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Dave Snowden, is formerly a director in the IBM Institute for Knowledge Management, where he led programmes on complexity and narrative. He is currently Director of the Cynefin Centre for Organisational Complexity which focuses on the development of the theory and practice of social complexity. The Centre spun off from IBM in July 2004. The Cynefin framework which lies at the heart of the approach has been recognized by several commentators as one of the first practical applications of complexity theory to management science and builds on earlier pioneering work in Knowledge Management. He regularly consults at the board level with some of the world's largest companies as well as to Government and NGOs and was recently appointed as an advisor on sense making to the Singaporean Ministry of Defence.
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| Workshop, Friday, 13.30-17.00, 7 July 2006, Oxford University |
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Applying Complex Systems and Narrative Approaches to Product Development Decisions
Led by Dave Snowden, Cynefin Centre
Product Development involves complex, difficult and important decision-making by an organisation. In a perfect world the best decisions should be prepared for and supported by as thorough an understanding both by individual experts and managers and the organisation as a whole. All available relevant knowledge, both internal and external to the organisation, should be available and actionable at key decision points in the product life cycle. Such a prepared organisation should be able to ask powerful questions, quickly obtain reliable answers, have the ability to react pro-actively and wisely to new and unexpected events, and to integrate risk and uncertainty evaluation in the organisation's preparation for the future using all knowledge flows available to it.
However the world is all too often not perfect and is inherently uncertain. Weak signals go un-noticed and small changes result in producing unexpectedly large consequences. Traditional approaches to decision support have relied on screening or filtering data so that the decision maker only sees what is relevant. Unfortunately such approaches screen out the very data that in retrospect the decision maker will realize they needed. Recent developments, driven in some cases by the information processes of anti-complexity are offering a new approach to decision support in which all data is made available at all times and the principles of serendipity and necessary ambiguity are used to focus the organization on resilience rather than stability and effectiveness rather than a blind focus on efficiency. Such systems aim to a achieve a symbiosis of human and machine intelligence and capabilities.
Although informatics approaches such as data-warehousing capture and integrate a vast amount of data, it is questionable that such an approach alone enables the organisation to make the best decisions it could make based on all knowledge it could have. We raise the question: what methods could enable an organisation to maximise its human capital and knowledge potential in its preparation for decisions it makes in the future involving the currently known and the inherently unknowable?
In this session we consider approaches that offer potential contributions to organisational development in the above context:
Sense making and Complex Systems Analysis - Sense making draws on a variety of scientific understanding, principally from the cognitive sciences, narrative theory and the science of complex adaptive systems theory to deal with inherently complex and unknowable realities of the world. The developments in this field have been funded over the last seven years in the complex and uncertain field of anti-terrorism and are now starting to be applied in the agrochemical and pharmaceutical sectors.
We will consider and compare how complex systems approaches could benefit an R&D organisation in the following decision-making situations:
A. Decision to advance product in research and early development
B. Decision to advance product into full development
C. Decision to launch product
D. Decision for action upon discovery of unexpected adverse event
E. Corporate Risk Management decisions for a portfolio of products
F. Cross Silo collaboration and interaction
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