- 1 DIKW (Data - Information - Knowledge - Wisdom) model revisited
- 2 Introduction
- 3 Keywords
- 4 Detailed Description
- 5 KM4Dev Discussions
- 6 Examples in Application
- 7 Related FAQs
- 8 Further Information
- 9 Original Author and Subsequent Contributors of this FAQ
- 10 Dates of First Creation and Further Revisions
- 11 FAQ KM4Dev Source Materials
DIKW (Data - Information - Knowledge - Wisdom) model revisited
One of the most active discussions in the long time (and on KM4DEV that is not insignificant), this discussion started on the fringes of a discussion about 'Knowledge generation, what/where/why?' on 1 February 2010 when a member on the list referred to the old DIKW model (data-information-knowledge-wisdom). References to this model really triggered a flurry (and fury) of emails, particularly after Dave Snowden's intervention, dismissing the model as irrelevant and dangerous and stating that 'Anyone talking about wisdom as a higher level of knowledge should be taken out and shot for the good of the field'.
This was a great opportunity to reflect about the model and ponder about its limitations. This entry summarises the key points in the debate.
Data, information, knowledge, wisdom, models, KM literature, KM, knowledge management.
The discussion thus started with this idea of using the DIKW model to explain the difference between all these terms. The specific reference to wisdom as an additional layer that helps contextualise knowledge and make it relevant caused the controversial statement by D. Snowden. It caused a number of messages about the acceptance of this model as a working model (or not) for the KM field.
A few referred to the importance of definitions to clear some doubts by people exposed to KM at the beginning. Others insisted about the importance of looking beyond data to explain knowledge and finally the crux of the matter was addressed: What some refute in this DIKW model is the linearity of the continuum D-I-K-W as well as its cultural limitation (failing to accommodate uncodified and unarticulated 'naturalistic' knowledge of the zen, sufis or even London Cab drivers.
Then Patrick Lambe made a crucial contribution to replace the DIKW debate in a historical perspective, explaining why the model has been used to legitimise computer/information science as valid and useful but was not meant to accommodate more complex considerations from e.g. a KM perspective. Knowledge should also not be perceived as a result from data and information but rather data is the result of 'knowledge-driven purposeful piece of design work'. Essentially, DIKW is a managerial model to explain how one can make use of data. He pursued arguing why this model became received wisdom (see detailed discussion or full transcript at the bottom for more).
Another point made later is that DIKW can be a useful model to explain the visibility/tangibility of different elements: We see a lot of data, less information, knowledge becomes opaque and wisdom a mystery? This is perhaps a reason explaining the success of the model: it makes it easier to focus on the visible stuff (data / info) but that approach often fails to address the most critical needs.
Another contribution pointed to the difference between subject (knowledge is a human emergent behaviour) and object (data and information can be captured). In other words D&I are part of a physical reality while K&W are part of our "inner universe". Yet another contribution asserted that knowledge could be identified with 'sets of consensual beliefs in a given context' as a result of transactions within a given community and that information could allow us to 'accumulate the outcome of these transactions' while wisdom would be the 'capacity to apply collective believes in new situations'.
The discussion then moved on to positive deviance (should be another wiki entry topic) and the fact that we fail to understand what motivates the behaviour of such people and we do not focus on the data, information and knowledge that seem to inform this behaviour either.
This is a selection of the key points expressed on the list:
- (the genesis of this discussion) Data becomes information when organised through analysis, concern and possible intent. Information becomes knowledge when it becomes part of skillset / capabilities of an individual/organisation/community. Wisdom allows us to properly apply knowledge in context (S. Lanfranco).
- Information stems from dialogue between people and now and then some data's added. People share information by talking to (or doing action-research) together and meanwhile they develops skills/experience. They can document this (write it down) but to learn, this information needs to be fed back in the dialogue and the cycle starts anew (J. Pels).
- (the controversial message) The DIKW model is plain wrong, difficult to explain and leads to bad labels. Knowledge helps us create information from data and if we share knowledge we can understand information. Wisdom as a higher level of knowledge is ludicrous (D. Snowden).
- Surprising to see that this well accepted model is debated again as it is helpful to explain the notions as a means of storytelling to transfer knowledge (P. Hall).
- Show examples of wisdom management or higher levels of knowledge that is not pretentious and I will agree (D. Snowden).
- Though DIKW didn't help much it's useful to have working definitions to distinguish the terms. Wisdom doesn't help here. It is the capacity to make right decisions on the basis of what's known/available, i.e. applied knowledge. Wisdom management doesn't make sense here (J. Schunter).
- How can wisdom be regarded as following objective and universal categories? KM every so often falls into the trap of treating human decision-making as intrinsically wise, provided that it is based on sufficient information / knowledge. We should reflect debates on what norms and decisions can be considered wiser while knowing that these foundations are constantly contested (B. Kumpf).
- Agree w/ D. Snowden, DIKW's based on analogy of processing databases, which is a different pathway than knowledge generation. Most (useful) knowledge for development is not in databases but structured in stories, feelings, patterns, rules of thumb, analogies, concepts, narratives, insights, guesses and portfolio of cases, inside living brains. The challenge is to be sensitive, open and intelligent enough to interact constructively with these forms of knowledge (S. Mendonça Ferreira).
- The danger of the model is in its linearity and hierarchy. Management science simply hasn't put as much effort into understanding knowledge than the history of philosophy. The DIKW model also fails to account of shamanistic knowledge & narrative Sufi philosophical traditions. It is therefore a culturally limited and inadequate model, closely followed in fallacy by the SECI model and it is responsible for 1000 failed KM initiatives. It forces people to think of knowledge as a thing, rather than a flow. On the other hand it is useful to see information as a structured form of data. But down the line, shared context is key for information flow and the purpose of KM is to create shared context (information, experience, education etc.) to all this to take place (D. Snowden).
- This is not about thrashing models but about being able to use wisdom/sagacity to know when to apply what. To do that we need a transdisciplinary knowledge and experience base and the ease to move between these depending on circumstances, needs and goals (W. Ho).
- I agree that all perspectives are limited but it doesn't follow that all perspectives have either value or validity (D. Snowden).
- The model emerged in the 1970s when computer/information science tried to legitimise itself as a strategic discipline. Data was then seen as critical to treat as strategic resource (in the sense that it would relate to information which in turn fed decisions based on knowledge). It was not meant to accommodate the far more complex world of KM and the model completely fails to acknowledge naturalistic ways that data, information and knowledge interact. Data is the product of a knowledge-driven, purposeful piece of design work but the DIKW model implies the opposite. The model also completely fails to account for the sea of knowledge activity in an enterprise which is never informationalised or structured as data. You need to go back to the contexts that created the data and the knowledge activities the data supports, in order to figure out how the data can be anipulated for greater advantage. So DIKW is a managerial model intended to explain how data can be leveraged as an enterprise resource. It has not practical value for guiding action beyond the D-I interface. How did the model gain recognition? 1) as a legitimising model (self-reinforcing), 2) The weakness of the model related to K-W was challenged too late, once the model was already accepted 3) Writers for KM journals in the 1990s lacked matter and copy/pasted old mental models without questioning them 5) Structuring KM work around DIKW model gains rapid IT support and when facing problems of adoption/usability it is easy to refer to the human intransigence and change resistance. (P. Lambe)
- "We have oceans of data, rivers of information, some pools of knowledge and a very few drops of wisdom. Note, not a hierarchy but shifts in communication channels" (V. Brown).
- Boisot is a useful writer here. His I-space model respects but moves beyond the IT tradition. One of his key sub-models contains the spectrum of knowledge from zen-narrative-symbolic. DIKW works only in the symbolic, hence the issues we have with it (D. Snowden).
- One way to read the DIKW pyramid is in terms of visibility and tangibility of the different elements. We do see a lot more data, it's easier to figure out where it is, and what to do with it. Information is less transparent and more complex to audit and map, knowledge is much more opaque, and wisdom auditing (people do actually sell this!) would be either a work of opinion or divination. So if DIKW just made claims about visibility it would have some use. That may be another reason why the DIKW pyramid has seemed so attractive: the visual form focuses us first on the more manageable (visible and tangible) elements and encourages us to work on those first as foundational elements - providing a visual justification for a quick win bias. The problem is that the knowledge ecosystem is more complex than DIKW allows, and focusing energies and effort on the easier stuff frequently fails to meet the most critical needs. (P. Lambe)
- The DIKW model should bring to light that Knowledge evolved as emergent behavior within human body as complex system, having consciousness and free will (mind and value) as well as behaving dynamically as Subject. On the other hand, DI not evolved but created or captured, should be and always treated as Object and only make people “well informed”. Knowledge and beyond, or KW, making people “knowledgeable and wise” concerning their action and performance. To summarize, let me state that DIKW model beyond doubt comprising two entities which have entirely different epistemology. DI derived from Physical Realities or Physical Universe, but, KW on the other hand derived from our Inner Universe or Knowledge domain. (MD Santo)
- Reference to David Weinberger's article (see 'Further information' section) 'The problem with the DIKW hierarchy'. The article goes back to the fundamental flaw of establishing a hierarchy between the four terms and also mentions this interesting bit about knowledge: "But knowledge is not a result merely of filtering or algorithms. It results from a far more complex process that is social, goal-driven, contextual, and culturally-bound. We get to knowledge — especially "actionable" knowledge — by having desires and curiosity, through plotting and play, by being wrong more often than right, by talking with others and forming social bonds, by applying methods and then backing away from them, by calculation and serendipity, by rationality and intuition, by institutional processes and social roles. Most important in this regard, where the decisions are tough and knowledge is hard to come by, knowledge is not determined by information, for it is the knowing process that first decides which information is relevant, and how it is to be used."
- We could identify knowledge with sets of consensual beliefs in a given context. They are the result of the transactions within the community. Information allows us to accumulate the outcome of these transactions. Wisdom is the capacity to apply these collective beliefs in new situations... The web 2.0 is the biggest codification adventure of mankind generating a mesh of information taht approximates to knowledge (A. Acuna).
- "I hadn't realised that the concepts of Data, Information, Knowledge, and Wisdom have been reified as a hierachy and/or pyramid among the knowledge management set until David Snowden's outburst. The relationship between the four terms is only a sequence; the inter-relationships can also form a pattern, an image, a prediction, a synergy and a collage." (V. Brown)
- "Don't you also think that data is separated from information as raw bits of text are separated from intentionally structured bits of text like books, articles, video documentaries etc. ? ... I prefer referring to the act of knowing than knowledge indeed as it is all about conjuring up all the things we have in ourselves to make (supposedly) better informed decisions, which could be ideas or facts... On wisdom, how about it being 'accumulated / analysed experience which allows us to make a better informed decision in a known or unknown context? (E. Le Borgne).
- It's the process of abstraction and codification that creates information from data (and requires a shared knowledge base). The knowledge base (common levels of abstraction, understanding of the conventions of codification) are what allows that process to take place... I'm happy if you want to talk about wisdom in the context of judgement (making choices etc. per your text) but that is one aspect there are several others... The whole point is that its not a linear process. You can have two boxes labeled DATA and INFORMATION and a double headed arrow connecting them (as it can go both ways); then a fussy cloud labeled knowledge between them. Wisdom may be the ability not to try to go beyond that. (D. Snowden).
- The DIKW promotes an artificial hierarchy and a false notion of a linear sequence of transformations. The model also lacks the negative companion to each of the elements (non data, non information etc.) (M. Menou).
- In a workshop participants made several references to experiential learning-based knowledge (unless you experience/do something, you wouldn't learn and know). It was easy to relate as a concept, much less so at a practical level. In another exercise, participants easily came up with a list of different forms/categories of data and some identified information. All in all, when there is investment in KM in local NGOs, I see the focus is in terms of the capacity development - in the infrastructure - computers, equipment, trainings, hiring a "knowledge/information officer", cabinets lined with files etc etc. This is done without much thinking on " What knowledge? from where ? and why?" without a learning strategy. (A. Singh)
- There are no absolutes and no agreement on the way to go from there to here (nor about what is there and what is here for that matter). Within this cloud of uncertainty one has to choose between the risks of evidence based decision making and some faith based decision making. I for one prefer the risks of evidence based decision making. One can learn from it. Successful design takes a lot of wisdom. We can argue about what it is, but we, as individuals and as communities had better pay some attention to where it comes from and how we deploy it, at least if we want to get beyond rhetoric to action, and move some bit toward there from here. (S. Lanfranco).
I intentionally omitted the part referring to the positive deviants' actions in this summary as it is only partly related to this discussion thread but you can find the whole exchange on this in the full transcript (bottom of this page). (Ewen Le Borgne)
The following members of the KM4Dev community contributed to the discussion thread on the DIKW model: Sam Lanfranco, Jaap Pels, Dave Snowden, Patrick Hall, Johannes Schunter, Benjamin Kumpf, Chris Burman, Sebastiao Mendonça Ferreira, Charles Dhewa, Wenny Ho, Patrick Lambe, Valerie Brown, MD Santo, Peter Bury, Nancy White, Alfonso Acuna, Ewen Le Borgne, Michel Menou, Amina Singh, Sarah Cummings, Tony Pryor
Examples in Application
A couple of articles were shared about the topic:
- The problem with the Data-Information-Knowledge-Wisdom Hierarchy (blog post by David Weinberger) 
- The Origin of the “Data Information Knowledge Wisdom” Hierarchy (article by Nikhil Sharma) 
- Complex acts of knowing (article by Dave Snowden about a.o. what is knowledge) 
Based on this very discussion:
- From data, with love (blog post by Patrick Lambe as a reflection on this discussion 
- Settling the eternal semantic debate what is knowledge what is information (blog post by Ewen Le Borgne as a reflection on this discussion 
- Narrative as mediator (blog post by Dave Snowden) 
Blog posts running in parallel:
- Nothing good can come from believing Data -> Information -> Knowledge (blog post by Chieftech) 
- The problem with DIKW (blogpost by Hypergogue) 
- George Siemens's take on the revived DIKW debate 
Images showing the DIKW model or related:
- At its simplest 
- More complicated 
- Still more complicated 
- Depicted as the information value chain 
- Illustrated in the basic structure and organisation of the organisational knowledge base 
Original Author and Subsequent Contributors of this FAQ
Original author: Sam Lanfranco.
Subsequent contributors: Jaap Pels, Dave Snowden, Patrick Hall, Johannes Schunter, Benjamin Kumpf, Chris Burman, Sebastiao Mendonça Ferreira, Charles Dhewa, Wenny Ho, Patrick Lambe, Valerie Brown, MD Santo, Peter Bury, Nancy White, Alfonso Acuna, Ewen Le Borgne, Michel Menou, Amina Singh, Sarah Cummings, Tony Pryor.
FAQ author: Ewen Le Borgne
Dates of First Creation and Further Revisions
First creation: 18 February 2010.
FAQ KM4Dev Source Materials
With regard to the good question "knowledge generated by whom?" there is an old construct that I find useful when doing workshops and training. In simple terms it starts with the idea of organizational structures and social processes surrounded by a cloud of DATA which only becomes INFORMATION as it is organized through some process of analysis, concern and possible intent. Information becomes KNOWLEDGE when it becomes part of the SKILLS SET/CAPABILITIES of an individual, an organization, a process or a community. The analysis frequently stops there with DATA>INFORMATION>KNOWLEDGE. We take it one step further and argue that knowledge only has meaning in CONTEXT and with used with WISDOM. One advantage of this simple construct is that it blends any aspect of KNOWLEDGE use, transfer, whatever, with two necessary real tasks, (1)properly identifying the CONTEXT in which it is to be used, and (2)assessing the relevant individual, organizational or community WISDOM to properly apply knowledge in context. (Sam Lanfranco)
Hi, To go from data to information you will need some knowledge (on how to do that), but knowledge came after information ... Now what is wisdom? I think we get confused by this 'linear logic' data -> etc. I think information stems from dialogue between people where now and then some data in added. Even worse, a lot of times the data and information are denied (genocides) to access the dialogue or ignored (fish population decline) or made up (WMD by Irak). To me people share information and knowledge while talking to (and doing action research with) each other. In the mean time they develop skills / experience and hone their mental / instrumental capabilities. This process can be documented to result in information (from personal notes to wikipedia). To learn this information has to be fed back (versioned) into the dialogue (the conversation, the discourse, the knowledge sharing process) and then the cycle start a new. Best, (Jaap Pels)
I would reject the DIKW pyramid, aside from the fact its just plain wrong, its difficult to explain and leads to bad albels Better to think that KNOWLEDGE is the way we create INFORMATION from DATA. If we share knowledge then we can understand information. Anyone talking about wisdom as a higher level of knowledge should be taken out and shot for the good of the field (Dave Snowden)
Let us give the DIKW pyramid a ritual burial in the KM4Dev community. (Jaap Pels)
I have been surprised by the resurrection of this debate about data-informaton-knowledge-wisdom. For me these are well understood ideas within the community, though tacit with clear definitions being elusive, and possibly unnecessary. Of course when discussing the ideas within a client organisation or with students it is useful to talk about these, give examples, and give the pyramid. This is transferring knowledge by a kind of story-telling. What is most unhelpful, and counter to all notions of knowledge sharing and open discussion, is the remark by Dave Snowden - "Anyone talking about wisdom as a higher level of knowledge should be taken out and shot for the good of the field". Perhaps he should take his own medicine for the good of the field. (Patrick Hall)
If you can show me any example of wisdom management or so called higher levels of knowledge which is not shot through with pretension then I will happily withdraw the comment. In the meantime I have my shotgun primed, and have not intention of using it on myself (Dave Snowden)
I knew knowledge was a dangerous thing..... (Jaap Pels)
Hi all, Looking back , I don't think the hierarchical DIKW model added much value to my KM work in the past. However, I do find it important to have good working definitions to distinguish these terms when talking to management or other non-KM people, as they often use some of the terms interchangeably, which causes a lot of confusion language-wise. I would also tend to say that the idea of wisdom doesn't add value to our work as KM practitioners. Wisdom is simply the capacity to make right decisions on the basis of whatever is known and available. One could also put it as "applied knowledge". The capacity to make good decisions is surely something every human being should strive for, and as such is not particularly KM-related. It may be something we can learn, but it is surely nothing which can be "managed". As such, David is right that a term like "wisdom management" doesn't make any sense. (Johannes Schunter)
Hi, I agree that the wisdom component did not add value to KM work and that being said, it is often very useful for a KM-practitioner to have good reply at hand when discussions on knowledge and wisdom pop up. However, I don't think that 'wisdom' can be regarded as a concept that follows objective and universal categories. What are "good" and "wise" decisions"? Do the same standards for such "wisdom" apply for the political, societal and individual levels alike? To what extent do national interests, power relations, ideologies and resource conflicts influence "wise" decisions"? Obviously, values and norms are not shared worldwide, also constructs such as the Human Rights Declaration are de-facto not accepted as universal, let alone globally respected. KM every so often falls into the trap of treating human decision-making as intrinsically wise, provided that it is based on sufficient information and knowledge. Thus, KM risks to overlook, at least in parts, that neither knowledge nor wisdom are constructs that can be universally defined. At least not outside certain in-groups. Especially KM for Development and Peace should reflect debates on what norms and decisions can be considered wiser than others and on what norms and values these decisions are based, under what circumstances they are made, while knowing that these foundations are being constantly contested. By people that are equally convinced that their values, norms and decisions are wise. Cheers (Benjamin Kumpf)
Depends on the context .... metaphorical or real (Chris Burman)
I do agree with the point of view of Dave Snowded. The pyramid DIKW is based on the analogy of processing data bases, as if knowledge generation followed that pathway. Most knowledge that is useful for development is not dispersed in data, inside data bases, but structured in a diversity of forms such as stories, feelings, patterns, rules of thumb, analogies, concepts, narratives, insights, guesses and portfolio of cases, inside living brains, expressed in specific languages. The challenge is to have enough sensitivity, openness and intelligence to interact constructively with these forms of knowledge, that at first glance, looks like dissonances. (Sebastiao Mendonça Ferreira)
One great thing about KM4Dev is the way jokes weaved into serious knowledge sharing. Thanks Dave. (Charles Dhewa)
Talking about wisdom is always interesting, and there are related words such as sagacity that provide insight. The issue is when people want to see it as a higher order of knowledge, linear and hierarchical models were a common product of the last few decades which were dominated by systems dynamics, engineering approach and outcome based approaches (Senge is in there along with Hammer, Kaplan, Nonaka and others). Unfortunately they simply don't match up either to the history of philosophy (which has put more effort into thinking about knowledge and wisdom that the odd management "scientist") or Cognitive Science. Aside from being linked to a particular period of systems thinking approaches, which we are hopefully moving on from, its very culturally specific. It fails entirely to account of shamanistic knowledge, or the narrative traditions of Sufi philosophy and others. I could go on, but the you get the point; the DIKW pyramid is a culturally limited and inadequate model which is done more harm that good. The SECI model with its de facto focus on codification comes a close second, as I said the other day its the model that launched a thousand failed knowledge management initiatives. The main problem is its tendency to get people to think of knowledge as a thing rather than as a flow. With complexity theory, with the increasing levels of understanding from the cognitive sciences, evolutionary biology and elsewhere we are starting to get a radically new perspective on knowledge management, decision support and above all the creation of meaning that was previously possible. Its a pity to allow a field to be held back from these. Seeing information as a structured form of data is useful, the issue is what is informative to you? If I give you a chart of accounts and you have no knowledge of accountancy then it will remain data, we we share that knowledge then I can inform you. I developed this idea, building on the work of Boisot, in a paper called Complex Acts of Knowing which is available on the web site. It points out that shared context is key for information flow and the purpose of knowledge management is to create shared context (information, experience, education etc.) to all this to take place. Distinguishing between information and knowledge is more problematic as much knowledge is stored in the form of information, and information is generally the product of knowledge application. One way I have found useful, to help people distinguish between managing information and managing knowledge is to use a metaphor of the taxi driver and the map. - London taxi drivers spend two plus years learning the name of every street and route in London, there is only a 40% pass rate and at the end they are said to have the knowledge. They have spend time training their brain to handle a complex set of patterns that they can process intuitively and in an unstructured way. (their brain is physically altered by the way. Their knowledge is Zen like, intuitive, unarticulated and uncodified. As a result they are able to be far more effective than you driving a car with a map, but there is a massive investment in time to get there. - The Map user on the other hand is dealing with highly codified, symbolic knowledge. Acquisition cost is low, but execution is slow and not adaptable, Also the map does not contain everything you need to know (I discovered that to my cost returning from the Opera in New York late at night to Tarrytown. The map said I could make a fast interchange at 125th street; it didn't tell me that walking a couple of clocks on 125th street in a dinner jacket with an IBM thinkpad over your shoulder approaching midnight is hazardous undertaking. So, is it a problem for a map user or a taxi driver? A lot easier for people to understand that the linearity of DIKW and it avoids the pretension of wisdom management. (Dave Snowden)
Hear hear. The start of a paradigm shift starts with challenging the 'standard' models. Are there more models to trash? This is the chance. (Jaap Pels)
Dear all, I don't think it is about thrashing models, but about the wisdom or sagacity of when applying what. Knowing when you can use models (which?) to clarify, or when to let go and navigate, move as you see contours emerging. It certainly is also about knowledge of trade-offs and pitfalls. As such I think we (I for certain) too often lack the information, knowledge and wisdom to move agilely between domains, paradigms and sciences. Much needed is a real transdisciplinary knowledge and experience base and the ease to move between these depending on circumstances, needs and goals. Sometimes even more needed is a humbleness regarding one's own limited perspectives. (Wenny Ho)
I assume you would have been happy to thrash the terra-centric model of the Universe post Kepler/Galileo? Otherwise I fully agree with you on the need for greater trans-discliplinary knowledge and capability, although while I agree that all perspectives are limited, it does not follow that all perspectives have either value or validity. I think its important to consider ideas of coherence and with that incoherence. So it is possible to say that evolution is coherence, even though we don't know everything, while we can say that creationism is incoherent and not worthy of attention other that of sympathy for ignorance if not willful. (Dave Snowden)
It's important to understand the origins of a model to understand what it was designed for. The DIKW model emerged out of the struggles of computer science and information science through the late 1970s and early 1980s to legitimise themselves as strategic disciplines for the enterprise. For the data managers, the struggle was to get their organisations to treat data as a strategic resource, so establishing a relationship to information that fed decisions based on knowledge made a lot of sense. For the information managers the "downwards" link to data gave them a structure to work from, and the "upwards" link to knowledge gave them legitimacy in the eyes of senior management. So while it had utility for data and information managers, the hierarchy was never designed to accommodate the far more complex world uncovered by knowledge management, and as Dave points out, it completely fails to acknowledge the naturalistic ways that data, information and knowledge interact. For example, it does not reflect the fact that data is a very small subset of repeatable information, abstracted and structured for mechanical processing based on knowledge. Data is the product of a knowledge-driven, purposeful piece of design work. The DIKW model implies the opposite, that knowledge is the product of a series of operations upon data. The model also completely fails to account for the sea of knowledge activity in an enterprise which is never informationalised or structured as data. In the natural world, data is the product of a very small component of knowledge activity. From the data manager's point of view, the problem in the enterprise is "we have all of this data sitting around, think of what we could do with it if we could figure out how to squeeze insight out of it". While this is a legitimate question, the knowledge manager has discovered rather painfully, that you need to go back to the contexts that created the data and the knowledge activities the data supports, in order to figure out how the data can be manipulated for greater advantage. You can't get there by performing a series of logical transformations on the data to create information, and then another series of operations to create knowledge. So DIKW is a managerial model intended to explain how data can be leveraged as an enterprise resource. It has no practical value for guiding action beyond the D-I interface where it has limited value, explains almost nothing about knowledge, and its references to wisdom have always been completely without substantive or actionable content. Why did the hierarchy become received "wisdom" in KM? (1) It became received wisdom very quickly in computer sciences and information science literature, because it was a legitimising model - such models become entrenched very quickly. (2) The weaknesses of the model in relation to knowledge and wisdom were never tested in its first decade by which time it had become entrenched in the literature. (3) Writers for new knowledge management journals in the 1990s - as in any new discipline - suffered from "citation poverty" and so fell back on the received literature and mental models from their parent disciplines, without adequately questioning their applicability in this new context. (4) If you don't actually try to do anything based on the model, it serves a quite useful function in proffering a glib explanation of the distinctions between data information and knowledge and makes a pleasing nod at wisdom, so it seems like it has utility. (5) If you do try to structure your KM work using the model, you get rapid support from the technology side of KM (so the model must be ok), and when you run into problems with ground adoption and usability, it's easy to chalk this up to human intransigence and change resistance, rather than the poverty of the model as a framing device. It's interesting to note that some information scientists have recently been reassessing their attachment to their offspring: Jennifer Rowley has a good review of how the DIKW model has been used in the literature, and its ambiguities and weaknesses (Journal of Information Science April 2007) Martin Fricke has a sustained critique of the hierarchy concluding that it is "unsound and methodologically undesirable" (Journal of Information Science April 2009). Nikhil Sharma has a useful overview of the origins of the DIKW hierarchy at http://www-personal.si.umich.edu/~nsharma/dikw_origin.htm (Patrick Lambe)
I like the phrase of a colleague who works on water managment: We have oceans of data, rivers of information, some pools of knowledge and a very few drops of wisdom. Note, not a hierarchy but shifts in communication channels (Valerie Brown)
Good post Patrick, the one thinker I would add to your list is Boisot - he and I are doing work together on complexity (if anyone is in Hong Kong in a few weeks time you will see the pair of us and Karl Wiig together). His I-Space model which can be found in Knowledge Assets respects the IT tradition but moves beyond it. His latest collection of essays in Exploration in Information Space is also excellent. Ironically Knowledge Assets won the Ansoff Prize around a decade ago. One of the key sub-models there, which emerged from a conversation in a Barcelona Cafe over two long days contains that spectrum of knowledge from Zen-Narrative-Symbolic to which I referenced in an earlier post. DIKW works in the Symbolic alone, hence the issues we have with it. (Dave Snowden)
Hi Valerie It often looks like this from an enterprise perspective, but I happen to think it's mistaken. My own view is that in most cases there's a lot more knowledge (in and around the people) than information, and even less data. I won't comment on wisdom. One way to read the DIKW pyramid is in terms of the VISIBILITY and TANGIBILITY of the different elements, which is a different thing from their presence. From that perspective, your colleague (and the visual representation of the pyramid) makes sense. We do see a lot more data, it's easier to figure out where it is, and what to do with it. Information is less transparent and more complex to audit and map, knowledge is much more opaque, and wisdom auditing (people do actually sell this!) would be either a work of opinion or divination. So if DIKW just made claims about visibility it would have some use. That may be another reason why the DIKW pyramid has seemed so attractive: the visual form focuses us first on the more manageable (visible and tangible) elements and encourages us to work on those first as foundational elements - providing a visual justification for a quick win bias. The problem is that the knowledge ecosystem is more complex than DIKW allows, and focusing energies and effort on the easier stuff frequently fails to meet the most critical needs. The critical stuff is just not "seen" through a DIKW lens - Dave's comment on the work with Boisot gives a very interesting insight into this. (Patrick Lambe)
- Dear Patrick,*
- Hoping to meet you next week in Sin, let me first share my view. One of the main answer of our issue regarding” [km4dev-l] Knowledge generation & movement; What? Where? Why?” is rooted to the dynamic of DIKW model. *
- The DIKW model should bring to light that Knowledge **evolved as emergent behavior within human body as complex system, having consciousness and free will (mind and value) as well as behaving dynamically as Subject. On the other hand, DI not evolved but created or captured, should be and always treated as Object and only make people “well informed”. Knowledge and beyond, or KW,
making people “knowledgeable and wise” concerning their action and performance.*
- Knowledge exist only inside human being, never outside as Data and Information. Considering the nature of knowledge just mentioned, I preferred using the word “evolved” rather than “created or captured” as commonly used for Data/Information. Knowledge as Subject making KM is live and could becoming central in science.*
- In brief, what I’ve done at Mobee Knowledge CoP http://mobeeknowledge.ning.com , * *was to anticipate that shifting paradigm
of Knowledge, through following step by step act respectively : Re-postulating the Knowledge – Hybrid Definition of Knowledge – Human Enlightment Process-based KM Definition – Five Basic Implications of New Paradigm of Knowledge – Taxonomy & Metadata Management in KM – KM System Development map derived from Human System Biology . ( all of those “steps” you could get into one by one in detail through the following “gateway” links: http://mobeeknowledge.ning.com/forum/topics/knowledge-towards-2012-great -* *KNOWLEDGE TOWARDS 2012 : GREAT TURNING FROM MIND BRAIN TO CONSCIOUSNESS DNA and* *http://mobeeknowledge.ning.com/forum/topics/step-by-step-process-of -* *STEP BY STEP PROCESS OF KNOWLEDGE MANAGEMENT 2.0 MAP)*
- To summarize, let me state that DIKW model beyond doubt comprising two entities which have entirely different epistemology. DI derived from Physical Realities or Physical Universe, but, KW on the other hand derived from our Inner Universe or Knowledge domain. It will bring us to new DI-KW model, in which DI written separately with KW. This entirely new paradigm giving us many
new varieties that we do not realize before, and it seems could answer your statement : …. the hierarchy was never designed to accommodate the far more complex world uncovered by knowledge management, and as Dave points out, it completely fails to acknowledge the naturalistic ways that data, information and knowledge interact….. Also it will make soon your sentences becoming like this : …. It will have practical value for guiding action beyond the D-I interface where it has unlimited value, explains almost everything about knowledge, and its references to wisdom have always been completely with substantive or actionable content…..*
- On Wisdom in KM, wise is the human attribute but it’s still within Knowledge domain epistemologically as well as ontologically in their taxonomic content.*
- BTW, I enclosed (see the Attachment) my piece : “From Basic Knowledge to KM 2.0 in Practice” which include 1.”The Structure & Function of Physics – Knowledge Continuum”, 2.”Human System Biology (HSB)-based KM 2.0 Map template and its usage” *
Dear Dave, now shooting is NEVER a good solution! Sorry I missed the DIKW... i'll try to catch up. (Peter Bury)
I always thought DIKW was an abb for do it knowledge worker. (Jaap Pels)
Sorry; Do It Knwoledge Worker! (Jaap Pels)
Did anyone see this article today on HBR? http://blogs.hbr.org/cs/2010/02/data_is_to_info_as_info_is_not.html totally related to this convo! (Nancy White)
Is Weinberger on the KM4Dev list? The Problem with the Data-Information-Knowledge-Wisdom Hierarchy (Jaap Pels)
http://blogs.hbr.org/cs/2010/02/data_is_to_info_as_info_is_not.html and http://nsharma.people.si.umich.edu//dikw_origin.htm Look a lot like each other. I hate that when authors (Weinberger in this case) do not use references. Instead you get a list (By HBR) of what other surfers clicked next ... useless. (Jaap Pels)
Hi there, As others have manifested the linearity of the DIKW pyramid is questionable. Particularly, I prefer to follow the concepts of the old constructivist school, where it is suggested that knowledge is involved in transforming data into information. We could identify knowledge with sets of consensual beliefs in a given context. Like when we said the Earth is flat, or later that it was round, immobile, and the starts were circling around it. But where do these beliefs come? They are the result of the transactions between individuals or better say transactions "within" the community. What are these transactions; well they are observation, experimentation, tradition, etc, etc ... and the analysis of the anomalies. Information allows us to accumulate the outcome of these transactions. In that respect I differ from the suggestion that knowledge resides in the individual. It is true that the individual absorb the manifestations of these transactions, like for example "experience" and "conventions". And if so what is wisdom? As others have suggested, wisdom is the capacity to apply these collective believes in new situations. I had "new situations" otherwise; it would be just exercising experience. In one of the reactions to this mailing there was an example of the taxi driver versus the map. It is true that a map is a highly codified set of information. And it is true a map is incomplete but it allows us to drive in towns where we never have been before. In contrast most of the experience of the taxi driver in London is useless when he drives in Paris. The shortcomings of the maps were addressed by other way of codification, the city guides. And with the advent of the Web more codification were added with travellers' blogs, crowd sourcing rating hotels and restaurants, navigation systems in the car, etc. I think that the example of the taxi driver versus the map is relevant because it allows us to go further into the implicit versus the explicit, and the individual versus the collective. In that sense, I could venture to assume that Web 2.0 is the biggest codification adventure of mankind generating a mesh of information that approximates to knowledge. cheers (Alfonso Acuna)
Nancy Thanks so much for this - one of the best articles and discussions on knowlwedge and DIKW - relevant to all K4D. Sarah I wonder if it could be borrowed for the Journal? I hadn't realised that the concepts of Data, Information, Knowledge, and Wisdom have been reified as a hierachy and/or pyramid among the knowledge management set until David Snowden's outburst. It certainly seems it urgently needs deconstructing. The relationship between them is only cause-and effect, a sequence, a jigsaw, or a hieracrchy if it is so treated. The inter-relationships can also form a pattern, an image, a prediction, a synergy and a collage. For me , they form independant, crucial synergistic contributions to how humans think, and each one involves identity, meaning and learning. Thank Weinberger, the author for Elliot in 1934 <http://nsharma.people.si.umich.edu//dikw_origin.htm>: Where is the Life we have lost in living? Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in the information? "The Rock <http://www.wisdomportal.com/Technology/TSEliot-TheRock.html>" by T.S. Eliot <http://en.wikipedia.org/wiki/T._S._Eliot> (Valerie Brown)
Dear Patrick, My response to the K4D on the Weinberger paper gives my understanding of all this - I hadn't realised DIKW had become reified so firmly. Quite useful for some purposes, but also something to move on from! It seems I am likely to misss Singapore this trip, the flightd don't fit other things. Thank you for your invitation to talk - perhaps another time, or will you be in Canberra again? (Valerie Brown)... and later: Apologies to the list AGAIN for a personal note. My trigger finger is too fast for my own good. (Valerie Brown)
Thank you all for such a rich debate which finally seems to offer some useful light on one of the phoenixes of KM conversations. I really appreciate Patrick and Dave's (and others') inputs on the history and basic flaws of the DIKW model. I was just blogging about this (1) and there's a couple of things I wanted to come back on: - I wonder about the statement that information is the product of data and knowledge, or, put in non-reified terms, knowledge allows us to make sense of data and turn it into information. It is an interesting and stimulating perspective that I might adopt but don't you also think that data is separated from information as raw bits of text are separated from intentionally structured bits of text like books, articles, video documentaries etc. ? - As for knowledge, I personally prefer referring to it as the act of knowing rather than 'knowledge' indeed because the latter tends to reinforce the reification of knowledge as something tangible that can be managed, which I totally disagree with. Isn't it (knowing / knowledge) all about conjuring up all the things we have in ourselves to make (supposedly) better informed decisions, which could be ideas as they could be acts. This might relate to what you were saying Dave about knowledge as flow vs. knowledge as stock. Knowledge/knowing if anything would be the ability and activity to combine all elements to do something with the information we have at hand in a given situation. - Finally, on wisdom, although I also don't work with this concept in practice, how about it being accumulated and analysed - as in reflected upon - experience which allows us to make a better informed decision in a known or (even more blatantly) in an unknown context? Anyway, although this may be considered too linear, I will try to capture this conversation on the KM4DEV wiki because it's been too many times too many of us had to come back on this junction between knowledge, information and the likes without feeling itchy and some of these elements could be great to refer to at a later time. Many thanks again! (1) for those interested the post is on: http://km4meu.wordpress.com/2010/02/06/settling-the-eternal-semantic-debate-what-is-knowledge-what-is-information/ (Ewen Le Borgne)
You might want to read Boisot (previously referenced) who deals with this stuff well The point on information and data - its the process of abstraction and codification that creates information from data (and requires a shared knowledge base). The knowledge base (common levels of abstraction, understanding of the conventions of codification) are what allows that process to take place. No shared knowledge, the information is still data. My son is studying chemistry, my daughter anthropology/philosophy. I find my daughter's essays information as I studied both. On the other hand, despite having an O-Level in Chemistry what my son writes is just data to me, even when he gets an A/ I once wrote an article Complex Acts of Knowing (http://www.cognitive-edge.com/articledetails.php?articleid=13) so I agree with you on that phrase I'm happy if you want to talk about wisdom in the context of judgement (making choices etc. per your text) but that is one aspect there are several others. The whole point is that its not a linear process. You can have two boxes labeled DATA and INFORMATION and a double headed arrow connecting them (as it can go both ways); then a fussy cloud labeled knowledge between them. Wisdom may be the ability not to try to go beyond that (Dave Snowden)
Hi, Indeed - as I wrote before (1 Feb 2010, at 09:18) - to go from data to information you will need some knowledge (on how to do that), And that is enough falsiication to reject the DIKW linear model unless you black-box the at-hand / needed knowledge by divine intervention from information :-) Best, (Jaap Pels)
Can't resist sharing my 2 €cents of witchdom. There are 2 problems with the pyramid metaphor in DIKW (and Maslow's human needs likewise) a) the artificial hierarchy b) the notion of a linear sequence of transformations Both are false IMO. Second D,I,K are basically related to the same "things" taking/being given different states or forms, according to particular actors, circumstances, times, needs, applications. The passing of one state to another involves additional energy and substance change and loss (for the actor not the thing). The above may stand for wisdom even though the latter relates more to the application facet of DIK than its contents. Finally, in order to be comprehensive, the "model" lacks the negative companion to each of the element: non-data, -information, -knowledge, and -wisdom. Or if one prefers the black holes. My grandfather's knowledge of the very reason why trenches and hedges are not straight and wisdom that one should not change their position and shape but very carefully, was deemed "unscientific" belief and reactionary. We got no hedges along straight large trenches plus wind erosion and floods. (Michel Menou)
Dear all, Around August/September 2009, I was asked to facilitate a half day session on KM to a group of people representing 12 different NGOs/projects. The NGOs were partners in the Danish Cultural Project - a three year project supporting these organisations using creative/innovative means to highlight and address keys social issues in the Nepali Society for social transformation. The KM session was part of a 3 day capacity development workshop which was organised to help these organisations reflect on their 3 year experience with the project, document the experience and learnings for further strategic input. So daunted by this task, I had sought advice in this KM4Dev forum - where I received some useful and practical tips. Now with this ongoing discussion on DIKW, I was inspired to reflect on that particular experience... The participating organisations were really young ( some were established within the 3 yr project duration) with limited capacity. Many of them had had a session on KM at the beginning of the project, almost 3 yrs ago. I decided to focus on the session on discussing the relevance of KM for them, how they can start...where to start. Some of my thoughts on the half day process: -Participants easily shared and discussed on what they mean by "knowledge", several references were made to experiential learning based knowledge...as they said, unless you experience or do something, you wouldn't learn and "know". As they say in Nepali - "padera matra haina, parera janincha" - one doesn't only learn/know from reading but from experience. It was easy to relate to it as a concept. It was difficult to relate to at a more practical level - like they found it difficult to identify what explicit "knowledge" generated throughout the project cycle. -There was some confusion in the discussion of data/info/knowledge....something that is data for one was regarded as information by another - I gathered now, this is due to the pre-existing notion of the linear relationship among the three..that data leads to information and information gives you knowledge. -In an exercise, participants easily came up with a list of different forms/categories of data (that is-according to them) they had gathered in the project duration. There were some information identified. Most of them found it difficult to articulate/identify the " knowledge" , if any, that was generated in the process - e.g.there was a group of independent film makers - who had made films on indigenous practices. They would do research, identify practices among their ethnic community, document through videos/films, screen them in the community for feedback, use them as basis to generate community discussions, appreciation/promotion of indigenous practices. They shared the number of documentaries made, the number of screenings, the attendance at screenings, breakdown of the audience by caste, ethnicity, age, gender etc, They told interesting stories of their visits to the communities, how they "discovered" some of the practices in conversations with the elderly, their experiences/frustrations and insights of the film making process, and some shared how they had changed their work as they gained more experience. I asked them, now for your organisation, what is important here - as in what of this experience needs to be documented and managed and why ? they showed me their folders of all the logistical details of the process...how many films, how many screenings, composition of attendance. They have neatly documented those as evidence of work done - but no clear indication of why ? My realisation from this is: when there is investment in KM in local NGOs, I see the focus is in terms of the capacity development - in the infrastructure - computers, equipment, trainings, hiring a "knowledge/information officer" ,cabinets lined with files etc etc. This is done without much thinking on " What knowledge? from where ? and why?" without a learning strategy. And hence the challenge relating it to the organisation's work, vision and mission. So with some of these organisations, I hope to be able to continue the conversation of " what knowledge, where and why"...for in the changing socio-political climate of the country, these organisations are generating new knowledge...as social norms and values are being critically assessed, identities being explored and discovered and the nation is in the making. appreciate this discussion and all the sharing... (Amina Singh)
(in another discussion thread on the 'DIKWhat? swamp')
Having stuck my foot in this quagmire once already I will be foolish enough to do it again. The challenge in all this is our intentionality, our desire to get "there" from "here", be that in education, health, jobs, income, peace, security or whatever. [I am hunting in this swam unarmed!] To do that as more than a monk's solitary contemplation we have to work with others. That poses the first problem with respect to the stew/cloud of data, information, knowledge, context and wisdom. In social processes (getting there from here) their are no absolutes, and hence no agreement, as to the properties of "here", the starting point. There is likely to be disagreement with what exactly "there" means. Just how does one measure progress in the MDGs? There are no absolutes in social reality as there are in the physical properties of the elements (iron, copper, neon, oxygen, uranium, etc). If I need a hammer, iron will work, neon won't. If I want to improve village health the choice between a village health worker and trained medical personnel is more complex, more dependent on context, and offers more scope for disagreement. Even if we can agree on "here" and "there" we can still have wide disagreements of the path from here to there. Water, in general, is made up of two hydrogen atoms and one oxygen atom. Maternal and child health is made up of.......bits and pieces of this and that, all of which have other impacts. Choice is fraught with all sorts of complexities. Of course there is no natural linearity in all of this. Each aspect has its own dialectical properties of action-reflection-reaction, a process that both brings evidence to bear on the task at hand, and changes all of the elements of the context within which that task is being undertaken. Within this cloud of uncertainty one has to choose between the risks of evidence based decision making and some faith based decision making. I for one prefer the risks of evidence based decision making. One can learn from it. Faith based decision making leaves little scope for learning. At the end of the day some array of boxes on the shelf [D][I][K] got us where we are either by luck or be design. Luck takes little wisdom. Successful design takes a lot of wisdom. We can argue about what it is, and pretty much agree that it is not inside one of those boxes, nor should it simply be added to the right hand side of the [K] box, but we, as individuals and as communities had better pay some attention to where it comes from and how we deploy it, at least if we want to get beyond rhetoric to action, and move some bit toward there from here. (Sam Lanfranco)
(in yet another discussion thread on the 'KM4Dev and positive deviancy (with a little something on DIKW)' Dear All I've been re-reading Laxmi Pant's and Helen Odame's paper from the September 2009 issue of the KM4D Journal 'The promise of positive deviants: bridging divides between scientific research and local practices in smallholder agriculture' 5(2) pp. 160-172 which I really enjoyed when it first came out. Reading it again, it struck me that you could probably describe members of this KM4Dev community as "positive deviants". What are the similarities between members of KM4Dev and the positive deviants identified in the article? Well, here are some: - positive deviants act out against the structures and rules of the game in knowledge, application and regeneration - they help introduce new approaches to old organisational structures and institutional set-ups - they are powerful agents for change, such a bridging the divides between different sort of knowledge systems - they initiate change in spite of difficult social and organisational environments, full of unpredictable obstacles and interferences - they believe that challenging the status quo is one way to harness individual creativity and innovations Personally, these characteristics make me think of many members of this community. But, just as one man's meat is another man's poison - or indeed one person's wisdom is another person's folly (and I think the Iraq war is a good example of this - I've been very keen to make this point in the developing DIKW discussion!), I was hoping that you might be able to help me think about how to argue that KM4Dev members are "positive" deviants? Well, they are obviously not "negative deviants" in the strict sense that negative deviants are criminals but, if you accept that positive deviants find better solutions (see this quote from the Positive Deviance Initiative http://www.positivedeviance.org/ below), how can we argue that we are doing things "better"? What is "better" in the context of KM4Dev? Is it enough that we are trying to do things "better"? Positive Deviance is based on the observation that in every community there are certain individuals or groups whose uncommon behaviors and strategies enable them to find better solutions to problems than their peers, while having access to the same resources and facing similar or worse challenges. Hoping to hear from some of you. I've also put the abstract of the article below. Kind regards Abstract Positive deviants challenge existing organisational structures and institutional set-ups, and promote alternative approaches to solving seemingly intractable social problems, either playing direct role of a boundary spanner or indirect role as activists. However, these roles of positive deviants have not yet been recognised to its potential in international development because the legacy of deviancy theory lies on negative deviants, such as addicts and criminals. This paper investigates the promise of positive deviants to bridging scientific research and local practices using empirical evidence from community-based participatory research of rice, a crucial subsistence crop in the Chitwan district of Nepal. Non-profit private and public stakeholders worked as boundary spanners, specifically to initiate stakeholder interaction with non-traditional partners, in spite of the lack of enabling environments to do so. Similarly, one of the members of a farmers' group developed a rice variety from a handful of seeds taken from a scientific experimental plot, initially without the knowledge of participating scientists. This research suggests that positive deviants have ingenuity to innovate, deviating from norms particularly when social and organisational environments limit stakeholder interaction for learning and innovation. This paper concludes that the collective intelligence of positive deviants can sustain or even stimulate innovation permitting people to survive, experiment new ways of doing things and even improve their living conditions under adverse social, political and agro-ecological circumstances. (Sarah Cummings)
I too like the article very much. My work is almost entirely with "positive deviants" and two of the PhDs I am supervising are working on the same themes in agricultural innovation and community change (respectively). Of course, I am one myself. Other terms I have collected organisational termites; circuit breakers, outriders, whistleblowers, the joker in the pack, marchers to a different drum, one who needs 'cresses from a far stream'. Ferreira's article on the new enlightenment in the same issue gives some needed criteria for "positive" and as Sarah says, "better". With my interest in the community-of-practice that this all represents, I am thinking think that the criteria should/could be drawn from the transparent ethics of the individual for each action. Sarah has described some characterisitc actions, but for each one we need to know the ethical purpose. Comments? . (Valerie Brown)
Hi Valerie, Sarah and all KM4Devers Have you had the opportunity of knowing the book of Elinor Ostrom "Understanding Knowledge as a Commons"? I think that her approach "knowledge as a commons" and the set of authors she gathered in her book can be very useful for the reflections we are doing in KM4Dev. Her book is mostly about academic knowledge, but most of it can be applied to any kind of useful knowledge. best wishes (Sebastiao Mendonça Ferreira)
Thanks for sharing this Sarah. I had mixed feelings as I read this, because it seemed to me to conflate the very concrete, problem-solving focus of the positive deviant with an ideological position, and the two do not necessarily go together. In that sense, the article challenged my sense of positive deviance (not necessarily a bad thing). The emergence of positive deviance within international development started as one of finding the people within a community who solve problems better. The positive deviance initiative then set about finding a process to help communities adopt those better solutions from within. Importantly, the change precedes empowerment, and the positive deviant (the person in the village with the more effective child-care practices) frequently never intended to challenge normal ways of doing things or inspire social change. Critically, empowerment is frequently an UNINTENDED consequence of the positive deviants' actions (this becomes clear in the article). However, as I read into the article, I realised that this motivation to rethink the status quo is a primary driver behind positive deviance as an approach. I really liked the way the paper ends: "The change management for rural development should... facilitate collective intelligence of such deviants through deeper processes of deliberation among themselves and with inflexible conformists." I still believe that we should not confuse the positive deviant who originates an innovative solution to a problem shared within a community (who may just be focusing on the problem), and the positive deviance practitioner who seeks to release these innovations for productive social impact. So I think there are two questions within your question: are we positive deviants in the sense that we have developed improved approaches and results in relation to shared problems, or in the sense that we help to find and release change into society? The first is very concrete (the attractive thing about positive deviance is that "better" is a statistical deviation too), the second still very aspirational I feel. I believe strongly in the power of aspiration, but I worry about getting distracted by the aspiration (and its characteristics) and forgetting the concrete. The power of the positive deviance approach is its in ability to hold the concrete (solutions) and the aspiration (empowerment) together. This is a case where I would look to the strength of the process more than the characteristics of the people involved. I suppose it's a little bit like the use of Open Space Technology. It's the process itself that makes Open Space so effective; it often works in spite of the characteristics of the facilitator. Yes, "good" OST facilitators have certain characteristics, but those characteristics don't help us to understand the true power of the approach. Best (Patrick Lambe)
This is a very exciting and interesting discussion. We recently had a SID meeting here on appreciative inquiry which also grappled with (or probably more accurately - stabbed at) many of these issues. (Although I would say the term "deviant" is not very helpful in terms of talking to anyone about these ideas in the real world; can we have a term that does not seem to be as perjorative?) Let me flag an experience that dates to the late 1970s and early 80s which really at the end of the day was an attempt to harness the positive deviant concept as a driver for major change in resource management. In fact, this change was SO fundamental that it affected USAID's approach to natural resource management for the next 20 years, and then became totally ingrained into AID's planning and design processes. But like the cargo cult or the Easter Island heads, the intent of the originators was mostly lost in the haze of time; institutionally within USAID the purpose of these driving principles has been muddied and to a large degree forgotten. As USAID though moves to go "back to the future" by reemphasizing results-based programming, the lessons from that earlier "proto-positive deviancy" approach would be worthwhile to revive. Your emails give me some ideas on how to do just that.
Let me very briefly outline what the team of French, American and African field practitioners did then (and which I THINK I described in more detail somewhere much earlier in KM4DEV): In the 1920s, the French imposed a Forest Code on much of Sahelian Africa, with the hope that it would protect the forests which played key watershed and resource conservation roles, and which were increasingly coming under pressure from herders and others. The law essentially made all trees the property of the state, and not something which the individual could just use. The objective was laudable but had of course the reverse effect, essentially the classic common property problem. If I don't own it, why should I care if it gets managed? Turning the forest service into a police force led essentially to increased corruption, and decreased management. Over the next 50 years, as desertification intensified and as forest land became more at risk, it became obvious that the Forest Code was partially to blame. But some farmers were experimenting with various innovative resource management approaches that were NOT being used by others. In some instances they were within a region where the broader community or organization or spatial unit decided just to ignore the code (essentially institutional or community deviance, not individual deviance). So a group of practitioners decided to do quick visits and interviews to anyone they heard about who was doing something differently. They purposefully did NOT look at project sites, but only went to where word of mouth identified an individual or a family which had undertaken some innovation. They didn't much care to capture the size of the change, or to study in depth the agronomic science behind the changes. All they were looking for was an answer to the question: why this person? Is he/she truly a "deviant" or are the broader cultural, social, institutional signals that were enabling this person to do something different. Essentially what were the enabling conditions which helped to lead to this risk-taking? It led to a series of papers called the Opportunities studies, which in hindsight were incredibly influential in the region, but are almost impossible to find anymore, having been written just before the PC and www age. What the development assistance world concluded from these studies was that there were indeed some underlying conditions which seemed to influence innovation in semi-arid Africa. And while donors simply are not able to effectively assist people one at a time, they COULD work to put these conditions in place, and then see if innovation would occur WITHOUT a heavy hand from the donor at the "retail", farmer by farmer by farmer level. I am copying a couple of folk here who know far more about this than I do, but it strikes me that this approach does indeed reflect some of the "positive deviance" ideas being outlined both in the emails and the initial KM4DEV paper. Any additions/corrections/subtractions to my summary above would be welcomed!! One key point though: as with the Easter Island heads, simply having the artifact of the innovation (pictures of the farmer and a description of the changes to ag practices they adopted, etc etc) is not enough. The KNOWLEDGE is not simply a factoid about a practice that was used successfully by someone who was bucking the system and conventional wisdom. What really matters is an understanding of WHY that individual did indeed innovate, and whether any of the conditions that led to the innovation and its success can be replicated. And often that's not the knowledge that's being saved. (Tony Pryor)
I like very much the idea of looking at the underlying conditions for an innovation. One of the steps in a positive deviance initiative process is to assess the innovation for wider transferability (this should be done by the community owning the problem). However, from a policy point of view, I can see that it could be very powerful to look across a number of successful positive deviations at underlying conditions. We're probably straying into the realm of complexity here, so it might not be the case that you could successfully replicate those conditions, but you could learn something about why some approaches succeed and some fail. I would be fascinated to learn more about how this all worked out in the USAID case. (Patrick Lambe)