Tactical, Operational & Strategic Analysis of Markets, Competitors & Industries
I have started a new blog named Rethinking Competitive Intelligence that is about, you guessed it, rethinking the field of competitive intelligence. Rethinking CI is an open notebook dedicated to bringing competitive intelligence into the 21st century.
The first in a series introducing the Cynefin decision-making framework to the CI field was just put up - however, I will append it here for your convenience.
#AdaptOrDie - www.rethinkingci.wordpress.com
Note: This is the first in a series of posts introducing the Cynefin decision-making framework to the field of competitive intelligence. The Cynefin framework will serve as a thread between subjects this blog intends to explore, including: sense-making, complexity, strategy, and modern intelligence methodologies.
Competitive Intelligence tends to treat all decision making enviroments as the same, regardless of the system it occurs in. This is a mistake because the system or environment the decision making occurs in differs from situation-to-situation and industry-to-industry.
Part of this disconnect is because the CI field was developed on Cold War era intelligence paradigms that were imported, nearly unchanged, from the government and designed for largely static issues and environment. While the US intelligence community broadened its to dynamic topics after the fall of the Berlin Wall, the CI field has not adapted its paradigms to better suit the external environment.
The Cynefin decision-making framework recognizes the causal differences that exist between system types, and proposes new approaches to decision-making in complex environments. Cynefin (Welsh term pronounced Kin-ev-in) is likewise a sense-making model making it conductive to modern intelligence paradigms designed for a dynamic environment.
Into to Cynefin
There are 5 domains or contexts in the Cynefin framework: simple, complicated, complex, chaotic, and disorder and is to be visualized as shown here below:
The first four domains can be described as follows:
Simple – Clear and obvious relationship between cause and effect. Known-knowns. Approach with Sense–Categorize-Respond and apply “best practices”.
Complicated – Cause and effect requires analysis, investigation or expert knowledge. Known-unknowns. Approach with Sense–Analyze–Respond and apply “good practice”.
Complex – Cause and effect can only be perceived in retrospect, not in advance. Unknown-unknowns. Approach with Probe–Sense–Respond to detect emergence patterns and practices.
Chaotic – No relationship between cause and effect on the systems level. Unknown-unknowable. Approach with Act–Sense–Respond to discover novelty, seek to stabilize environment.
The fifth domain is disorder and abuts all the other domains. This is to signify that any given domain can slip easily into disorder, when not knowing what what type of causality exists and people revert back to their entrained thinking for decision making.
It is important to note that Cynefin is not a categorization model – this is not a simple B-school 2×2 matrix. Problems can overlap boundaries, and the lines between boundaries blur.
Future posts in this series will further explore Cynefin and its applications to CI.
The New Dynamics of Strategy: Sense-making in a Complex-Complicated World, by Cynthia F. Kurtz and David J. Snowden. IBM Systems Journal, Fall 2003. (PDF)
A leader’s framework for decision making, by David J. Snowden, and Mary E. Boone. Harvard Business Review, November 2007, Volume: 85 Issue: 11. (PDF)
Systems Thinking and the Cynefin Framework: A Strategic Approach to Managing Complex Systems, by H. William Dettmer. Goal Systems International, 2011. (PDF)