the review of the respective literature highlights that Lev was already investigating the concept of measuring intangible assets (especially the human capital component) in the early 1970s.  In fact, it was in the year 1971 when Lev published the article ‘On the Use of the Economic Concept of Human Capital in Financial Statements’, which was co-authored with Schwartz (Lev and Schwarz 1971).  The article highlights the definition of human capital as a source of income embodied in a person (implicit knowledge) widely used in the economic literature, and is included in their discussion of the human capital concept. Their main objective was to expose accountants to the economic concept and measurement procedures and in particular to point to some possible accounting implications of this concept.
Furthermore, Handy (1989) observed that (on average) an organisation’s intangible assets are three to four times the firm’s book value. However, Lev and Schwartz (1972, p. 153) affirmed that since human capital reporting models during that time were largely nonexistent, it was almost impossible to define precisely the role of human capital information in decision making. However, Lev’s extensive research was not widely acknowledged in the respective literature until the mid 1990's.
It is also widely acknowledged that Itami’s ‘Mobilizing Invisible Assets’, which was first published in Japan in 1980, and then translated into English in 1987, represents the first meaningful contribution in the field of intellectual capital management coming from Asia, which was widely acknowledged by Western academia.
It was in 1986 when Sveiby’s first book was published (co-authored with Risling) in Swedish with the title ‘Kunskapsföretaget’ (The Know-How Company) before it became a bestseller. Based on his further work in the late 1980s (Sveiby 1986, 1988, 1989) he then became one of the most acknowledged contributors in this field before he finished his PhD dissertation titled ‘Towards A Knowledge Perspective On Organisation’ in the year 1994.
It is perceived that it is Tom Stewart, who in his article ‘Brainpower – How Intellectual Capital Is Becoming America’s Most Valuable Asset’ (Stewart 1991), brings ICM firmly on the management agenda. In his article, Stewart defines intellectual capital as ‘the sum of everything everybody in a company knows that gives the company a competitive edge in the market place’ and later he further clarifies it as intellectual material – knowledge, information, intellectual property and experience – that can be put to use to create wealth (Stewart 1997, cited in Bontis 2001, p. 42).
In his book ‘The New Organizational Wealth: Managing and Measuring Knowledge-Based Assets’ (1997) Sveiby argues that intangible knowledge-assets are treated as invisible only because they lack a generally accepted definition and measurement standard and suggests a methodology for approaching the difficult task of classifying and measuring intangible assets, by considering the three main elements on which his IAM (Intangible Assets Monitor) model builds ‘employee competence’ (i.e. skills, education, experience), an organisation’s ‘internal structure’ (i.e. organisational design, patents, concepts, models, R&D capabilities, software), and its ‘external structure’ (i.e. image, brands, customer and supplier relations) (Gibbert et al. 2002).
Furthermore, in the same year, Edvinsson and Malone (1997) observed that the traditional model of accounting, which so described the operations of companies for half a millennium, was failing to keep up with the revolution that was taking place in business, by arguing further that it had become obvious that the real value of most companies lies not in bricks and mortar, or even in inventories (book value), but in another, intangible kind of asset called Intellectual Capital (IC), by highlighting the difference between market capitalisation and book value and by illustrating examples like Microsoft and Intel! The goal of their influencing work was to ‘identify’ these intangible factors off the balance sheet, ‘measure’ them, and find a way to ‘present’ them coherently. Typically, these intangible factors appear to take the following three basic forms: human capital (employee competence), structural capital (internal structure), and customer capital (external structure).
However, Edvinsson and Malone (1997) combined Sveiby’s work (1989) with Kaplan and Norton’s Balanced Scorecard (1996). However, for them ICM is the study of the roots of a company’s value and the measurement of the hidden dynamic factors that underlie the visible company of buildings and products. In their study, Edvinsson and Malone also explain how Skandia, a Swedish financial services company, made a start in 1994 (to consider that Edvinsson was appointed first world-wide Corporate Director of Intellectual Capital at Skandia in 1991). The result of the Skandia study was a model for ‘visualising and reporting’ intellectual capital. They also state that rather than replacing the traditional financial measurement system, the intellectual capital measurement in fact complements and augments it.
Most of Itami and Sveiby’s thinking about valuing intellectual assets strongly influenced Sullivan’s work. Sullivan’s main contributions for the ICM literature arose between 1996 and 2000 with ‘Technology Licensing: Corporate Strategies for Maximizing Value’ (1996, co-authored with Parr), ‘Profiting from Intellectual Capital: Extracting Value from Innovation’ (1998), and ‘Value-Driven Intellectual Capital: How to Convert Intangible Corporate Assets into Market Value’ (2000).
In his highly practical work Sullivan suggests basic concepts underlying intellectual capital and corporate value creation, by investigating the linkage between intellectual capital, business strategy, and profits, and providing methods for ‘calculating’ the financial value of organisations for market capitalisation and mergers or acquisitions. Sullivan’s contribution into practice can be regarded as an extremely helpful approach for managers for valuing their organisation’s intangible assets, by providing good answers to Lev’s suggestion that the successful management of intellectual assets requires a ‘unified’ approach across the major domains of knowledge-discovery (innovation), employees competence, customers (external structure), and organisational designs (internal structure), and the linking of KM to the overall strategy of the enterprise (2000, p. 10).
Later, when intellectual capital management (ICM) became the domain of the so-called Chief Knowledge Officer (CKO) (Earl and Scott 1999; Guns 1998; Herschel 2000; Raub and Rüling 2002), Bontis reviewed the literature pertaining to the assessment of knowledge-assets and published his findings in the article ‘Assessing Knowledge Assets: A Review Of The Models Used To Measure Intellectual Capital’. Bontis investigated the main models used in practice for measuring intangible assets by highlighting their strengths, weaknesses and their ability to operationalise (2001, p. 42). He acknowledges that it is definitely Skandia, a Swedish financial services company, representing the first large organisation to have made a truly coherent effort at measuring knowledge-assets (2001, p. 44).
In the same context, Covin and Stivers (1998, cited in Bontis 2001, p. 58) surveyed 253 companies among US Fortune 500 and Canadian Post 300 in their study of non-financial measure usage. Results showed that, even though two third of the sample felt that measuring intangible assets was important, only 14% were actually measuring it, and only 10% were actually using the measures for redesigning their business strategy. However, these results show a significant measurement/use gap.
Another study that was conducted four years later (2002) showed that 25% of Fortune 500 companies currently had CKOs, and that 80% of these companies currently had dedicated staff for KM. Based on a survey conducted at the 2001 World Economic Forum (WEF) in Switzerland, 95% of the participating CEOs said that KM was critical to their organisational success.
Furthermore, Bontis’ review (2001) of existing models to measure intangible assets confirms that, interestingly, many ICM models had similar constructs and measures that were merely labelled differently by arguing that this re-labelling of similar conceptualisations can be construed as both positive and negative for the field of ICM. On a positive note, Bontis states that this shows that different researchers are narrowing their frameworks, and focusing on important concepts that are consistent across various perspectives. However, he argues further that since the field was still in its embryonic stage, no one was willing to give up their own nomenclature and build off each other’s work, by suggesting that perhaps a change for the better will occur as this field develops further and the desire for more valid and ‘generalisable’ measures emerges. This is important for the development of this field in the near term to build on each researcher’s work so that a common set of definitions can be used, and that a major challenge for ICM research thus far was that it had been primarily of the anecdotal variety, by arguing that most researchers had thus far conducted case-based reviews of organisations who had established intellectual capital initiatives already. However, in Bontis opinion, researchers have merely documented the metrics that were developed by Skandia and others without advancing or testing them (Bontis 2001, p. 57).
After two more years of academic work Lev and Zambon (2003, p. 598) believe that the rise of the importance of intangible assets in today’s economy requires not only the development of specific measurement tools for these assets, but also the adoption of a different and more comprehensive conceptual view of organisational dynamics. In their view, this requires in turn different measurement, communication and interpretation tools and methods.
However, the many theoretical models, which were developed during the last 15 to 20 years, have found a high degree of acceptance by practitioners. In fact, Lev and Zambon (2003) report that a significant response to the issues by non-traditional accounting and reporting has been the definition and implementation of intellectual capital statements in various organisations. Furthermore they report that beyond their potential ‘informativeness’ for external stakeholders, such intellectual capital statements seem to have a fundamental function of self-analysis for the organisation, forcing it to recognise both its implicit assets and the different links between the various types of capital.
However, more research is still required to address the numerous conceptual and operational issues in this field. According to Lev and Zambon (2003), the multiform nature of intangibles also suggests the adoption of differentiated research approaches, which should have in common an effort to overcome the traditional disciplinary boundaries and to employ new ways of conceiving and addressing the relevant issues.
In his article "New Pressures On Valuing Acquired Intangibles" (2002), Petrash corroborates that, thanks to the new company-merger accounting rules promulgated in the middle of 2001 by the Financial Accounting Standards Board (FASB), at least in the USA, investors and other corporate stakeholders can gain unprecedented visibility into the way organisations manage their intangible assets. He argues further that because corporate stakeholders today are demanding greater accounting transparency, as a result, organisations must now take steps to better articulate, measure, and manage their intangible assets, by highlighting that what companies were once able to depreciate over a longer period of time they frequently must get rid of at one time under the new accounting strictures (Petrash 2002).
In Switzerland, organisations, which want to become approved for the Swiss (Stock) Exchanges’ (SWX) Main-Segment need to strictly follow the IAS (International Accounting Standards) or US-GAAP (United States Generally Accepted Accounting Principles). In this context, the revised IAS-38 standard as well as the IFRS-5 (International Financial Reporting Standards) standard target the accounting rules in accordance with the organisation’s intangible assets. However, companies that want to become approved for the SWX’s Local Caps need to keep their books by following the FER (Fachempfehlungen zur Rechnungslegung) also known as the Swiss GAAP FER accounting standards. These standards represent the minimum rules for companies, which are quoted on the SWX. Hence, Swiss organisations must also guarantee greater accounting transparency and take further steps to better measure and manage their intangible assets.
Generally, ICM practices appear to be more concerned with the ‘MEASUREMENT’ of intangible assets as opposed to a more ‘MANAGEMENT’ oriented approach. It can also be argued that these kinds of practices relate strongly to the ‘implicit’ dimension of knowledge oriented assets as opposed to the ‘explicit’ dimension.
The first attempt to measure intangible assets relies on the various initiatives of the OECD (Organisation for Economic Cooperation and Development). By recognising a gap in reporting intellectual capital, which led to the misallocation of resources in capital markets, OECD’s main constraint was the inability of organisations to identify and measure intangible assets (OECD 1996, 1997a, 1997b, 1999).
Also the European Commission (EC) introduced comparable methodologies, which were especially promoted in their member countries (EC 1995; Meritum 2002). Both the OECD and the EC proposed new intellectual capital reporting frameworks to overcome the uncovered gap in financial reporting.
A good and ‘operationalised’ example to confront this gap is the well known and still well established Intellectual Capital Navigator (ICN) of Skandia, a Swedish financial services company. Generally, the tool supports many of Sveiby’s (1986, 1987, 1989) ideas and has been developed at Skandia between 1985 and 1994 and implemented for the first time in 1994 under the lead of Leif Edvinsson when Skandia’s first annual report with inclusion of intellectual capital indicators was published.
By representing an intellectual capital value measurement system, such monitoring-tools can be used to measure various intellectual capital bounded factors (Bontis 1998, 2001, 2002; Petrash 2002; Sullivan 2000; Wiig 1997) describing the organisation’s most valuable intangible assets and as an indicator to navigate the company’s resource-based strategic orientation (Bukh et al. 2002; Kaplan and Norton 1996).
However, here Edvinsson and Malone (1997, p. 209) point out that the goal of such applications is to identify those intangible factors off the traditional balance sheet, measure them, and present them in a coherent way. In other words, it can be seen as a model for measuring, visualising and reporting intellectual capital. As mentioned above, such practices delineate a prerequisite for more effectively conducting organisational knowledge management (OKM), an orientation that is discussed below.



O
rganisational Knowledge Management

The origins of the organisational knowledge management (OKM) theory appear more opaque. Generally, the first meaningful publications in the early 1990s regarded the management of knowledge more from a system-oriented perspective as opposed to the complementary human-oriented view and were particularly inspired by the Internet bubble.
According to Wiig (1997) the main objective of OKM is to maximise the organisation’s knowledge related effectiveness and returns from its knowledge-assets to renew them continuously. Although coming from a different angle (namely intellectual capital management), in this context Sveiby (1997) prefers to define organisational knowledge management (OKM) as ‘The Art of Creating Value from Intangible Assets’ (the word ‘value’ representing both financial and non-financial assets).
As took place in the ICM field, it seems that much of the OKM related theory was also influenced by various Japanese contributions which date back to the work of Nonaka and Takeuchi (1995) and Takeuchi’s (1998) work, which serves particularly as a warning to Western managers, who have jumped on the KM bandwagon in the mid 1990s. However, Takeuchi recognised that Europe has an edge on ‘measuring’ knowledge (ICM focus) and the US on ‘managing’ it (OKM focus).
Furthermore Takeuchi (1998) explains two kinds of knowledge, ‘tacit’ (meaning ‘implicit’) and ‘explicit’, and admits that although he has made a clear distinction between these two kinds of knowledge; they are not totally separate, but ‘mutually complementary’. Takeuchi’s main argument goes back to what he had elaborated three years before while co-authoring the book ‘The Knowledge Creating Company’ with Nonaka (Nonaka and Takeuchi, 1995), that it is all about knowledge ‘creation’ and not knowledge ‘management’, by arguing that knowledge can only be created and not managed.
Two widely recognised practitioners who contributed much in the area of managing knowledge-assets are Davenport and Prusak. Probably their most valuable contribution came with the book ‘Working Knowledge – How Organizations Manage What They Know’ (1998), where they explain the various elements of what knowledge is, and where it typically resides in organisations, by drawing on the importance of the codification of knowledge-objects (transferring implicit knowledge into explicit knowledge).
In their study ‘What’s Your Strategy for Managing Knowledge?’ Hansen et al. (1999) examined the system- versus the human-oriented knowledge management divide by investigating the practices of major consulting firms. Their own denomination for knowledge-object oriented strategies is ‘codification’, meaning the codification of implicit knowledge into information systems for transferring knowledge-assets into an explicit format. Their term ‘personalisation’, on the other hand, represents the implicit knowledge-oriented strategy, where the people-to-people knowledge transfer or exchange (i.e. collaboration) is emphasised (Hansen and Nohria, 2004). The academics found that the firms of their study sample were generally focusing on one of the two strategies and using the other in a supporting role, and that they did not try to use both approaches to an equal degree. The academics also found that by isolating KM in functional departments like HR or IT there is the risk of losing its real benefits.
Interestingly von Krogh, Ichijo, and Nonaka’s (2000) definition of knowledge ‘knowledge is justified true belief’ is the same as the one previously used by Sveiby in the mid 1980s and early 1990s, going back to Michael Polanyi’s original work of the late 1950s and mid 1960s. von Krogh et al. (2000) argue that while one may be able to manage related organisational ‘processes’ like community building and knowledge exchange, one cannot manage knowledge itself.  However, they complain that in many organisations a legitimate interest in knowledge-creation processes has been reduced to an over-emphasis on information systems (seeing and handling knowledge as an object) or measurement tools for intangible assets (ICM).
OKM builds on what organisations perceive and define as the strategically most valuable factors of the intellectual capital building-blocks (external structure, internal structure, employee competence) as put forward by various scholars (Itami 1987; Edvinsson and Malone 1997; Lev and Schwartz 1971, 1972, Lev 2000; Lev and Zambon 2003; Stewart 1991; Sveiby 1986, 1987, 1989).
OKM practices appear to relate simultaneously to both dimensions, the ‘MEASUREMENT’ and ‘MANAGEMENT’ of knowledge-assets and thus represent a mix of various strategic directions an organisation can choose to assure that the company remains competitive in its relating market place.
It also relates simultaneously to both kinds of knowledge, ‘implicit’ and ‘explicit’ (Itami 1987; Hansen et al. 1999; Nonaka 1994; Nonaka and Takeuchi 1995; Takeuchi 1998; von Krogh et al. 2000).
However, it is the process of creating new (domain) knowledge and transferring implicit knowledge into explicit knowledge (and vice-versa) through the application of specific learning methods, which is the main focus of the organisational learning management (OLM) concept, an orientation that is discussed below.



Organisational Learning Management

The first meaningful publications in this field appear to be ‘Learning Organization: Theory in Practice (1974)’ and ‘Organizational Learning: A Theory in Action Perspective (1978)’, by the two American academics Argyris and Schön back in the mid to the late 1970s. The researchers identified the following six alternative meanings of the term organisational learning: social psychology, sociology, anthropology, political theory, management theory, and information theory.
Based on the respective OLM literature, this theory provides various approaches for different levels of understanding (i.e. individual learning, group learning, organisational or corporate learning). It is exactly these different understandings that make this conceptual perspective difficult to investigate.
In this context, Hedberg (1981, p. 6) states that although organisational learning occurs through individuals, it would be a mistake to conclude that organisational learning is nothing but the cumulative result of their members’ learning. He argues that organisations do not have brains, but they have cognitive systems and memories, and as individuals develop their personalities, personal habits, and beliefs over time, organisations develop world views and ideologies. He observed that members come and go, and leadership changes but organisations’ memories preserve certain behaviours, mental maps, norms, and values over time.
Additionally, Fiol argues that although individual learning is important to organisations, organisational learning is not simply the sum of each member’s learning and that organisations, unlike individuals, develop and maintain learning systems, which not only influence their immediate members, but are then transmitted to others by way of organisation histories and norms. However, for her, organisational learning means ‘the process of improving actions through better knowledge and understanding’ (Fiol 1985, p. 803-804).
It is this ‘better knowledge and understanding’ that Hamel and Prahalad (1990) defined as the corporation’s core competence, by describing core competencies as the accumulated knowledge and skills from various groups of employees (North, 1999).
It seems that the learning organisation has become a powerful metaphor for inspiring individuals and organisations to transform their activities, and as Levitt and March (1988) suggest, although they recognised that companies mostly change through a sequence of small learning steps, in order to be effective, the design of learning organisations must value the extent to which the comprehension of its historical happenings may involve abrupt rather than incremental changes. According to Argyris (1999) there is a focus on learning as part of a continuous process rather than a series of discreet events. Based on his investigations, the reference to continuous transformation points to the need for ‘double-loop-learning’, referring to an organisation's ability to adapt and change the assumptions, values and beliefs that underlie its structure and culture. However, much of Argyris’ work has been to explore how organisations can ‘increase their capacity’ for double-loop-learning, by arguing that double-loop-learning is necessary if organisations are to make informed decisions in rapidly changing and often uncertain contexts (Argyris 1974, 1982, 1990).
In this context, Nonaka and Takeuchi (although focusing more on OKM) suggest that double-loop-learning (often seen as the key to radical innovation and learning because of its questioning of underlying operating assumptions) is not particularly difficult and indeed becomes routine. They argue further that seen from an organisational knowledge ‘creation’ perspective; double-loop learning is not a difficult task but a daily activity for the organisation (Nonaka and Takeuchi 1995, p. 46, cited in Pedler 2002, p. 524).
Hence, as a holistic means of implementing effective organisational learning management (OLM) practices, an integrated action learning approach is an ideal tool for individual, group, and organisational development. From an OLM perspective action learning can also be used effectively at the three levels of policy, strategy, and operations (Garratt, 1991, p.43-44). In this context, Revans (1969, cited in Pedler 2002, p. 525) argues that the purpose of action learning is not just to promote local action and learning, but to bring about organisational change, as in the enterprise as a learning system (1969). Stemming from an empiricist paradigm tradition, action learning also draws on phenomenological and existential notions about being in and acting on the world, in which ideas are of low value unless they are used to change things (Revans 1998, cited in Pedler 2002, p. 525).
In this context, Edmondson and Moingeon (1998, p. 160) argue that the underlying theory is that the reasoning processes employed by individuals in organisations inhibit the exchange of relevant information in ways that make double-loop learning difficult – and all but impossible in situations in which much is at stake. In their opinion, this creates a dilemma, as these are the very organisational situations in which double-loop-learning is most needed.
Furthermore, by taking the view of the organisation as a learning system Senge contributed meaningful new insights. In his highly cited publication ‘The Fifth Discipline’ (1990) he argues that the organisations that will truly excel in the future will be the ones that discover how to tap people's commitment and capacity to learn at all levels within an organisation. Senge believes that the following ‘five component technologies’ are converging to create learning organisations: 

  • 1. Personal Master: This goes beyond competence and skills (Hamel and Prahalad 1990) and refers to people who are continually expanding their ability to create the results in their life they truly seek.
  • 2. Shared Vision: This creates a shared sense of purpose that permeates the organisation and gives coherence to diverse activities. He contrasts a shared vision with a top down ‘vision statement’ that is unlikely to gain commitment from staff.
  • 3. Team Learning: He argues that teams, as well as individuals, are important learning units in modern organisations. He distinguishes between ‘discussion’ and ‘dialogue’. Discussion is concerned with specific solutions to particular problems, whilst dialogue is used to explore current assumptions and paradigms.
  • 4. Mental Models: Represents the process of testing and refining the assumptions and theories that guide action.
  • 5. Systems Thinking: Seeing the ‘big picture’ which involves understanding complex interrelationships rather than linear cause-effect chains and seeing processes of change rather than snapshots.

Furthermore, Huber (1991) has also contributed to a more knowledge and information ‘life cycle’ oriented understanding of organisational learning, by presenting four constructs integrally linked to organisational learning (knowledge acquisition, information distribution, information interpretation, organisational memory). Based on his findings, Huber (1991, p. 88) argues that much has been learned about learning from experience, but also that there is a lack of cumulative work and a lack of integration of work from different groups of scholars. Furthermore, as Dodgson (1993, p. 335) puts it, while the various literatures are revealing in particular aspects of organisational learning, a more complete understanding of its complexity requires a multi-disciplinary approach.
In his work ‘Disciplines of Organizational Learning: Contributions and Critiques’, Easterby-Smith (1997) argues against most scholars’ attempts to create a single framework for understanding and explaining the management of organisational learning. By reviewing the most meaningful literature in the field he identified the following six disciplinary perspectives: psychology and organisational development, sociology, management science, strategy, production management, as well as cultural anthropology. Then, he points out that each of these disciplines provides distinct contributions and conceptions of particular practical problems, by suggesting that whereas organisational learning is discipline-based and analytical, the learning organisation is multidisciplinary and emphasises action and the creation of an ‘ideal-type’ of organisation. Hence, due to the diversity of perspectives, Easterby-Smith suggests that it might be more appropriate to consider organisational learning as a multidisciplinary field.
In a 2003 article of Easterby-Smith and Lyles (2003) where they re-read one of Argyris’ first books ‘Organizational Learning’ (1978) for the purpose of studying the impact of his work to the academic community the researchers suggest that the emphasis on systems theory and the degree of integration of the concepts mean that acceptance of any part should imply a commitment to the wider way of thinking, by arguing that those who do not make this commitment are easily accused of being defensive and unwilling to accept external challenge (2003). However, they add that above discussion appears to be a game that many contributors have chosen not to play, and hence the majority of academics who have used Argyris (and Schön’s) work have chosen to select the theories and concepts that fit best with their own purposes.
Furthermore, the review of the most meaningful contributions in the field of organisational learning highlights the difficulties of organisational learning management as a discipline with its many facets and theoretical orientations. The literature clearly suggests that further research of this field should better concentrate on the integration of the various frameworks, which were developed since the mid 1970s to enable practitioners to better understand the phenomenon and to implement more effective OLM practices.
Although ‘learning’ in the sense used in this study relates only to the intra-corporate context, it encompasses both (knowledge) processes and outcomes, leading to new knowledge. As Dodgson (1993) suggests, ‘learning’ can be described as the ways organisations build, supplement and organise knowledge and routines around their activities and within their cultures, and adapt and develop organisational efficiency by improving the use of the broad skills of their workforces.
Based on the review of the respective literature it can be perceived that organisational knowledge management (OKM) strategies inform organisational learning management (OLM) initiatives about ‘what’ organisational learning practices to implement. Hence, OKM is more concerned with the definition of the ‘methodology’ perspective and, consequently, it can be argued that organisational learning management (OLM) is more concerned with the concrete ‘procedures, methods, and techniques’ to implement new or refined KM practices and thus supports a change of strategic management direction (Argyris 1982, 1990; Argyris and Schön 1978). In other words, organisational knowledge management (OKM) elaborates more the knowing ‘WHAT’ to do in the context of following a new or revised and resource-based strategic management orientation to gain competitive advantage, as opposed to organisational learning management (OLM), which refers more to the knowing ‘HOW’ to do the things concretely, by the use of appropriate learning procedures, learning methods, or learning techniques (e.g. action-learning) towards an effective and efficient learning organisation (Edmondson and Moingeon 1998; Garratt 1991; Pedler 2002; Probst and Büchel 1998; Revans 1969).
Organisational learning management (OLM) is also more concerned on the ‘MANAGEMENT’ dimension of knowledge by offering appropriate procedures, methods, or techniques for facilitating organisational learning, and following an inductive strategic management approach (from individual- to group- to organisational-learning), towards an implementation of specific organisational learning practices (Trillitzsch 2004).
However, organisations that purposefully construct new strategies and structures so as to enhance organisational learning have been designated as ‘Learning Organisations’ (Dodgson 1993, p. 377).