Cynefin framework

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Domains of the Cynefin framework

The Cynefin (/ˈkʌnvɪn//kun-EV-in) framework is an approach to decision-making and knowledge management that helps managers and policy makers incorporate complexity into their decisions. Developed in the early 2000s within IBM, it has been described as a "sense-making device".[1]

Cynefin offers five decision-making contexts or "domains"—simple, complicated, complex, chaotic, and disorder—that enable decision-makers to identify how they perceive aspects of a situation. This allows them to make sense of their own and other people's behaviour.[2] The framework draws on research into systems theory, complexity theory, network theory and learning theories.[3]



Cynefin is a Welsh word meaning haunt, habitat, acquainted, accustomed, familiar.[4] It carries with it the idea of rootedness—temporal, physical, cultural or spiritual.[5] The word is similar in meaning to Heimat in German and has been compared to the Maori word turangawaewae, a place to stand.[6][7] The concept of the Cynefin framework is that it offers decision-makers a "sense of place" from which to view their perceptions.[8]


Dave Snowden, then of IBM Global Services, began work on a Cynefin model in 1999 to help manage intellectual capital within the company.[a] He continued developing it as European director of IBM's Institute of Knowledge,[11][12] and later with Cynthia Kurtz at the IBM Cynefin Centre for Organizational Complexity, established in 2002, where Snowden was director and Kunz the principal researcher.[b] They described the framework in detail the following year in a paper, "The new dynamics of strategy: Sense-making in a complex and complicated world", published in IBM Systems Journal.[1][14][c] The Cynefin Centre—a network of members and partners from industry, government and academia—began operating independently of IBM in 2004.[15]



Cynefin offers five contexts or "domains" of decision-making: four spaces and a centre of disorder.[1][d] These give managers a "sense of place", write Larry Browning and Roderick Latoza, from which to "imagine narratives about what happened, what could have happened, and how to act differently in future".[8] The domains on the right, simple and complicated (above), are "ordered": cause and effect are known or can be discovered. The domains on the left (complex and chaotic) are "unordered": cause and effect can be deduced only with hindsight or not at all.[16] The domain names have changed over the years: Kurtz and Snowden (2003) referred to the simple and complicated domains as known and knowable,[1] and since 2014 Snowden has used obvious instead of simple.[17]


Since 2014 Snowden has called the simple domain obvious.[17] Early versions of Cynefin used known and knowable instead of simple and complicated.[1]

The simple domain represents the "known knowns". There are rules (or best practice), the situation is stable, and the relationship between cause and effect is clear: if you do X, expect Y. Cynefin describes this type of context as "sense–categorize–respond": establish the facts ("sense"), categorize, then respond by following the rule or applying best practice.[18][19]

According to Thomas A. Stewart, "[t]his is the domain of legal structures, standard operating procedures, practices that are proven to work. Never draw to an inside straight. Never lend to a client whose monthly payments exceed 35 percent of gross income. Never end the meeting without asking for the sale. Here, decision-making lies squarely in the realm of reason: Find the proper rule and apply it."[20]


The complicated domain consists of the "known unknowns". The relationship between cause and effect requires analysis or expertise; there is a range of right answers. The framework recommends "sense–analyze–respond": assess the facts, analyze, and apply the appropriate good operating practice.[18]

Stewart writes: "Here it is possible to work rationally toward a decision, but doing so requires refined judgment and expertise. ... This is the province of engineers, surgeons, intelligence analysts, lawyers, and other experts. Artificial intelligence copes well here: Deep Blue plays chess as if it were a complicated problem, looking at every possible sequence of moves."[20]


The complex domain represents the "unknown unknowns". Cause and effect can only be deduced in retrospect. There are no right answers: "rather, instructive patterns emerge if the leader conducts experiments that can safely fail." Cynefin calls this "probe–sense–respond".[18]

"Complex systems, battlefields, markets, ecosystems, corporate cultures are impervious to a reductionist, take-it-apart-and-see-how-it-works approach", Stewart writes, "because your very actions change the situation in unpredictable ways. ... [T]he idea is to allow patterns to surface and trust your gut to recognize them." Hard cases for insurance companies are one example: "the best all do the same thing: Dump the file and spread out the contents".[20]


In the chaotic domain, cause and effect are unclear. Events in this domain are "too confusing to wait for a knowledge-based response", writes Patrick Lambe. "Action—any action—is the first and only way to respond appropriately."[21] In this context, managers "act–sense–respond": act to establish order; sense where stability lies; respond to turn the chaotic into the complex.[18] (Cynefin uses chaotic in the ordinary sense, rather than the sense used in chaos theory.)[22]

The September 11 attacks were an example of the chaotic category.[18] Stewart offers others: "the firefighter whose gut makes him turn left or the trader who instinctively sells when the news about the stock seems too good to be true." One crisis executive said of the collapse of Enron: "People were afraid. They were either misdirected or undirected. Decision-making was paralyzed. ... You've got to be quick and decisive—make little steps you know will succeed, so you can begin to tell a story that makes sense."[20]


The dark disorder domain in the centre represents situations where there is no clarity about which of the other domains apply. By definition it can be hard to see when this domain applies. "[M]ultiple perspectives jostle for prominence, factional leaders argue with one another, and cacophony rules", according to Snowden and Boone (2007). "The way out of this realm is to break down the situation into constituent parts and assign each to one of the other four realms."[18]

Moving through domains[edit]

As knowledge increases, Kurtz and Snowden write, there is a "clockwise drift" from unknown to known, from chaotic through complex and complicated to simple. Similarly, a "buildup of biases", lack of maintenance or complacency can cause a "catastrophic failure": a clockwise movement from simple to chaotic, represented by the "fold" between those domains. There can be counter-clockwise movement as people die and knowledge is forgotten, or as new generations question the rules, or a counter-clockwise push from chaotic to simple when a lack of order causes rules to be imposed suddenly.[1][18]

Applications and reception[edit]

Cynefin was used by its IBM developers in policy-making, product development, market creation, supply chain management, branding and customer relations.[1] Others used it later to analyse the impact of religion on policymaking within the George W. Bush administration,[23] emergency management,[24] network science and the military,[25] the management of food-chain risks,[26] homeland security in the United States,[27] aspects of measurement within the British National Health Service,[28] medical knowledge,[29] and agile software development.[30]

Criticisms of Cynefin include that terms such as known, knowable, sense, and categorize are ambiguous,[31] that the model is difficult and confusing, it needs a more rigorous foundation, and it covers too limited a selection of possible contexts.[32]

See also[edit]


  1. ^ Snowden (2000): "An early form of the Cynefin model using different labels for the dimension extremes and quadrant spaces was developed as a means of understanding the reality of intellectual capital management within IBM Global Services (Snowden 1999a)."[9][10]
  2. ^ IBM Systems Journal (2003): "Cynthia F. Kurtz ... is Principal Researcher for IBM's Cynefin Centre for organizational complexity. ... She moved to the [IBM] Institute for Knowledge Management in 2001 to work on both narrative programs and complexity programs before helping found the Cynefin Centre in 2002. ... David J. Snowden ... is the director of IBM's Cynefin Centre shortly to be based in Cardiff University, Wales. ... He was a director in IBM's Institute for Knowledge Management before founding the Cynefin Centre in 2002."[1]:483

    IBM Global Services (2002): "The Cynefin Centre for Organisational Complexity is a global network of members and partners applying complexity theory to organisations by developing a diverse portfolio of pragmatic sensemaking methods and models that can help solve problems for which structured approaches have failed."[13]

  3. ^ Bob Williams, Richard Hummelbrunner, Systems Concepts in Action (Stanford University Press, 2010): "Developed by David Snowden and Cynthia Kurtz when they were at the IBM's Institute of Knowledge Management, Cynefin identifies four behaviors a situation can display ..."[3]
  4. ^ Williams and Hummelbrunner (2010): " ... Cynefin identifies four behaviors a situation can display: simple, complicated, complex, and chaotic. This terminology is not new; the systems literature has used it for decades. However, in Cynefin the behaviors and the properties that underpin these four states are not entirely drawn from systems theories or even theories of chaos and complexity. Cynefin draws heavily on network theory, learning theories, and third-generation knowledgement management.
    "Crucially, compared with many network and company approaches, Cynefin also takes an epistemological as well as an ontological stance. Similar to the Soft Systems and Critical Systems traditions ... Cynefin explores how people perceive and learn from situations."[3]


  1. ^ a b c d e f g h Kurtz, Cynthia F.; Snowden, David J. (2003). "The new dynamics of strategy: Sense-making in a complex and complicated world" (PDF). IBM Systems Journal. 42 (3): 462–483. doi:10.1147/sj.423.0462. 
  2. ^ Williams, Bob; Hummelbrunner, Richard. (2010). Systems Concepts in Action: A Practitioner's Toolkit, Stanford, CA: Stanford University Press, 10, 173.
  3. ^ a b c Williams and Hummelbrunner (2010), 163–164.
  4. ^ "Cynefin". Welsh-English / English-Welsh On-line Dictionary. University of Wales. Retrieved 24 November 2016. 
  5. ^ Oates, Matthew (2015). In Pursuit of Butterflies: A Fifty-year Affair. Bloomsbury Publishing.
  6. ^ Lane, Eifiona Thomas, et al. (2015). "Re-creating and celebrating place(s) in designated space(s): the case of Wales", in Joost Dessein, et al. (eds.) Cultural Sustainability and Regional Development. Routledge, 190.
  7. ^ Berger, Jennifer Garvey; Johnston, Keith (2015). Simple Habits for Complex Times. Stanford, CA: Stanford University Press, 236–237, n. 5.
  8. ^ a b Browning, Larry; Latoza, Roderick (31 December 2005). "The use of narrative to understand and respond to complexity: A comparative analysis of the Cynefin and Weickian models", Emergence: Complexity and Organization, 7(3–4): 32–39 (last modified: 23 November 2016).
  9. ^ Snowden, David (October 1999). "Liberating Knowledge", in Liberating Knowledge, CBI Business Guide, London: Caspian Publishing.
  10. ^ Snowden, David (2000). "The Social Ecology of Knowledge Management", in Charles Despres, Daniele Chauvel (eds.), Knowledge Horizons, Butterworth–Heinemann (hereinafter Snowden 2000), 239 (shorter version).
  11. ^ Snowden 2000, 237–266; also here.
  12. ^ Snowden, Dave (May 2002). "Complex Acts of Knowing: Paradox and Descriptive Self Awareness", Journal of Knowledge Management, 6(2), 100–111. doi:10.1108/13673270210424639
  13. ^ "The Cynefin Centre for Organisational Complexity", IBM, archived 14 June 2002; "Membership", IBM, archived 10 August 2002.
  14. ^ Quiggin, Thomas (2007). "Interview with Mr. Dave Snowden of Cognitive Edge", Seeing the Invisible: National Security Intelligence in an Uncertain Age. Singapore: World Scientific Publishing Co., 212.
  15. ^ "The Cynefin Centre: Life after IBM", KM World, 14(7), July/August 2005.
  16. ^ Koskela, Lauri; Kagioglou, Mike (2006). "On the Metaphysics of Production". Proceedings of the 13th Annual Conference on Lean Construction, Sydney, Australia, July 2005 (37–45), 42–43.
  17. ^ a b Berger and Johnston (2015), 237, n. 7.
  18. ^ a b c d e f g Snowden, David J.; Boone, Mary E. (November 2007). "A Leader's Framework for Decision Making". Harvard Business Review, 69–76.
  19. ^ Williams and Hummelbrunner (2010), 165.
  20. ^ a b c d Stewart, Thomas (November 2002). "How to Think With Your Gut", Business 2.0 (1–5), 4–5.
  21. ^ Lambe, Patrick (2007). Organising Knowledge: Taxonomies, Knowledge and Organisational Effectiveness. Oxford: Chandos Publishing, 136.
  22. ^ Berger and Johnston (2015), 237, n. 11.
  23. ^ O'Neill, Louisa-Jayne (2004). "Faith and decision-making in the Bush presidency: The God elephant in the middle of America's livingroom" (PDF). Emergence: Complexity and Organisation. 6 (1/2): 149–156. 
  24. ^ French, Simon; Niculae, Carmen (March 2005). "Believe in the Model: Mishandle the Emergency". Journal of Homeland Security and Emergency Management. 2 (1). doi:10.2202/1547-7355.1108. 
  25. ^ Verdon, John (July 2005). "Transformation in the CF: Concept towards a theory of Human Network-Enabled". Ottawa: National Defence, Directory of Strategic Human Resources.
  26. ^ Shepherd, Richard; Barker, Gary; French, Simon; et al. (July 2006). "Managing Food Chain Risks: Integrating Technical and Stakeholder Perspectives on Uncertainty". Journal of Agricultural Economics. 57 (2): 313–327. doi:10.1111/j.1477-9552.2006.00054.x. 
  27. ^ Bellavita, Christopher (October 2006). "Shape Patterns, Not Programs", Homeland Security Affairs, II(3), 1–21.
  28. ^ Mark, Annabelle L. (November 2006). "Notes from a Small Island: Researching Organisational Behaviour in Healthcare from a UK Perspective", Journal of Organizational Behavior, 27(7), 851–867. doi:10.1002/job.414 JSTOR 4093874
  29. ^ Sturmberg, Joachim P.; Martin, Carmel M. (31 October 2008). "Knowing – in Medicine", Journal of Evaluation in Clinical Practice, 14(5), 767–770. doi:10.1111/j.1365-2753.2008.01011.x
  30. ^ Pelrine, Joseph (March 2011). "On Understanding Software Agility: A Social Complexity Point Of View" (PDF). Emergence: Complexity & Organization. 13 (1/2): 26. 
  31. ^ Williams and Hummelbrunner (2010), 182.
  32. ^ Firestone, Joseph M.; McElroy, Mark W. (2011). Key Issues in the New Knowledge Management. Abingdon: Routledge, 132–133 (first published 2003).