Complexity & Decision Making Capability
By H Griffiths: Originally Published Jan 11 2018 on Medium.com
Are we facing a complexity driven crisis in business decision making brought on by waves of new technologies?
Recently I’ve worked with several organisations to review a range of new technologies that it could be deployed in their businesses. At some point during the analysis the initial enthusiasm for the possibilities that new technologies could bring always seem to collide with the realisation of the complexity that will be involved in implementing and managing it.
That point often comes when people start to think through the detail of how all of the new pieces will fit together and how they will fit in with the existing architecture, operating model and business model.The challenge then is often the same. If we cannot figure out a way of reducing the perceived complexity of the task then the next step in the process — making a decision to take action — will be difficult.
Part of the problem I believe is that new technologies are introducing many new factors that need to be considered which those involved do not necessarily have a good knowledge or understanding of. I recently wrote a separate post on this subject called Can do, will do, and the need for Chief Philosophy Officers?
Does: (Perceived complexity) x (lack of knowledge) = Decision making difficulty?
If the above statement is generally true, what are the possible solutions to this problem? I believe that one approach may lie in first better understanding the true degree of complexity and what knowledge is required to understand it.
When it comes to being able to tame complexity, I often use the example of the Rubik Cube:
However, the real lesson is that if you have the right knowledge, you can greatly reduce the perceived complexity to a point where it is manageable.
That lesson only becomes apparent when you learn that you only need to learn eight different sequences of moves (algorithms) to solve the 3x3 cube. In addition, you only need to know a subset of those eight moves to solve the 2x2 cube, since the 2x2 cube pieces behave in exactly the same way as the corners of the 3x3 cube.
So, how do we take the insights from solving a Rubiks Cube and apply them to decision making in organisations today? The answer may lie in first better understanding the true degree of complexity and what knowledge is required to reduce it to a point where it can be managed.
I read a thought-provoking book on decision making recently entitled Decision Making in the New Reality* which, along with several other articles on newly discovered cognitive limitations of the human mind, led me to sketch out the diagram below.
Are we facing a complexity driven crisis in business decision making brought on by waves of new technologies?
Recently I’ve worked with several organisations to review a range of new technologies that it could be deployed in their businesses. At some point during the analysis the initial enthusiasm for the possibilities that new technologies could bring always seem to collide with the realisation of the complexity that will be involved in implementing and managing it.
That point often comes when people start to think through the detail of how all of the new pieces will fit together and how they will fit in with the existing architecture, operating model and business model.The challenge then is often the same. If we cannot figure out a way of reducing the perceived complexity of the task then the next step in the process — making a decision to take action — will be difficult.
Part of the problem I believe is that new technologies are introducing many new factors that need to be considered which those involved do not necessarily have a good knowledge or understanding of. I recently wrote a separate post on this subject called Can do, will do, and the need for Chief Philosophy Officers?
Does: (Perceived complexity) x (lack of knowledge) = Decision making difficulty?
If the above statement is generally true, what are the possible solutions to this problem? I believe that one approach may lie in first better understanding the true degree of complexity and what knowledge is required to understand it.
When it comes to being able to tame complexity, I often use the example of the Rubik Cube:
- A 2x2 cube has 8 parts and 3,674,160 possible combinations.
- A 3x3 cube has 26 parts and 43,252,003,274,489,856 possible combinations. (43 Quintillion)
However, the real lesson is that if you have the right knowledge, you can greatly reduce the perceived complexity to a point where it is manageable.
That lesson only becomes apparent when you learn that you only need to learn eight different sequences of moves (algorithms) to solve the 3x3 cube. In addition, you only need to know a subset of those eight moves to solve the 2x2 cube, since the 2x2 cube pieces behave in exactly the same way as the corners of the 3x3 cube.
So, how do we take the insights from solving a Rubiks Cube and apply them to decision making in organisations today? The answer may lie in first better understanding the true degree of complexity and what knowledge is required to reduce it to a point where it can be managed.
I read a thought-provoking book on decision making recently entitled Decision Making in the New Reality* which, along with several other articles on newly discovered cognitive limitations of the human mind, led me to sketch out the diagram below.
The diagram is intended to provide a subjective assessment of the perceived degree of complexity and knowledge required to complete each stage of the strategy to the execution process for a new initiative, given the knowledge and cognitive capability of the people involved.
If the blue points (complexity) are above the green points (knowledge required to understand the complexity), it should prompt you to ask how could you increase your knowledge, or decrease the perceived complexity?
The red line indicates the current capability within your organisation, so if the green points and blue points are above it, then you will either have to either raise your internal capability or turn to external sources of knowledge or solutions that can reduce the complexity to a point where it can be managed.
If the people carrying out the analysis/thinking stage are different to those that will make the decisions, it may help to draw a separate line for each group which may highlight the degree to which knowledge needs be transferred between those two groups.
The diagram currently assumes that the collective wisdom of a team is greater than any one individual, but is that always the case? Is there a point where collective wisdom is replaced by groupthink or rival factions which reduces the capacity to decide?
Conclusion
This tool is still a work in progress, so I would welcome your thoughts on whether it is useful or not and how it could be improved. I would also be interested to know what other useful tools that you know of and have found useful that surface the issue of complexity and decision making. Tools such as the Cynefin framework and OODA loop spring to mind.
Further Reading:
Books:
- *Decision Making in the New Reality ISBN 978–0–9798459–5–6
- HBR 10 must-reads on making smart decisions