Managing the Creation, Mobilisation and Diffusion of Knowledge

It is important for managers to understand the Factors they have to focus on to increase the organisational readiness for the creation, mobilisation or diffusion of knowledge. KIAT diagnoses the organisational readiness independently for each stage of the knowledge life-cycle. Therefore, for an organisation that appears to be more prepared for knowledge creation than the other two, managers can identify the Factors to address to improve the readiness for the other two stages of the knowledge life- cycle. This clarity as to which Factors play significant roles for each stage of the knowledge life-cycle helps managers to position the organisation in a ready state to implement KMS across the stages of the knowledge life-cycle. The following discussion examines and proposes the relevant Factors leading to the readiness of the Infrastructure, Knowledge Structure and Knowledge Culture dimensions for each stage of the knowledge life-cycle.

Knowledge Creation and Socio-Technical System dimensions

Knowledge management research suggests that knowledge culture is an important condition for knowledge creation activities to take place in an organisation (von Krogh, Nonaka and Aben, 2001; De Long and Fahey, 2000; Nonaka and Konno, 1998). Un and Cuervo-Cazurra (2004) suggest that the recognition scheme, the structure of communities and the habits of knowledge workers to work in communities, and integrative communication are positively correlated with the capability to create knowledge. They suggest that the project team strategy in problem solving with knowledgeable members is positively correlated with the capability to create knowledge. Obstfeld (2002) contends that for an organisation to have a capability for knowledge creation it needs a dense network of workers who are knowledgeable and eager to share their knowledge.

Nonaka and Takeuchi (1995) claim that the role of the organisation in the organisational knowledge creation process is to provide the proper context for facilitating group activities as well as the creation and accumulation of knowledge at the individual level. They suggest five conditions are required at the organisational level to promote the knowledge spiral: Intention, Autonomy, Fluctuation and Creative Chaos, Redundancy, Requisite Variety. Intention is meant to cover the strategy of the firm that will make the workers understand what knowledge they need for the business and that the firm listens to the workers as to what knowledge needed to be pursued. With this, collective commitment is achieved. Autonomy is meant to allow workers to act autonomously. In other words, workers can control their own time at work. According to De Long and Fahey (2000) and Nonaka and Takeuchi (1995) autonomy increases the possibility that individuals will motivate themselves to create new knowledge. Fluctuation in the organisation can trigger creative chaos that

strengthens individual commitment. Fluctuation means the exposure of external conditions to the workers. In other words, working habits in communities that include external communities will enhance the knowledge creation activities. Redundancy refers to the existence of information and knowledge that goes beyond the immediate operational requirements. When there is redundancy knowledge, creation is enhanced. In other words, when the KMS addresses both the organisation and the workers’ benefits, knowledge creation activities are enhanced. Requisite Variety is meant to have communities with skill varieties. In other words, the structure of communities needs to be addressed to induce and enhance knowledge creation.

Bartlett and Ghoshal (2002) state that it is unrealistic to expect workers to exercise knowledge activities outside their work process. Knowledge activities need to be streamlined and aligned with the business processes (Davenport and Glaser, 2002; Braganza and Lambert, 2000). In their work studying the knowledge stickiness, Szulanski (1996) and von Hipple (1994) suggest that if workers feel threatened from their current position it is only natural that their knowledge and the information they possess become ‘sticky’, i.e. the knowledge is not shared. Therefore, an implementation of KMS should address the workers’ value inside the organisation if it is to bring beneficial results to the organisation. Heaton and Taylor (2002) and Wenger (2000) demonstrate how communities of practice, that is the structure of communities and the habits of people working in communities, enable the knowledge creation in an organisation.

My research indicates, as elaborated in Project Two, that a number of Factors in KIAT significantly or completely affect the Knowledge Creation (KC) stage. Those Factors are listed in Table 1-3. One Factor is of the infrastructure dimension, seven Factors are of the knowledge structure dimension, and nine Factors are of the knowledge culture dimension. The evaluation of these Factors, as explained in Project Two, reports the readiness of the Infrastructure – KC (i.e. the Infrastructure for Knowledge Creation), Knowledge Structure – KC, and Knowledge Culture – KC with a scale between one to five. A scale of five is the highest readiness state. As elaborated in Chapter Four: Project Two, I propose that a scale of three is a level where organisations have a better chance for implementing KMS. Readiness of lower than three does not, however, necessarily mean that the organisations must not proceed with the implementation. What it means is that managers have the information as to what lower-scored Factors they need to address in the effort to implement KMS for knowledge creation.

Table 1-3: Factors that significantly or completely affect the knowledge creation (KC)

This discussion leads to a conclusion, expressed as:

Proposition 3: Readiness to create knowledge increases as the measure of the Infrastructure – KC, Knowledge Structure – KC, Knowledge Culture – KC increases.

Knowledge Mobilisation and Socio-Technical System dimensions

Mobilising knowledge means validating knowledge prior to its diffusion to a larger community, and at this stage the originators share their knowledge with people who make up part of a trusted community (Birkinshaw and Sheehan, 2002). In other words, the structure of communities on which community members can build trust needs to exist in an organisation. As the objective of this stage of knowledge life-cycle is to confirm new knowledge, a validation process will need to be available (Brown and Duguid, 2000) and may be facilitated by knowledge brokers (Davenport and Prusak, 1998).

Knowledge mobilisation involves fewer people than knowledge diffusion (Birkinshaw and Sheehan, 2002). However, members of this trusted community will need to have motivation in associating themselves with others to confirm knowledge prior to diffusing it (Francis and Bessant, 2005; Birkinshaw and Sheehan, 2002). Furthermore, motivation of the ‘confirming knowledge’ community members very soon decreases if they learn that the results of their participation are in vain (De Long and Fahey, 2000).

My research indicates, as elaborated in Project Two, that a number of Factors in KIAT significantly or completely affect the Knowledge Mobilisation (KM) stage. Those Factors are listed in Table 1-4. Two Factors are of the infrastructure dimension, eleven Factors are of the knowledge structure dimension and eleven Factors of the knowledge culture dimension. The evaluation of these Factors, as explained in Project Two, reports the readiness of the Infrastructure – KM (i.e. the Infrastructure for

Infrastructure Knowledge _Structure Knowledge_Culture

Training programme that links to people

development and business needs Structure of communities

Workers who understand what they need to know to perform

Recognition scheme

Workers who are eager and positive towards becoming trained and sharing what they know

Knowledge feedback loop Problem solving Identification of important knowledge that

comes from workers Expert users Knowledge structure that addresses both the

organisation's and the workers' benefits Subject matter experts Stream-lined activities Working in communities

Enriching workers' value What Is in It For Me (WIIFM) awareness Two-way communication

Workers who control their own time

Know

Knowledge Mobilisation), Knowledge Structure – KM, and Knowledge Culture – KM with a scale between one to five. A scale of five is the highest readiness state. As elaborated in Chapter Four: Project Two, I propose that a scale of three is a level where organisations have a better chance of implementing KMS. Readiness of lower than three does not, however, necessarily mean that the organisations must not proceed with the implementation. What it means is that managers have the information as to what lower-scored Factors they need to address in an effort to implement KMS for knowledge mobilisation.

This discussion leads to a conclusion, expressed as:

Proposition 4: Readiness to mobilise knowledge increases as the measure of the Infrastructure – KM, Knowledge Structure – KM, Knowledge Culture – KM increases.

Table 1-4: Factors that significantly or completely affect the knowledge mobilisation (KM)

Knowledge Diffusion and Socio-Technical System dimensions

The enthusiasm about knowledge management, historically, has been induced by the potential Information Technology (IT) can bring to diffuse knowledge (Alavi and Leidner, 2001; Davenport and Prusak, 1998). The role of IT remains important for knowledge diffusion (Majchrzak et al., 2004; Beccerra-Fernandez et al., 2004; Pan and Leidner, 2003). Davenport and Glaser insist that an alert feature needs to be

Infrastructure Knowledge

Structure

Knowledge Culture

Direct funding to individual projects is an organisation policy

Relationship of knowledge to business activities

Workers who understand what they need to know to perform

The means to channel system feeback Ease of navigation Workers who communicate and build trust _{with a standard language}

Knowledge broker

Workers who are eager and positive towards becoming trained and sharing what they know

Structure of communities Problem solving Validation process Expert users Recognition scheme Subject matter experts Knowledge feedback loop Working in communities Structured team to promote knowledge

initiative Workers who work through metrics Knowledge structure that addresses both the

organisation's and the workers' benefits What Is in It For Me (WIIFM) awareness Stream-lined activities Two-way communication

Enriching workers' value Workers who control their own time

Know

considered to have just-in-time knowledge – “the key to success is to bake specialised knowledge into the jobs of highly skilled workers - to make the knowledge so readily accessible that it can’t be avoided” (2002:108). They further suggest that the most promising approach for knowledge diffusion is to embed it into the technology that knowledge workers use to do their jobs. In other words, knowledge activities need to be streamlined within the business processes (Ghoshal and Gratton, 2002) and that the communities adhere to the business processes (El Sawy et al., 2001). Knowledge management is supposed to help knowledge workers to perform their work and not to make it harder (Fahey and Prusak, 1998), therefore ease of use for KMS deserves a great deal of attention (Alavi and Leidner, 2001; Grover and Davenport, 2001).

Diffusing knowledge requires communities with members that are eager to share knowledge (Brown and Duguid, 2001; Wenger and Snyder, 2000). Furthermore, the role of knowledge brokers is required to facilitate the interaction between the people who have the knowledge – the experts and the people who need to use the knowledge (Hauschild et al., 2001; Fahey and Prusak, 1998). It is important to note that a KMS will be used when users are informed of its availability and are trained on how to use it. Assuming that they will automatically use the system without training is a recipe for marginal return (Fahey and Prusak, 1998). Training programme, consequently, is an important Factor that needs to be addressed.

Brown and Duguid (2000) suggest that allowing untested knowledge into KMS will quickly make it lose credibility. Diffused knowledge requires validation (Birkinshaw and Sheehan, 2002; Brown and Duguid, 2000) and a knowledge feedback loop needs to be facilitated to allow users to have active participation (McInerney, 2002; Szulanski, 1996).

At the heart of knowledge diffusion is people not only technology (Storck and Hill, 2000; Hansen et al., 1999). Therefore, Factors related to knowledge culture are often mentioned by different authors, for example commitment from top management (Beazley et al., 2003; Davenport, de Long and Beers, 1998), open communication (Grant and Baden-Fuller, 2004), workers that have freedom of ‘space’ (Heaton and Taylor, 2002), and problem solving culture (Lesser and Storck, 2001).

My research indicates, as elaborated in Project Two, that a number of Factors in KIAT significantly or completely affect the Knowledge Diffusion (KD) stage. Those Factors are listed in Table 1-5. Fourteen Factors are of the infrastructure dimension, fifteen Factors are of the knowledge structure dimension, and seventeen Factors are of the knowledge culture dimension. The evaluation of these Factors, as explained in Project Two, reports the readiness of the Infrastructure – KD (i.e. the infrastructure for Knowledge Diffusion), Knowledge Structure – KD, Knowledge Culture – KD with a scale between one to five. A scale of five is the highest readiness state. As elaborated in Chapter Four: Project Two, I propose that a scale of three is a level where organisations have a better chance of implementing KMS. Readiness of lower than three does not, however, necessarily mean that the organisations must not proceed with the implementation. What it means is that managers have the information as to what lower-scored Factors they need to address in the effort to implement KMS for knowledge diffusion.

This discussion leads to a conclusion, expressed as:

Proposition 5: Readiness to diffuse knowledge increases as the measure of the Infrastructure – KD, Knowledge Structure – KD, Knowledge Culture – KD increases.

Table 1-5: Factors that significantly or completely affect the knowledge diffusion (KD)