The following blog summarises the feedback received from the respondents to the Knowledge Creation Capability Questionnaire.
Thank you for taking part and I hope the results will provide some insight into how the model can be applied in your organisation.
The target audience for the questionnaire was delegates planning to attend the South African Knowledge Management Summit. The results below reflect the data gathered from 17 respondents.
Nonaka and Takeuchi (1995: 56) see problem-solving as the source of continuous innovation and continuous innovation as the source of sustained competitive advantage.
When organizations innovate, they do not simply process information, from the outside in, in order to solve existing problems and adapt to a changing environment. They actually create new knowledge and information, from the inside out, in order to redefine both problems and solutions and, in the process, to re-create their environment.
From this statement follows that problems are central to continuous innovation. In other words, problems presented by customers and markets may lead to innovation. Similarly, the daily problems that knowledge workers experience may result in innovative solutions and new knowledge or know-how from within the organisation. Nonetheless, problems must be solved in order to create something new.
The chart below indicates that the majority of respondents solve problems regularly in the workplace. The majority further indicate that they learn when they solve problems. More than 90% agreed that problems may lead to new innovative solutions. These are all important views to ensure that knowledge creation will follow problems. It further confirms that problems are valuable.
The majority of the respondents are spending the most time understanding a problem. Consider the quote below:
“If I had an hour to solve a problem I'd spend 55 minutes thinking about the problem and 5 minutes thinking about solutions.” - Albert Einstein
This seems to indicate that it is good practice to understand problems before solving them. The planning tool may assist here to ensure that knowledge workers allocate enough time to the various phases.
The cognitive domain can be described as the place of learning. The cognitive domain may be enhanced by using specific learning methodologies to stimulate creative learning. As seen in the previous section on problems, complex problems require a cognitive approach and critical thinking is a valuable skill. Bloom's taxonomy of learning is widely used and seen as a method to stimulate creative learning through critical thinking.
The chart below represents a cognitive map of all the respondents to the questionnaire. We can see that the application phase for this group of respondents is highly active.
The following chart represents the cognitive map of respondents filtered by Master's degree level.
The following chart represents the cognitive map of respondents filtered by industry level (Human resources).
Below are a comparison between two knowledge workers. Comparing the create phase of these two workers clearly demonstrate that they are hypothesizing to a great extent - but that designing and constructing actions are taking place to a lesser extent. There's not much that we can gather from this, at this point in time.
But if these were workers in a specific industry where innovative solutions are to be crafted, the question might have been asked why is the specialist not designing and constructing more?
Many organisations are daily faced with the question of which soft skills are required in my organisation. Where will the training budget have the biggest impact? If innovation is seen as a key business driver then the organisation may want to invest in the critical skills as listed by the OECD (2011: 41).
The chart below reflects the generic skills required, based on the OECD report. The majority of respondents have indicated an advanced level of skills. If this were an organisation they might want to ensure that all employees are on an advanced level for these skill.
The statement, 'I ought to know this’, appears to be the first level of learning for innovation. If one can admit that one ought to know about something the stimulus/motivation for innovative learning is in place. The KC model also incorporates the Socratic view of the more one knows, the more one knows that one ought to know more. These two questions form the basis for the creation of a continuous cycle of improvement or innovation.
If knowledge exists and the imagination is triggered by a fresh idea, attitude will determine if the idea becomes a feasible innovation. Seelig (2012: 188) explains that attitude is the spark that jump-starts creativity. Attitude is a complex neurological process and in the field of psychology various studies have been done in this regard. Some attitudes, it seems, are better suited to drive innovation processes. The attitudes used in the questionnaire was researched by me as part of the MIS degree.
The chart below clearly shows healthy attitudes exist in the majority of respondents. Where we have disagreement on these attitudes it will be important to understand why these respondents are disagreeing.
The values below are linked to Bloom's affective traits required for successful learning and knowledge creation. The majority of respondents supported these behaviors. Once again if this was an organisation one would like to understand the reasons for those that do not support these behaviours.
Without knowledge there can be no innovation. Aranda and Moline-Fernandez (2002: 292) confirm the statement that knowledge is a source of competitive advantage. They further state that the importance of knowledge as a source of competitive advantage is even higher for those sectors where innovations are continually being developed (Decarolis and Deeds, 1999: 954; Pisano. 1994: 96).
The acquisition, transmission and integration, as well as application of knowledge, become the base for measuring an organisation's efficiency (Grant, 1996: 380; Nonaka and Takeuchi, 1995: 26; Spender, 1996: 49; Zander and Kogut, 1995: 77).
The chart below highlights important knowledge management issues.
The responses below further shows that the respondents value the role that access to knowledge has in knowledge creation, when the majority agrees with the statements below.
Aranda, D.A. and Molina-Fernández, L.M. 2002. Determinants of innovation through a knowledge-based theory lens. Industrial Management and Data Systems, 102(5): 289-296.
Decarolis, D.M. and Deeds, D.L. 1999. The impact of stocks and flows of organizational knowledge on firm performance: an empirical investigation of the biotechnology industry. Strategic Management Journal, 20: 953-68.
Grant, R.M. 1996. Prospering in dynamically-competitive environments: organizational capability as knowledge integration. Organization Science, 7(4): 375-387.Nonaka, I. and Takeuchi, H. 1995. The knowledge-creating organisation: how Japanese companies create the dynamics of information? Oxford: Oxford University Press.
OECD. 2011. What are the skills needed for innovation? Skills for innovation and research. Paris: OECD Publishing.
Pisano. G.P. 1994. Knowledge, integration and the locus of learning: an empirical analysis of process development. Strategic Management Journal, 15: 85-100.
Seelig, T. 2012. InGenius: A crash course on creativity. New York: Harper Collins.
Spender, J.C. 1996. Making knowledge the basis of a dynamic theory of the firm. Strategic Management Journal, 17(2): 45–62.
Zander, U. and Kogut, B. 1995. Knowledge and the speed of the transfer and imitation of organizational capabilities: an empirical test. Organization Science, 6(1): 76-92.