CYNEFIN framework

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CYNEFIN Framework

NOTE: CYNEFIN Framework is to be pronounced as kuh-NEV-in

Acronym

None

Alternate name(s)

None

Main dependent construct(s)/factor(s)

• Effectiveness of decision-making and problem-solving.

Corresponding explanation is as follows:

• The main dependent construct/factor when using the Cynefin Framework in the context of Information Systems would be the effectiveness of decision-making and problem-solving. The framework is designed to help individuals and organizations make sense of complex and uncertain situations and to tailor their approach to decision-making based on the nature of the problem at hand.
• In the context of Information Systems, effective decision-making and problem-solving can have a significant impact on an organization's ability to manage its technology infrastructure, maintain data security, and adapt to changing technology trends. By using the Cynefin Framework, organizations can improve their ability to navigate complex and uncertain situations, identify potential solutions, and make informed decisions that support their overall goals and objectives.
• Therefore, the effectiveness of decision-making and problem-solving would be the main dependent construct/factor when using the Cynefin Framework in the context of Information Systems.

Main independent construct(s)/factor(s)

• Nature of the problem or situation being addressed.

Corresponding explanation is as follows:

• The main independent construct/factor when using the Cynefin Framework in the context of Information Systems would be the nature of the problem or situation being addressed. The Cynefin Framework is designed to help individuals and organizations make sense of complex and uncertain situations by categorizing them into one of five domains: Simple, Complicated, Complex, Chaotic, and Disorder.
• The nature of the problem or situation being addressed determines which domain it falls into and therefore how it should be approached. For example, a technical issue that has a clear cause-and-effect relationship and a straightforward solution would fall into the Simple domain, while a cybersecurity threat that is unpredictable and has multiple possible outcomes would fall into the Complex domain.
• Therefore, the nature of the problem or situation being addressed is the main independent construct/factor when using the Cynefin Framework in the context of Information Systems.

Concise description of theory

The Cynefin Framework was created in 1999 by Dave Snowden when he worked for IBM Global Services. Cynefin framework is a decision-making approach which draws its strength from:

1. Systems theory: is a multidisciplinary field that studies how systems interact with their environment and with other systems
2. Complexity theory: is a branch of systems theory that focuses on how complex systems emerge from simple interactions among agents
3. Network theory: is a mathematical field that analyses how networks are structured and function
4. Learning theory: this theory could be any about one or more psychological theories that explain how humans acquire and process knowledge. The primary five categories in learning from which any learning theory is drawn upon are: Cognitive Learning, Behaviorism Learning, Constructivism Learning, Humanism Learning, Connectivism Learning

Above four theories (system, complexity, network, learning theory) help explain how systems behave and evolve under different conditions of order and disorder.

The Cynefin framework uses these theories to categorize situations into different domains based on their level of complexity and predictability.

Each domain has different implications for decision-making and problem-solving.

Generic context

The phrase "one-size-fits-all" is well known adage among ‘problem solving’ circles in any industry. And most effective leaders understand that their actions are influenced by the prevailing situation. However, the actual challenge is in knowing, which approach should one use in a given situation? And are there any professional tips to avoid making the wrong decision?

Cynefin (pronounced as kuh-NEV-in) is a Welsh word meaning habitat, haunt, acquainted, familiar. Cynefin framework has been described as a "sense-making device". So, the idea of the Cynefin framework is that, it offers decision-makers a "sense of place" from which the leaders can view their perceptions. The Cynefin Framework consists of five domains:

• Clear (earlier term used was ‘Simple’, until it got changed)
• Complicated
• Complex
• Chaotic
• Disorder

‘Information Systems’ context

The Cynefin Framework is a decision-making model that helps individuals and organizations make sense of complex and uncertain situations. In the context of information systems, the framework can be used to understand the nature of the problems faced by organizations in managing information and technology.

• Clear/Simple: This domain is characterized by clear cause-and-effect relationships, and the solution is obvious and straightforward. In the context of information systems, examples might include routine IT maintenance or troubleshooting basic hardware or software issues.
• Complicated: This domain is characterized by a high level of expertise required to understand the problem and identify potential solutions. In the context of information systems, examples might include diagnosing and fixing more complex technical issues or designing and implementing a new software system.
• Complex: This domain is characterized by a lack of clear cause-and-effect relationships and unpredictable outcomes. In the context of information systems, examples might include addressing cybersecurity threats, managing large-scale data migrations, or adapting to rapidly changing technology trends.
• Chaotic: This domain is characterized by complete disorder and unpredictability. In the context of information systems, examples might include responding to a major system outage or cybersecurity breach.
• Disorder: This domain represents a state of uncertainty where it is unclear which of the other domains the problem belongs to. In the context of information systems, examples might include situations where the organization is facing a new and unfamiliar problem or where there is disagreement among stakeholders about the nature of the problem.

By understanding which domain, a problem falls into, IS organizations can tailor their approach to decision-making and problem-solving. For example, in the Simple domain, an organization might use standard operating procedures or checklists to address the issue, whereas in the Complex domain, it might use experimentation and iterative problem-solving to explore potential solutions. The Cynefin Framework can therefore help organizations to navigate the challenges of managing information systems in an increasingly complex and unpredictable environment.

Diagram/schematic of theory

• Figure 1: Cynefin Framework (Source: Wikipedia)
• Image credits: By Tom@thomasbcox.com - Own work - a re-drawing of the prior artwork found here (https://commons.wikimedia.org/wiki/File:Cynefin_as_of_1st_June_2014.png) that incorporates more recent changes, such as renaming "Simple" to "Clear"., CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=123271932

Cynefin Framework

.

Originating author(s)

It was developed and published in the Harvard Business Review in 2007 by:

• David J. Snowden
• Mary e. Boone

Seminal article(s)

1. Sheth, J. N; & Stellner, W. H. (1979). Psychology of Innovation Resistance: The less developed concept (LDC) in diffusion research (No. 622). Urbana-Champaign, IL, USA: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign. Permalink: https://hdl.handle.net/2142/26627
2. S. Ram (1987), A Model of Innovation Resistance, in NA - Advances in Consumer Research Volume 14, eds. Melanie Wallendorf and Paul Anderson, Provo, UT: Association for Consumer Research, Pages: 208-212. https://www.acrwebsite.org/volumes/6688/volumes/v14/NA-14
3. Ram, S. and Sheth, J.N. (1989), Consumer Resistance to Innovations: The Marketing Problem and its solutions, Journal of Consumer Marketing, Vol. 6 No. 2, pp. 5-14. https://doi.org/10.1108/EUM0000000002542

Originating area

Strategy – Leadership Decision Making

Level of analysis

Group or System

Links from this theory to other theories

1 liner with links to other theory. Example: This theory is different from ‘Diffusion of Innovations Theory’, which is also a popular innovation-based theory used in context of IS – Information Systems

Key References Outside IS Research Area

1. Heidenreich, S. and Kraemer, T. (2016), Innovations—Doomed to Fail? Journal of Product Innovation Management, Vol 33: Pages 277-297. https://doi.org/10.1111/jpim.12273
2. Ju, N., Lee, KH. (2020), Consumer resistance to innovation: smart clothing (Fashion and Textiles), International Journal of Interdisciplinary Research, Volume 7, 21. https://doi.org/10.1186/s40691-020-00210-z
3. Mohd Sadiq, Mohd Adil, Justin Paul (2021), An innovation resistance theory perspective on purchase of eco-friendly cosmetics, Journal of Retailing and Consumer Services, Volume 59, 102369, ISSN 0969-6989, https://doi.org/10.1016/j.jretconser.2020.102369
4. Dan Huang, Alexandra Coghlan, Xin Jin (2022), A process perspective on consumer innovation resistance to Airbnb: A narrative approach, International Journal of Hospitality Management, Volume 107, 103306, ISSN 0278-4319, https://doi.org/10.1016/j.ijhm.2022.103306

IS articles that use the theory

1. Chung, K. C., & Liang, S. W. J. (2020). Understanding factors affecting innovation resistance of mobile payments in Taiwan: An integrative perspective. Mathematics, 8(10), 1841. https://doi.org/10.3390/math8101841
2. Kaur, P; Dhir, A; Ray, A; Bala, P.K; and Khalil, A. (2021), Innovation resistance theory perspective on the use of food delivery applications, Journal of Enterprise Information Management, Vol. 34 No. 6, pp. 1746-1768. https://doi.org/10.1108/JEIM-03-2020-0091
3. Zhenya Tang, Leida Chen (2022); Understanding seller resistance to digital device recycling platform: An innovation resistance perspective, Electronic Commerce Research and Applications, Volume 51, 101114, ISSN 1567-4223, https://doi.org/10.1016/j.elerap.2021.101114
4. Shishan, F., Hmoud, H., Zaidan, H., Qasem, Z. (2022). The Innovation Resistance Theory: The Case of Cryptocurrencies. In: Musleh Al-Sartawi, A.M.A. (eds) Artificial Intelligence for Sustainable Finance and Sustainable Technology. ICGER 2021. Lecture Notes in Networks and Systems, vol 423. Springer, Cham. https://doi.org/10.1007/978-3-030-93464-4_45
5. Park, E. H., Werder, K., Cao, L., & Ramesh, B. (2022). Why do Family Members Reject AI in Health Care? Competing Effects of Emotions. Journal of Management Information Systems, 39(3), 765–792. https://doi.org/10.1080/07421222.2022.2096550

External links

1. https://solvinnov.com/resistance-of-innovation/ - a website maintained by Dr. Adam Tacy, dealing with various topics of innovation and has a dedicated section on IRT
2. An exploratory study of mobile banking services resistance, July 2012, International Journal of Mobile Communications 10(4):366-385, https://doi/10.1504/IJMC.2012.048136 -- this doesn’t directly use the IRT theory but makes a good contextual reading on innovation resistance
3. NADINE HIETSCHOLD, RONNY REINHARDT, SEBASTIAN GURTNER (2020), Who put the “NO” in Innovation? Innovation resistance leaders’ behaviour and self-identities, Technological Forecasting and Social Change, Volume 158, 120177, ISSN 0040-1625, https://doi.org/10.1016/j.techfore.2020.120177 -- this doesn’t directly use the IRT theory but makes a good contextual reading on innovation resistance
4. https://hbsp.harvard.edu/product/W18034-PDF-ENG – Apple Watch: Managing Innovation Resistance, a teaching business case study by Tania Bucic, Gaganpreet Singh
5. https://www.diva-portal.org/smash/get/diva2:865523/FULLTEXT01.pdf -- Attitudes of French consumers towards breakthrough innovation – A qualitative study about Google Glass, a 2015 Masters-degree-thesis by student authors Allison Le Garrec and Jérémy Torregrosa, under their Supervisor Peter Hultén, of college Umeå School of Business and Economics
6. https://www.google.co.in/books/edition/Information_Systems_Innovation_and_Diffu/B2K9W5sqvKEC?hl=en&gbpv=0&kptab=overview – Google Books – Larsen, T. J. (1998). Innovation: A Framework for Research and Practice. Information systems innovation and diffusion: Issues and directions, 411.

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