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KMGN Beacon. Issue 1
September 2022 Issue #1
The View (Editors Letter)
Dear KMGN members,
“An investment in knowledge always pays the best interest.”
Wise words from Benjamin Franklin, one of the founding fathers of United States, and known polymath of his time, an active writer, scientist, inventor, statesman, diplomat, publisher and political philosopher.
As I reflect upon these words, I feel a bit of conflict, and maybe a tinge of regret. Whilst his words resonated with my passion for Knowledge Management (KM), I have yet to see it practiced in many organisations that I have interacted with. It makes me wonder what else can be done as a KM professional - to help organisations reach that realisation.
Such is the mission of KMGN and we believe that we can achieve this through collaboration - in order for KM to flourish, and KM professionals need to work together. We hope that this inaugural newsletter represents another foundation stone for KMGN, allowing global KM professionals to connect and contribute as a community.
The newsletter shall be published monthly, beginning from Jordan and the Middle East. Each KMGN partner network shall have an opportunity to publish and share local case studies and reports, and in so doing contribute to the diversity of perspectives with regards to KM. This shared platform endeavours to forge a shared sense of togetherness amongst global KM professionals.
I call on us all, to take this opportunity to learn from each other, and embrace the diverse cultures, languages, and values - as we tackle similar challenges in KM. Let us all come together, and help many organisations across the globe, to realise the following wise words of Benjamin Franklin.
“An investment in knowledge always pays the best interest.”
Article of the Month: ISCCEE Model of Knowledge Dimensions & Conversion
Khattab Salman
When you attempt to define knowledge, you will find different people and businesses defining it in different ways and purposes. The same applies when you ask about the types of knowledge in an endeavor to answer that first question. However, for the sake of this article’s purpose, we will stick to this statement:
Knowledge exists is three states:
Explicit
Implicit
Tacit
In order for organizations to benefit from knowledge, it most probably needs to be as explicit as possible. This means that implicit and tacit knowledge need to be converted into a more usable state to be used and applied to problem-solving or decision-taking situations.
Organizations can benefit from explicit knowledge, may benefit by implicit knowledge, but cannot do with tacit knowledge. This naturally applies when you want to transfer knowledge to others so they are as knowledgeable as the next person. However, when it is tacit, it is deep and this means that in most cases you do not know you have that knowledge in your organization, thus you miss out on it.
That is why that tacit knowledge needs to be “emancipated” to the realm of explicit or at least implicit level, and to do that you need to understand the dimensions and conversion approaches that explain how this happens.
Immense discussions have been around for some time and resulted in what can be considered the basis knowledge management, as we know it today, stands on.
Among these were the SECI Model for Knowledge Conversion by Ikujiro Nonaka, the I-Space conceptual framework by Max Boisot and the Cynefin Framework developed by Dave Snowden. The attempt was to understand how knowledge moves, develops and is used.
To accommodate the three types of knowledge types, and how they are moving in those dimensions, I present a model that explains this “emancipation” of knowledge assets in the “Ba” of Nonaka or the “Cynefin” of Snowden, both revered authorities on the subject.
The six facets of ISCCEE conversion
ISCCEE is an acronym for Identification, Socialization, Conveyance, Contemplation, Erudition, and Encryption. These are the six conversions of knowledge that happen within the dimension in which knowledge resides.
Imagine the universe of ISCCEE conversion as a cube within a cube. The smaller cube is Knowledge while the bigger one is the conversion process.
The six faces of the cube represent a status that a specific type of knowledge is going through.
The six faces are six conversions in order as below:
Tacit → Implicit (Identification)
Implicit → Implicit (Socialization)
Implicit → Explicit (Conveyance)
Explicit → Explicit (Contemplation)
Explicit → Implicit (Erudition)
Implicit → Tacit (Encryption)
The path of the order is explained in the next diagram:
Tacit → Implicit (Identification)
Situation: The will of the organization to audit what they have in terms of Knowledge Assets. This is not aimed only at tacit, but also includes explicit and implicit knowledge assets.
Approach: Knowledge audit, induction, situational observation
Tacit knowledge is deep and hard to specify or identify. It is camouflaged in the abilities of someone or a process. Therefore, the process of converting tacit to implicit is basically identifying that the organization has that knowledge. This means it changed in type from Tacit to implicit. Needless to say, this could be the most valuable type of knowledge, and at the same time the most damaging if unearthed and that needs induction, a comprehensive knowledge analysis and sometimes behavioral or situational observation.
Implicit → Implicit (Socialization)
Situation: The creation of a cultural environment that spreads knowledge sharing so people can see what others know, connect with them, and recognize means of contributing to a common objective of capacity building and development of ideas and concepts in different fields.
Approaches: Communities of Practice, Communities of Interest, Work Teams and Groups, Knowledge Events, storytelling.
When knowledge is at the implicit knowledge level or stage, it is at least known. It is the same of Nonaka’s SECI dimensions for tacit knowledge but applied on implicit one. Sharing and transferring implicit through experiences or events (cafes, lectures…) attended by people with implicit (or even tacit) knowledge. Socialization is basically breaking down barriers of knowledge hoarding. Naturally this stems from willingness of knowledge owner or holder to share it with others.
Implicit → Explicit (Conveyance)
Situation: Knowledge transfer in a concentrated manner through specific apprenticeship programs
Approaches: Meetings, brainstorming, interviews, observation, mentoring, shadowing, note taking. Conveyance is transfer. This is when knowledge is actually laying the foundation for being explained, communicated and comprehended. Nonaka believes that since implicit knowledge is difficult to formalize and often time and space specific, it can be acquired only through shared experience, such as spending time together living in the same environment or working on the same project. This can happen in any manner that translates knowledge into simpler form that can be understood by the recipients, and occurs in a traditional apprenticeship setting where apprentices learn the knowledge needed in their craft through hands-on experience, rather than from written manuals or textbooks.
Explicit → Explicit (Contemplation)
Situation: Delivering on targets; be them learning, performance, or task oriented ones. prototypes.
Approaches: Book of Knowledge, knowledge repositories, networks, expert locator systems. Although knowledge is now concrete, it still needs some work to be more useful. One definition of KM that I like is “providing the right information to the right person and the right time and in the right format to make and take the right decision.” Part of that definition is format, and time. Sorting and combining knowledge assets to serve defined purposes, answer certain questions and aid specific people is essential. This includes publishing, articulation and de-codification develops the basis for new knowledge creation. What is conceptual and inherit is now concrete and sharable. Without that, knowledge assets would remain stored in a database and no one would know about it, use it or develop it into new knowledge. Dissemination does not occur and the learning process is broken.
Explicit → Implicit (Erudition)
Situation: Your ability to create new knowledge by identifying the connections and patterns to make sense between these different domains of knowledge, points of view to come up, based on your newly learned knowledge and the inherent one from before, to create new knowledge, methods, and procedures.
Approaches: Innovation and Creativity, Learning Organization, fostering learning and encouraging it, R&D. The new knowledge creation starts at this stage provided that we get here successfully. Recipients learned knowledge from the sources and internalized it. This is where learning occurs. People spend too long finding information they need and little time reading, comprehending and creating/adding to it. If knowledge is available in the format that can be used, accessed in time to use and comprehended fully, then creativity and innovation happen through reflection that happens in different ways for different people depending on their different abilities, understandings and purposes. These differences make the new knowledge created implicit (remember we said it depends on varying competencies, comprehension and purpose.) It is not explicit as people cannot see it, understand it, or accessed the way you, the creator of this new knowledge, do. It will be part of your individual private deep knowledge, skill and competency at one level, and part of the organization’s capabilities deep in its processes and procedures on the other.
Implicit → Tacit (Encryption)
Situation: The patents, Innovative solutions, creative processes of the organization.
Approaches: Tools can be as in phase 1 (Knowledge audit, induction, situational observation.). This is how knowledge becomes tacit. It is encrypted, mostly in the brain of the learner in a manner that he/she only can understand or fathom its depth, dimension and even application. It can also be encrypted in how an organization does its work. This could be manifested in processes, culture or even legally protected patents (it is tacit to outsiders but very explicit for the organization). Because of that, it cannot be identified or accessed unwillingly. That is why it is so difficult to capture that type of knowledge. It is too deep that normal knowledge identification or capturing processes will only scratch the surface.
Points to consider:
It is essential to understand that these conversions are a continuous process. They can start at any stage as a starting point and continue in a spiral manner to reflect continuous learning and knowledge creation (innovation.) When this transcends the individual to the collective, we arrive at a learning organization.
The difference between phases 1 and 6 is that at this stage, organizations have a fair idea of where that knowledge is and, to some extent, its quality.
Phase 6 is not “bad” since it is a natural process of human accumulation of knowledge. It is human nature; this is how we learn, process and store knowledge in our heads.
Since it is a spiral learning process, and if we are cognizant of how it happens, or even control or guide it in a certain direction, the organization becomes a Learning Organization. Learning organizations continuously benefit from what they know to create new innovative knowledge that will equip the organization with new capabilities (stemming from ever developing competencies of its individuals) that can keep it ahead of others because of that “competitive advantage” or “added value” or whatever you want to call it.
Organization of the Month: Saudi Central Bank
Khattab Salman
At the beginning of 2019, I was asked to help the Saudi Arabian Monetary Authority (SAMA), which is the Saudi Central Bank to implement, or rather continue their efforts in implementing a KM program.
They had earlier started the program with a big four consultancy house but the efforts went astray for several reasons we are not discussing here.
The KM program was entrusted with a KM section within the Excellence Center in sector 6. SAMA had six sectors or “deputyships” with 48 organizational units. SAMA employees stood at around 3000 personnel. (the number is now around 1300 as I understand.)
The biggest challenge for SAMA was the age gap between new recruits and the “old guard” who are about to retire or leave the organization.
So, the target of the KM program I put was to transfer knowledge from the “grey” to the “black” through implementing KM processes that guarantee the smooth transition between old middle and top management and the new succession planning candidates to replace them.
To do that, we needed to first determine who are these candidates, who are the potential leavers, the network they are associated with, and the cost of the replacement process.
We developed several tools to measure these inputs and worked closely with the HR, IT, and strategic planning teams to ensure that the KM program would hit its targets.
Among the tools developed were:
Knowledge Landscape Analysis
Social Network Analysis
Succession and Onboarding Planning
We had to hold a meeting with every agency within SAMA and interview their teams in an exercise to determine where knowledge lies, be it in people, processes, repositories, third-party content providers…
The desired outcome of the abovementioned tools was to:
Determine the Knowledge map of SAMA
Determine the knowledge gap we have
Draw a social network of how knowledge flows with SAMA
Prepare recommendations on how to go forward.
The KM team (4+) interviewed 46 of the 48 organizational units and received responses from 44 units. The KLA report was built on these responses and recommendations were drawn based on the findings after analyzing these responses.
The most prominent findings were:
Number of knowledge gap needs was 160+
The needs focused on training and qualification, field visits (benchmarking and conference), and consultancy services.
The surprising need was access to information from other internal units, which significantly implies a classic silo syndrome of knowledge and information islands that do not communicate or share knowledge.
We also found out that one reason for that was the sharing (if any) mechanisms depended on paper and document shuttling between units (66% while e-mail counted for 19%)
Explicit knowledge assets totaled 370 assets while implicit knowledge assets (experts) reached 239 covering 242 disciplines.
The recommendations put forward were:
Develop a plan to bridge knowledge gaps with relevant units
Providing collaborative information systems
Existence of an institutional knowledge communication plan that is related to and enhances the knowledge content, and linking them to explicit knowledge assets recipients from organizational units within SAMA and external partners. The goal of this plan is to deliver information to its users in an institutional manner and not to be satisfied with providing information when requested
Linking to electronic systems between organizational units and partners of all kinds, as much as possible
Reaching a compromise on confidentiality of information to be accessed by providing information about the origin of knowledge without access to if it.
Establishing criteria for who is an expert and who is merely an employee of long service.
Institutional tacit knowledge is centered on one person, so there is a need to focus on transferring critical knowledge
The need for a system of incentives and rewards for sharing knowledge or maintaining its momentum
Laying foundations for data and information governance through:
Standardization of the storage location for documents
Unification of employee knowledge pages
Existence of clear institutional methodologies on knowledge content and its management
A unified classification system for business in the organization, as this system helps in classifying, searching, and retrieving knowledge assets in a logical, fast, and efficient manner.
Raising awareness of the concepts and principles of knowledge management in the organization and at all administrative and technical levels through workshops, lectures, and training, especially for knowledge ambassadors in organizational units
Continuing to implement the KLA yearly or bi-yearly basis.
The need for a system of incentives and rewards for sharing knowledge or maintaining its momentum.
The project took one calendar year to finish. This does not mean that the KM efforts are done, although SAMA is now considered a pioneering knowledge organization in Saudi Arabia through continuing its efforts in implementing a comprehensive Knowledge Management program. Through that phase, we prepared the ground for a proper KM program to be implemented and build upon.
KMGN News & Events
September 15, 1PM UTC (90 minutes) – Led by Rudolph D'souza, India
How did an infrastructure company with a traditional culture transform to a thriving knowledge sharing culture?
In this interactive session, the KM team will share a bit about their journey, but will be happier to respond to audience questions.
More information here
September 21, 1PM UTC (75 minutes) – Led by Dr. Eric Tsui, Hong Kong
KM and the metaverse
More information here
October 12, 5AM – 1PM UTC (8 hours- people can join partially) – Led by Faiz Selamat, Singapore
First global KM hackathon marathon – experts, professional KMers, business leaders and KM lovers co-create the solution for main KM challenges. Registration form
KM’s Who’s Who: Karl Wiig: The Man Who Brought Us KM!
Khattab Salman
Karl Wiig was born in 1934 in Norway, came to the United States in 1957 and currently lives in Arlington, Texas. He has been CEO of Knowledge Research Institute, Inc. since 1995 and a technical and management consultant and researcher since 1970.
Karl is known to be the professional who coined the term “Knowledge Management” back in 1986 in a paper he presented to a UN conference in Switzerland. Dave Snowden states that Karl Wiig is one of the first KMers who paved the way for the KM movement, while other sources claim that the term KM was coined by both Karl and Karl-Erik Sveiby in that same year. Nevertheless, the talk about Knowledge can be attributed to other scholars, especially Peter Drucker’s literature when he first used the term 'knowledge work' in The Landmarks of Tomorrow (1959) and later coined the term 'knowledge worker' in his The Effective Executive book published in 1966.
Karl has numerous books and articles on Knowledge Management. His writings mainly focus on societal intellectual capital management and the building of competence. According to Stan Garfield’s Profiles in Knowledge, “in the 1960s he worked with analysis of industrial and biological systems and computer-based control of industrial processes. In the 1970s at Arthur D. Little, Inc. he started the Policy and Systems Analysis group and subsequently, the Applied Artificial Intelligence (AI) Center that initiated the concept of Knowledge Management (KM) in 1983. Later, he was consulting partner at Coopers & Lybrand. He was the co-founder of the International Knowledge Management Network.
I had the pleasure of inviting Karl Wiig to be the Keynote speaker at the KM summit I organized in Dubai back in 2003.
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