Intellectual capital and knowledge have been explored and pursued along varied dimensions particularly from the early ‘90s, when the world saw a sudden surge towards recognition of these resources as valuable, intangible assets. However, knowledge and its management were still thought to be focused primarily on artificial intelligence, databases and corporate intranets.
Lately, there has been a growing inclination towards both its technological as well as the social connotations. This has led to the treatment of the management of knowledge in a more ‘systemic’ fashion, rather than considering it an isolated and discrete constituent of managing intangible assets.
This paper explores the ‘systems’ concept and looks at the dynamic interactions between all types of organisational assets: financial, tangible, and intangible. Following the definition of systems, the concepts of their wholeness and synergetic effects are discussed. Major types and classes of systems are then identified, followed by a detailed discussion of the key characteristics of the ‘social-systemic organisation’, as well as systems thinking and practice in organisations.
Knowledge and its management being the focus of this study, a model based on systems thinking and practice in organisations is developed and elucidated. This model endeavours to include the social as well as technological implications along with the subsystems, parts, and elements of the entire organisational system which have to be considered in an attempt to effectively manage knowledge in a more holistic manner, rather than treating it as a secluded and disconnected function. Prior to conclusion, the model is further exemplified by a practical illustration using an organisation that employs such a model to manage its intangible assets.
During the late 1980s and particularly in the 1990s, the entire business environment underwent radical changes resulting in sweeping effects on the way organizations operated globally. This was fuelled primarily by increasing customer knowledge and market awareness, thereby leading to an increased demand for high quality, value-for-money goods and services. Resultantly, businesses engaged in relentless and intense competition on a global scale. This was augmented by rapid technological advancements, increased customer focus, aggressive marketing strategies, and global expansion.
Organisations underwent major transformation in terms of re-engineering production and design methods, as well as restructuring and ‘flattening’ management styles by eliminating layers of hierarchies and encouraging decentralization and emphasizing greater teamwork.
Furthered by employees becoming progressively skilled and being able to work better than their immediate bosses, the socio-economic environment in organisations became increasingly turbulent, thus resulting in greater de-centralized control. The mechanistic concept of management, argues Ackoff (1999A:23), changed focus from ‘command and control’ to managing employee interactions, and not their actions alone; as well as to administer the interactions of the unit they manage with other internal and external organisational units and organisations.
As the marketplace grew, it became inevitably competitive. This, in turn gave rise to the unprecedented value of the wealth of information and knowledge. During these past 50 years, argues De Geus (1999:32), the world of business shifted from one dominated by capital to one dominated by knowledge: thus leading to the rise of asset-poor, brain-rich companies. He argues that the critical production factor, then shifted from capital to people. Knowledge, according to him, has eventually ‘displaced capital as the scarce production factor – the key to corporate survival and success’.
Economists have attributed this transformation to the shift in the global economic infrastructure: from a labour-intensive and manufacturing-based economy, to one that is knowledge-driven, from the industrial era to the information and knowledge age. The result: a global marketplace in which information, knowledge, and services act as the key drivers for economic viability and growth. The instant dissemination of these vital entities has been made possible by rapid advancements in the communications and information technologies.
The concept of systems dates back to the days of Aristotle and Plato. Ackoff even boldly claimed as far back as 1974 that we are living in ‘the Systems Age’, while Bertalanffy wrote in 1968 that the systems theory ‘heralds a new world-view of considerable impact’ (Ackoff, 1974, and Bertalanffy, 1968, cited by Checkland, 2000)
Systems have been described by various authors in an assortment of contexts. In an earlier essay on systems, Ackoff and Emery (1972), define a system as a ‘set of interrelated elements, each of which is related directly or indirectly to every other element, and no subset of which is unrelated to any other subset’. They deduce from the above, two points that are core to the definition:
(a) A system is an entity composed of at least two elements, and a relation that holds between each of its elements and at least one other element in the set.
(b) The elements form a completely connected set, which is not decomposable into unrelated sets.
From the second point we can infer that although a system may itself be part of a larger system, it cannot be decomposed into independent subsystems: each subsystem, part, and/or element in not independent of one another but they all form a set that is bonded by the interrelatedness of the parts of the system.
In light of the above, we can arrive at a summarized and simplified definition of a system:
‘A system is a whole, that consists of necessary but insufficient, interrelated parts or subsets having one or more defining properties or functions, and which cannot be sub-divided further into autonomous subsets, parts, or elements without loss of its defining function’
The concept of wholeness plays a pivotal role in systems thinking. While defining systems, when we talk about the interrelated parts of a system that comprise elements which cannot be decomposed into separate unrelated sets, it becomes evident that systems in themselves are actually ‘wholes’ and have to be viewed as such. Failing this, if we deem systems to be otherwise, the interrelatedness between the parts fails to hold true, which renders it void for such entities to be considered as systems.
Fuenmayor (1991:229) refers to this as a ‘pragmatically intended systems approach’ to systems thinking and argues that ‘in such a context the intuition of wholeness means that changes impinging upon the parts could have an overall affect very different from that which they have on the parts by themselves.
Plato, in the fourth century BC expressed this notion as: ‘You ought not to cure the eyes without the head, or the head without the body, so neither ought you to attempt to cure the body without the soul; and this is the reason why the cure of many diseases is unknown to the physicians of Hellas, because they are ignorant of the whole, which ought to be studied also; for the part can never be well unless the whole is well’ (Plato, 1954:13, cited by Fuenmayor, 1991:229).
Smuts, in 1926 (cited by Checkland, 2000) claims that ‘Holism is the inner driving force behind (evolutionary) progress: ‘every organism, every plant or animal, is a whole with a certain internal organisation and a measure of self-direction. Not only are plants and animals wholes but in a certain limited sense the natural collocations of matter in the universe are wholes; atoms, molecules and chemical compounds are limited wholes…A whole is a synthesis or unity of parts, so close that it affects the activities and interactions of those parts….The parts are not lost or destroyed in the new structure…their independent functions and activities are grouped, related, correlated and unified in the structural whole’.
Peter Senge in his groundbreaking book, ‘The Fifth Discipline’, asserts that in order to solve problems, we tend to break them apart into smaller fragments, while this may make complex tasks and subjects more manageable, we pay an enormous, hidden price: ‘we lose our intrinsic sense of connection to the larger whole’.
The whole or the system, according to him, is ‘bound by invisible fabrics of interrelated actions, and can be understood only by contemplating the whole and not just any individual part of the pattern’.
Arguing the case of the vitality of looking at problems systemically, Senge (1990:127) presents the metaphor of having the ability of the ‘art of seeing the forest and the trees’, the ability to ‘step back’ far enough from the details to ‘see the forest for the trees’. ‘But unfortunately’, he says, ‘for most of us when we step back, we simply see just a lot of trees. We pick our favourite one or two and focus our attention and efforts for the change of just those’. While we may think that, we have been able to solve the problem, by ‘curing’ just that single part, the actual reality may be different, as, going back to Plato: ‘the part can never be well unless the whole is well.’
When the parts of a system perform their intended functions, they produce a powerful and multiplicative effect that is greater than the simple sum of the functions of the parts taken individually. The resulting synergy makes us understand why we have to consider systems in a more holistic fashion.
Laszlo (1972:36) has especially pointed out the synergetic effect that the idea of wholeness brings about in systems thinking: ‘the concept of wholeness defines the character of the system as such, in contrast to the character of its parts in isolation. A whole possesses such characteristics that are not possessed by its parts singly; the whole is therefore, other than the simple sum of its parts.
In other words, if we sum up (Vs ) individual parts va, vb, vc, …vn of a system S, then the sum of the constituents, ∑ will not be actually equal to the simple sum of these parts as shown below:
S [Vs ≠ ∑ (va + vb + vc + … vn)]
Instead, the effect produced by the synergetic whole will be greater than the mere summation of the individual parts.
S [Vs > ∑ (va + vb + vc + … vn)]
We will now have a detailed examination of the characteristics, and the conditions to be satisfied before any entity can be recognised as a system. Summarised below are such five stipulations that Ackoff (1999A:59), puts forth. He describes a ‘system’ as a whole consisting of two or more parts that satisfies the following five conditions:
¨ Each part in the set can affect the behaviour or properties of the whole.
¨ There is a subset of parts that is sufficient in one or more environments for carrying out the defining function of the whole; each of these parts is necessary but insufficient for carrying out this defining function.
¨ The way that each essential part of a system affects its behaviour or properties depends on (the behaviour or properties of) at least one other essential part of the system.
¨ The effect of any subset of essential parts on the system as a whole depends on the behaviour of at least one other such subset.
Systems in general can be classified in diverse terms such as those of size, location, functions, and discipline e.t.c. Patching (1990) maintains that precise classification is difficult ‘as certain types of systems overlap, depending very much on individual interpretation and point of view’. Wilson, according to him, proposes four major classes: natural, designed, social & cultural, and human activity systems.
Alternatively, Boulding’s (1956) hierarchy of systems (Hatch, 1997 and Checkland, 2000) encompasses nine levels ranked in order of complexity: frameworks or structures, clockworks, control mechanisms, open (living) systems, genetic (lower organisms), animals, humans, social organisations or socio-cultural systems, and finally, transcendental.
Checkland (2000) draws attention to another attempt regarding construction of a systems taxonomy: the Jordan’s (1968) classification of systems. Jordan’s classification instigates from perceptive deduction of three ‘organising principles’ that may enable us to perceive a group of entities as ‘a system’. These principles are rate of change, purpose, and connectivity. Each of these principles in turn, defines a pair of systems properties which are totally opposite to each other. Rate of change leads to the properties ‘structural’ (static) and ‘functional’ (dynamic); purpose leads to ‘purposive’ and ‘non-purposive’; and the connectivity principle leads to such groupings that are either ‘densely connected’ (organismic) or ‘not densely connected’ (mechanistic or mechanical).
Originating from these three principles are eight ways of selecting one from each of the three pairs of properties, giving rise to eight ‘cells’ which are potential descriptions of groupings worthy of the name ‘system’, e.g. structural/purposive/mechanical, functional/non-purposive/organismic, etc. (Checkland, 2000).
Figure 1: Dimension-based taxonomy of systems (after Jordan, 1968)
Ackoff (1999B) however contends on such classification that is based on the basis of one critical classifying variable: purpose.
According to this classification criterion, the parts of a system and the system as a whole are determined as to if they are purposeful or not. Based on this paradigm, he puts forth the following four different types of systems and models:
¨ Deterministic: such systems that, as systems (as a whole), as well as their parts, have no purpose of their own are classified as deterministic. They are generally mechanical in nature; examples include automobiles, clocks and motors.
¨ Animated: those systems and models which are purposeful as a whole but their parts are not (taken individually). Living organisms, plants and animals, including humans are examples of this category of systems. A human being has a purpose of existence in its wholeness, taken together, but individual parts (organs) of the human body have no existence or purpose.
¨ Social: both the parts, considered separately, and the system as a whole have a purpose. Corporations, organisations and universities are examples of this type and model.
¨ Ecological: opposed to animated systems, ecological systems contain some parts which are purposeful taken individually, but viewed in their entirety and wholeness; have no purpose of their own. Nature, for instance, comprises interacting and purposeful parts such as mechanistic, social, and organismic systems, but it has no purpose of its own, taken individually as an entire, whole system.
Regardless of which method of classification we consider, what is actually most significant is how the individual perceives the system, and his purpose. Going back to Patching (1990), ‘classification depends primarily on individual interpretation and point of view’.
Given the limitation and the scope of this study, we will restrict our discussion exclusively to those systems in which the parts, considered independently, as well as their sum: the whole, have a purpose: social systems.
Prior to discussing the concept of systems thinking in organisations, we will first look at what is meant by an organisation in systems terms. An organisation, describes Gaus, (Selznick, 1948) is ‘the arrangement of personnel for facilitating the accomplishment of some agreed purpose through the allocation of functions and responsibilities’. These functions and responsibilities, which Gaus evokes, are accomplished by employing three critical elements: procedures, processes, and people.
Procedures ‘enable the coordination required to achieve a coherent organisational identity or to ensure that services are consistent across units’ (Hatch 1997:32). The systematic application of such procedures (what) facilitates decision-making in order to execute work processes (how), by drawing on available resources: people (human resources), for instance.
These functions and responsibilities have to be allocated to personnel through some departments, divisions, or parts within the organisation, in order to facilitate the ‘accomplishment of some agreed purpose’ described by Gaus, or what Ackoff (1999A), calls the ‘defining function’ of the organisation.
In order to attain this defining function, the technical and managerial skills on hand have to be mobilized, which in turn require a pattern of coordination, a systematic ordering of positions and duties which defines a chain of command and makes possible the administrative integration of specialized functions (Selznick, 1948). Barnard (Selznick, 1948:301) proposes a more generalized, and a ‘system oriented’ definition of an organisation as being ‘a system of consciously coordinated activities or forces of two or more persons.
Systems thinking, on the other hand has its foundations in the field of system dynamics, originally founded by MIT professor Jay Forrester in 1956, as he recognized the need for a better way of testing new ideas about social systems, in the same way we can test ideas in engineering.
Aronson (1998) contends that the approach of systems thinking is fundamentally different from that of traditional forms of analysis. According to him, whereas the word ‘analysis’ means ‘to break into constituent parts’, systems thinking, in contrast, ‘focuses on how the thing being studied interacts with the other constituents of the system – a set of elements that interact to produce behaviour – of which it is a part.’ The fundamental concept of this approach makes it look at the picture in its wholeness, rather than considering each broken part as an independent, separate and isolated entity.
As organisations today become increasingly complex with several departments performing highly specialized and differentiated functions, the management, in an attempt to address problems that arise, not only fails to step back and look at the issues, in their entirety, but often makes poor decisions by considering each occurring problem as isolated and disintegrated from the other.
Senge (1990) describes systems thinking as a ‘conceptual framework, a body of knowledge and tools that has been developed to make the patterns clearer and to help us see how to change them effectively’.
‘Systemic thinking’ (Peters & Beishon, 1981:14), taken loosely, looks at situations, topics, problems, etc., as a complex of interacting parts which can be divided into specific systems and within these, subsystems, and if necessary, into sub-subsystems, and so on. Once these various constituent systems and sub-systems are identified, the relationships between these are examined. These may be the flows of influences, materials, energy, other resources, and the routes these adopt both among and within the system in a given environment (ibid).
Although interaction between the parts of a system has been emphasised throughout this section, as a key element in recognition of a system as ‘systemic’, what has to be appreciated, however, asserts Ackoff (1999A:19), is the quality of the interaction of the parts and not just the mere interaction of the parts: ‘The performance of a system depends more on how its parts interact than on how they act independently of each other.’
High-quality organisational interaction between the parts, both within and outside the concerned organisation leads to such an organisational environment that is highly conducive to the systematic execution of business procedures and processes, which leads to the realisation of organisational objectives, the ‘defining function’ (Ackoff 1999A), or the ‘accomplishment of some agreed purpose’ (Selznick, 1948:301).
Social systems encompass social concerns such as organisations, corporations, universities, and societies. These systems may be part of larger social systems that comprise other social systems. Examples include large corporations and nations (Ackoff, 1999B).
Such systems are composed of parts that work together in individual capacities to achieve the ‘defining function’ of the system as whole. A manufacturing company may be composed of ‘parts’ such as the production, manufacturing, administration, human resources, operations, and finance departments. Each part (department) of the system (company) works individually and therefore serves the purpose of attaining the defining function.
The essential parts of the system can affect the performance of the system as a whole, but cannot do so autonomously and independently of all other essential parts working in the same system. While attempting to improve productivity or efficiency of an essential part, its effect on the system as a whole should not be overlooked. This will correspond to the degree and nature of the affect and behaviour the part in question has on the functioning of the system.
The parts, therefore taken and deemed to have a systemic influence on the functioning of the system as a whole to realize the defining function is core to social-systemic models of organisations.
While tracing the events leading to social-systemic modelling in present-day organisations, Ackoff contemplates that after World War II, the corporate world saw a momentous transformation in the way organisations operated globally. Apart from the ‘hard elements’ such as production techniques and methods that contributed towards such change, the management’s social responsibility and work-related ethics emerged as major concerns.
Ackoff puts forth a model of the social systemic organisation, by ascribing certain features to such types of set-ups. These characteristics, suggested by him, have been summarised below.
Such organisations are democratic in nature, since everyone affected by the decisions made has a say, and everyone in authority is accountable to others collectively. This means that no one has the ‘ultimate authority’ over others in the organisation.
The parts of the system (organisation) can sell or purchase both goods and services from any internal or external sources to meet their requirements. Higher-level intervention may be made use of, in order to compensate the affected part of the system in case of increased costs or lost income.
The structure of the organisation has units of three different types located at each level of the organisation. These are defined by (a) their function (such units whose output is primarily consumed internally), (b) their output (external consumption of products and services), (c) their users (the markets: defined by the type and location of customers).
Interactive planning makes use of idealized re-design of the organisation and the closest approximation to that design. Such planning then passes through the following steps: selection of the requisite means, provision of the required resources, determining the steps to its implementation, and finally design of the monitoring, evaluation, and control of the initially designed plan.
The social-systemic organisation contains a decision support system that facilitates learning and adaptation by (a) recording the expectations associated with each significance, (b) the assumptions and information on which they are based, and (c) the process by which the decision is arrived at and by whom it was reached.
The system subsequently monitors the implementation, original assumptions, and effects of every decision; rectifies where the decisions are incorrect or fall below desired expectations and retains in an easily accessible memory what has been learned. It also detects and identifies any changes that have occurred or are about to occur that necessitate adaptation by the organisation.
Asserting the influence and power of these key characteristics, Ackoff contends that any one or a subset of these changes can improve organisational performance significantly. Better still, when all are made together, there is powerful and multiplicative effect. This notion instigates the derivation of ‘systemic thinking’: the synergetic effect of the whole being greater than the simple sum of its parts.
To begin with, an established model for Knowledge Management will be discussed, on the basis of which a model of a ‘generic dynamic systemic knowledge management system’ will be developed by integrating the theoretical implications of systems, systems thinking, the systemic organisation and system dynamics developed so far.
Knowledge management is a complex area, and one that spans boundaries – learning and development, information technology, and human resources. Having a model that describes the scope of activity that the knowledge management efforts cover can be a powerful monitor and communicate what an organisation’s approach encompasses (Collison and Parcell, 2001).
The model that will be employed here is one which Collison and Parcell present. This model attributes successful knowledge management to the interaction between three fundamental elements:
¨ People: knowledge roots from people; they form the basis for newly created knowledge. Without people, there will be no knowledge.
¨ Technology: a standardized and consistent reliable technological infrastructure that is able to support the appropriate tools on an organisation-wide scale.
¨ Processes: the capture, distillation, validation, transfer, and dissemination of knowledge throughout the organisation are completed by applying certain processes and procedures.
All three elements are not only necessary, but also complementary to one another, since knowledge management is such an area, where all three elements overlap as exhibited in Figure 2 below.
[Adapted from Collison & Parcell (2001; pp. 18)]
This model is based on a framework that has been developed by the authors in an attempt to demonstrate the activities that go into managing knowledge. The knowledge life cycle, put forth and described by the authors, explains how created and codified knowledge is actually made practically useful: by embedding it into business processes and activities.
As illustrated below in Figure 3, the cycle passes through the following steps:
[Adapted from Collison & Parcell (2001; pp. 19)]
It is worth noting that communities of practice play a central role in the framework. These can be loosely expressed as ‘such groups that learn’. They are not formed deliberately or in a structured manner. Instead, they arise out of certain individuals; drawn and attracted towards one another, and bound by a force that is ‘both social and professional’ (Stewart, 1998). They have common problems, and are in a constant and common pursuit of solutions. Communities of practice contribute in two major ways to the formation of human capital: knowledge transfer and innovation.
The model itself is centred on one fundamental process: Learning. The authors assert that the learning process spans over the entire knowledge management function.
In a learning organisation, every individual learns: employees stretch, grow, nurture, develop, and enhance their skills and capabilities to create and innovate. People learn to take risks while developing and experimenting new ideas. They are invited to learn what is going on at every level of the organisation. This promotes further learning through feedback as to how their individual contributions make a difference to the organisation as a whole and how they can further the shared cause.
Communication occupies a significant place in a learning organisation. Employees at all levels feel free to inquire about one another’s ideas, notions, concepts, and approaches. Mutual respect, trust, empathy, and a sense of belongingness play a significant role in building a learning organisation.
Peter Senge (1990;67) brings out the importance of making team-based, joint efforts in such organisations:
‘As the world becomes more interconnected and the business becomes more complex and dynamic, work must be become more ‘learningful’. It is no longer sufficient to have one person learning for the organisation, a Ford or a Sloan or a Watson. It is just not possible any longer to ‘figure it out’ from the top, and have everyone else following the orders of the ‘grand strategist’. The organisations that will truly excel in the future will be the organisations that discover how to tap people’s commitment and capacity to learn at all levels in an organisation’.
The model on knowledge management can be seen to carry the distinctive feature of ‘learning’ embedded in its architecture. It emphasises the need of learning at every opportunity: ‘before, during and after’ everything that is done. The authors contend that learning is one of the key elements of getting business results from business objectives.
Learning, according to them, takes place along three dimensions, which they explain as follows:
Learning Before: Before commencing a new task, team members can learn from work done on similar projects since it is likely that someone has already worked on it before. Corporate intranets, the Internet, search engines, corporate-wide yellow pages, etc., all prove to be good starting points for existing knowledge. It seems reasonable to learn from such instances before actually embarking on the venture.
Learning During: If, during the course of a project, team members occasionally keep on reflecting on what they have done so far, a lot of time, effort and resources may be saved by contemplating on the progress made and measuring it against the intended design. The authors suggest initiatives such as an ‘after-action review’ (AAR), short team meetings, and setting up communities of practice, etc.
Learning After: New projects tend to create a lot of new knowledge during the process of completion. Evaluating original intended design against current outcome and reality, during post-implementation reviews and audits, enables the team members to gauge how it could have been done better, and how the newly created knowledge could be codified for future use and reference.
Figure 4: The Collison And Parcell Model For Knowledge Management
[Adapted from Collison & Parcell (2001; pp. 29)]
6.3. Knowledge Capture During The Process
The codification of tacit knowledge converts it into the explicit form, thus leading to the formation of a permanent knowledge asset of the organisation. Captured knowledge requires some context and a collection of specific experiences that are ‘distilled’ to provide the content (Collison and Parcell, 2001). When team members ‘write down’ what experience they have gained while working on a particular project, they actually facilitate building up a knowledge repository, something that anyone in the organisation can always refer back to, should the need arise.
It is worth appreciating at this stage that the knowledge management model, in concurrence with the knowledge life cycle, the right tools, the appropriate software, and the requisite infrastructure are not all that is required for managing free-flowing knowledge in organisations. Perhaps one of the most vital and significant elements is the organisational culture.
Implementing the infrastructure is much simpler as compared to reengineering the entire organisational culture with a view to developing it in such a manner that is based on shared values, trust and empowerment, continuous learning, innovation, and improvement, in a no-blame environment. Without creating the right environment: the appropriate culture, ‘one which nurtures the right behaviour and fosters a supportive company culture’ (Collison and Parcell, 2001), all efforts to manage knowledge become futile, despite there being everything else that is necessary.
The preceding two sections of this section have dealt with the development of generic business and knowledge management models. These models will now be integrated into the theory of systems thinking and systems dynamics, discussed in the foregoing section, to develop such a model of managing knowledge that takes into account the systemic facet of organisations.
Smith (1998) defines systemic knowledge management as ‘those processes, tools, and infrastructures by which an organisation continuously improves, maintains and exploits all those elements of its knowledge base (related to its financial, tangible, and intangible assets) which the organisation believes are relevant to achieving its goals. It includes the processes, tools, and the infrastructure by which these goals are modified as the organisation’s base changes’.
An important aspect to which this definition points, is the consideration of the financial, tangible, and intangible assets of organisations, which have to be considered in an attempt to ‘improve, maintain, and exploit’ the elements of which the knowledge base of organisations is built up.
Smith (1998) asserts that despite the fact that interest in addressing the potential of intangible assets has increased, concern for, and the management of financial, tangible, and intangible assets have become increasingly disconnected. He ascribes this to a sudden surge towards increased specialisation, which he contends, roots from mounting competitive pressures on both academics and varied internal and external experts.
In section 2, we saw that an organisation’s knowledge base incorporates the data, information, intuition, insight, perception, the knowledge it possesses (know how), the understanding (know why), and wisdom that resides both within the organisation, as well as in the outside parties that it transacts business with.
In an attempt to highlight the relationship that exists between financial, tangible, and intangible assets, Smith (1998) presents a Venn diagram with overlapping circles as illustrated in figure 5, whereby:
[Adapted from Smith (1998)]
He further expands on the ‘intangible asset system’ as exhibited in Figure 5 above illustrating the relationship between the three types of intangible assets. Overlapping and non-overlapping areas of the circles indicate the corresponding degree of potential available for asset mobilization and stimulation in order to capture existing opportunities.
[Adapted from Smith (1998)]
Smith contends that ‘neither Intellectual Capital nor Knowledge Management is sensitive to the dynamic complex nature of the systems with which they deal’. What matters here, according to him, are the method in which the three elements identified and illustrated in both Figures 5 and 6 can move in relation to one another, along with the speed of change and their inter-relatedness. Without this understanding, he argues, organisations are forced to run their businesses as if they were a football team which could only see the scoreboard at the end of every quarter, and had to try to win the game with no feedback on the play by play.
Keeping in view system dynamics and systems thinking in organisations, a model has been developed that takes into account the systemic facet of the management of knowledge in organisations. The model, set out in figure 7, has been explained below.
7.3. Fundamental Model Concepts
The behaviour of an organisation’s leaders, together with their vision determines the ‘organisational rationale’ as well as the intent of running the business. This creates an ambience of harmony and unison, which leads to forming an environment and a culture within which people serve to achieve company objectives.
The management, on the other hand, is responsible for chalking out the business strategies and policies of administering the organisation as a whole. Organisational culture plays a critical role in creating a learning atmosphere, which eventually proves to be highly instrumental in creating and disseminating knowledge.
The ‘enablers’, alongside other organisational procedures and practices, ultimately lead to the identification, creation, capture, adaptation, and the embedding of knowledge. These eventually lead to the formation of a knowledge repository within the organisation, for it to be drawn upon by workers, as per their individual requirements.
The intellectual capital comprising the human, structural, and the customer capitals constitutes the intangible asset base of organisations. These components are built up during the course of an assortment of activities that take place in organisations. While each class of capital belongs to a different category, all three are interrelated to one another, and cannot be seen to be disconnected or independent of each other.
The organisation’s mission and vision, as envisaged by the leadership is implemented by the management via a clearly laid down, stakeholder-focused organisational strategy. Such a strategy is sustained by employing relevant business processes, plans, policies, and practices, in order to materialise the intended organisational results and objectives.
7.3.5. Increased Financial Capability Leading To Enhanced Opportunities For Investment In Tangible And Intangible Assets, Enabling Organisational Knowledge Management Infrastructure Strengthening And Capacity Building
By employing the strategies and the policies and realising the intended results and objectives, organisations amass financial capital, thus enabling them to invest further in both tangible and intangible assets.
The SKMS Model is a framework based on the premise of ‘systemic thinking’, and the ‘systems’ theory that dictates that all parts of a system have to be taken as belonging to a ‘whole’, interacting with one another forming an indivisible entity with all parts contributing towards the realisation of the system’s ultimate specified objective, or what Ackoff calls the ‘defining function’.
The arrows emphasize the dynamic nature of the model, reflecting the interrelatedness of the system’s parts, which is core to the principles of systems thinking. They depict that all parts of the SKMS are integrated with one another to interplay collectively so as to accomplish the organisational objectives.
The model is built up of an assortment of interacting components. Business processes, learning, culture, the leadership, and management collectively make up the ‘enablers’: the processes and procedures to get things done. The creation, identification, adaptation, and embedding of knowledge build up the ‘organisational knowledge base’: the second constituent of the model.
The intangible assets, constituting the human, structural, and the customer capitals, develop as a consequence of certain activities and processes that are outlined in table 1 below:
Organisational (Structural) Capital
▪ Training & Development
▪ Learning, Sharing & Mentoring
▪ Communities of Practice
▪ Recruitment & Selection
▪ Corporate Yellow Pages
▪ Competitor Intelligence
▪ Lessons Learned
▪ Corporate Memory
▪ Information and Communication
▪ Best Practices
▪ Work Flows
▪ Customer Focus
▪ Alliances and Partnerships
▪ Goodwill and Reputation
Table 1: Constituents of Intangible Assets
The activities and processes summarized in the table above, lead to the creation of the organisational knowledge base, through the aid of ‘enablers’ (business processes, learning, culture, vision, management, and leadership) that facilitate the process of knowledge creation, identification, and adaptation.
The intended organisational results and objectives are materialized with the aid of the business strategies and policies set out by the management. Once achieved, they assist in building up the organisational financial asset base. The resulting increased financial capability leads to greater investment opportunities. Consequently, organisations are faced with the prospects of investing such amassed financial capital in both tangible and intangible assets. As a result, the organisational knowledge management infrastructure is strengthened; this is turn leads to reinforcing the enablers, which in turn enrich and supplement the existing organisational knowledge base. This goes on to aid in generating further tangible and intangible assets.
The distinctive feature of this model is the ‘cyclical characteristic’ which encompasses all tangible organisational assets alongside the capabilities that it possesses. As tangible and intangible assets are developed, the enhanced capability goes on to reinforce the enablers (business processes, management styles, etc.) which ultimately result in augmenting and deepening the existent organisational knowledge base.
Another significant attribute of the proposed model is that although it does not explicitly bring up the ‘interrelatedness’ of the parts of the system, yet it is evident by its design. The model brings out the inevitable ‘connectivity’ within and between the parts. The model shows coherence with the systems theory in terms of the parts belonging to a unified whole.
A working example of the model presented above can be demonstrated by drawing on Smith’s demonstration of the how ‘interconnections between financial, tangible, and intangible assets might be visualised generically and could be manipulated for commercial advantage through such a ‘systemic’ approach to managing knowledge’. The demonstration, presented in two phases, takes care of all three elements of intellectual capital: customer, human and structural, as well as the tangible and financial assets.
The organisation employed in the illustration can be considered to be a generic trading business concern, which utilizes essential business processes and activities such as ordering, purchasing, supplying, marketing, investing, etc.
In the first phase, exhibited in Figure 8, the SKMS takes as its inputs the vendor’s degree of satisfaction while employing measurement of factors such as:
Based on these inputs, the SKMS, argues Smith, ‘dynamically deploys the organisation’s available finances for long-term financial viability, without violation of traditional accounting practices. A model such as this, affords an appropriate balancing mechanism for strategic thinking and operational decision making with respect to the status of financial, tangible, and intangible assets’.
Figure 8: Model Development Phase 1
(Adapted from Smith, 1998)
Figure 9: Model Development Phase 2
(Adapted from Smith, 1998)
The customer capital in the SKMS, for instance, gets inputs such as one of the customer’s perceived value, which, in turn is based on the customer orders and expectation satisfied. These, sequentially depend on the vendor’s delivery capability as well as the customer’s orders and expectations satisfied. This constituent subsequently determines the revenue, which builds up the financial capital of the organisation in question. The financial capital determines the financial capability of the organisation, which itself comprises the investment made.
Looking from a practical-feasibility perspective, such models can be run conveniently on computer simulations representing a number of years’ of commercial operations. Operational parameters can be altered at intervals representing real-time elapsed months, years etc. Long-term viability of projects can therefore be easily forecasted by using such type of simulation runs. Different operational strategies can be tried out to help understand the dynamics of the situation, and to aid in real-life business scenarios, without any risk to the organisation. Smith cautions, however, that results obtained from simulation runs of models as these should not be considered as predictive, but they do offer directional and other strategic insights.
Developing the model to the next phase (Figure 9), he adds further layers of complexity in an attempt to give a practical insight to the results obtained from simulation runs.
As an instance, consider the human capital constituent of the intellectual capital of the organisation, it receives inputs from factors such as ‘training, learning, and recruitment’ which themselves are affected by the organisation’s investment in intangible assets, which in turn relies on the financial capability of the company. The investment in intangible assets results in embedding knowledge in the structural capital of the organisation. Ultimately, this results in what Smith refers to as structural renewal, thereby leading to formation of the human capital.
Looking hypothetically, this demonstration intends to prove that all elements of Intellectual Capital: customer, human and structural capital, along with the financial, tangible and the intangible assets are not in any way disconnected or isolated from one another, but instead, any single event in any asset, triggers a chain of transactions that may cause wide-ranging results to the knowledge and intellectual capital structure of the organisation. These results may not be noticeable if we cease to look at the organisation as a system composed of interrelated and connected parts, with the change in any part leading to extensive organisation-wide results.
To look at such interrelatedness, consider the transactions in the system as cyclical: one event resulting in outcomes that may influence all constituents of intellectual capital. Consider, for example, the following: the financial assets health determines the financial capability of the organisation; this leads to an investment in intangible assets that embeds knowledge in the system’s procedures, thus building the structural capital that enhances the organisational capability. This results in the customer orders and expectations being satisfied, increasing customer perceived value, thereby building up the customer capital. As the customer capital grows, it results in greater revenue, contributing towards strengthening the financial asset base of the organisation, starting the cycle all over again.
Conventional definitions of knowledge management do not take into account this facet of knowledge and its management, as they fail to recognize the interrelatedness between the parts of the system (the organisation), such as the financial capital, and other intangible and intangible assets.
A holistic outlook of all the parts of organisational systems will ensure that all parts of the system are given an equal weightage and will aid in providing a remedy to the ‘critical shortcomings of traditional IC-based approaches since they emphasise the importance of intangible assets at the expense of financial and tangible assets’ (Smith 1998).
The dynamic models presented in figures 8 and 9 are themselves testimony to the synergetic principle. Considered individually, the parts of a social system fail to conform to the systems theory and fulfil their role as contributing towards the whole, and viewed from a holistic perspective, the interacting parts create a powerful multiplicative effect, that facilitate in realizing organisational objectives.
One of the most critical shortcomings in current practices of measuring and managing intellectual capital and knowledge in organisations today is that departments are viewed as discrete and disparate entities with no connection to the larger whole. The management tends to emphasise the significance of intangible assets at the expense of the tangible ones. ‘Current procedures approach the problem ‘a-systemically’ and ignore the wholeness that has to be accounted for as well. If organisations are to be viewed from a holistic perspective, all their parts have to be considered as part of a system, rather than separate entities and factions’ (Smith, 1998). Bringing up the significance of this concept, Senge (1990:371), goes even a step further, where he advocates contemplation of systems in their entirety: ‘the earth is an indivisible whole, just as each of us is an indivisible whole. Nature (and that includes us) is not made up of parts within wholes, but wholes within wholes’.
Let us take a hypothetical organisation in which all departments are taken a-systemically. Even if each unit within the organisation is thought to be operating at its optimum capability thus yielding maximum productivity, it will not necessarily imply that the organisation as a whole is functioning as efficiently as it could have, if organisational practices and procedures were designed in such a manner that would have led to enhanced interrelatedness between all departments. The significance of the interrelatedness of the parts of a system (in this case, an organisation) has been expressed by Ackoff (1999A:49) as follows: ‘If each part of a system, considered separately, is made to operate as efficiently as possible, the system as a whole will not operate as effectively as possible’.
A Systemic Knowledge Management System takes care of this aspect and advocates management of all the parts of a system being part of a larger whole, in an endeavour to maximize efficiency and effectiveness of organisations. The distinctive feature of the proposed model is the cyclical feature which tends to encompass both tangible and intangible assets. The business practices and procedures of an organisation that employs such a model are designed in such a fashion that result in a tightly knit unified and connected whole in which the capability built by each department is made use of by all other divisions within the organisation.
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About the Author:
Asad. K. Ghalib has been associated with the banking services sector for over a decade, and currently works for The Royal Bank of Scotland, based in Manchester, U.K. He holds memberships of the British Computer Society (BCS) and the Institute for the Management of Information Systems (IMIS). E-mail: firstname.lastname@example.org; Mob: + (44) 7960-890-859