Dealing with complexity requires the ability to adapt to different ways of thinking; traditional approaches to problem solving, whilst comfortable and compelling in terms of received wisdom are often entirely inappropriate, resulting in impenetrably complicated representations of the problem domain.
Naming of Parts
The initial challenge in any systems problem is to achieve valid simplification. In traditional approaches this is often achieved by decomposing on a system by system basis, however a key feature of complex systems is that important aspects of behaviour arise from interactions between sub-systems, which may not be apparent through inspection of the separate systems.
Fundamentally, the relationships between sub-systems are as important in understanding behaviour as the the sub-systems themselves – and this requires a far more sophisticated approach to problem decomposition.
Seeing the Wood for the Trees
The implications of failing to deal correctly with a problem that is mathematically complex cannot be overstated. Niaive decomposition will invariably result in astonishingly complicated representations, failing to reveal the underlying simplifications that are key to an elegant solution.
More significantly, however, they will obscure the more significant aspects of emergent behaviour that can add real value to a solution set, or more frequently result in unanticipated and damaging outcomes. We have seen many ‘informed’ solutions in which the ‘expert’ view is little more than a confoundingly complex amalgam, effective only in obscuring a lack of real insight.
Art and Science
Whilst complexity thinking remains as much an art as a science during these early stages of its evolution, it does nevertheless begin to offer insights to valid simplifications of previously intractable problems.
Most significantly though, complexity thinking is not just another systems management fad, set to come and go as management fashions dictate, it represents the leading edge of a new and important science, ripe for exploitation and development.
Informatics
Complexity is not new, however the highly dynamic information domain that supports previously unachieveable levels of sophistication and richness in information exchange and exploitation is. CSI has recognised the importance of the information domain as the single most significant factor in the rapid growth of system complexity.
We have embraced complexity thinking as an important tool in the systems engineering toolbox, applying broad-ranging engineering insight to the development of fundamentally robust generic toolsets that allows us to deal coherently with complex interactions and outcomes.
Our Approach
CSI complex systems system of systems design approaches are optimised to deal with dynamic, emergent and information-centric aspects of systems complexity. These approaches include:
Capability Based – Outcome-oriented, considering wide-ranging influences with implicit and comprehensive representation of the information domain, ensuring appropriate focus and design emphasis on areas that are critical to shaping solutions.
Model Based – Problem domain decomposition using coherent systems and capability viewsets, supporting valid simplifications for analysis, visualisation, design, options and solution development, exploiting a sophisticated sub-set of complexity models.