I am often asked the method of observing complex issues enabling us to innovate (creating something new) in a complex environment, which might be applicable to diverse domains such as engineering, maintenance, management, strategy, marketing, etc.

1. Interactions between elements (usually diverse) create complexity and the quality of the interactions change over time. Hence observing interactions is the first important step.

2. Quality of interactions change because some quantity within the interactions change “non-linearly“.  As quantities change monotonically problems appear. This can also help us solve problems. Therefore, observe what changes non-linearly.

3. The “non-linearity” of all complex systems is hidden in the interactions. This changes the system behavior as a whole, which also exhibits non-linearity. The outcome might be ‘desirable’ or ‘undesirable’. So, observation of the non-linear system outcomes and their effects and patterns is the third most important step in observing complex issues.

Hence, the solution lies in taking care of non-linearity. This is not to say that non-linearity would magically transform into something linear that makes it easy for us to manage but we attempt to keep it within some limits or introduce or amplify some other non-linear phenomenon or eliminate or mitigate certain non-linearity as the case might demand. That is the essence of obtaining a solution.

Based on these three principles of observations we can see more deeply into all changes that happen in the real world. This leads us to few more principles of observation, which are the following:

4. Changes happen due to interactions of physical forces, chemical reactions or electromagnetic interactions or human interactions or interactions between nations or communities or interactions between organizations and customers or economy and the market etc.

5. These create specific patterns and shapes which if we are lucky might be captured as data or information. However, such data or information are always relational else no movement would ever happen (consider the force of walking vs the force of friction — they are in tandem – one never leaving the other — forming a movement).

6. So when we look at relational data and trend them we find a pattern. Such patterns can be of various types and shapes (like spirals, waves, cracks etc. )

7. Since real world systems work far from equilibrium conditions (that is interdependence of diverse elements – where everything affects everything else) such relational trends either run in ‘sync’ or ‘out of sync’. (that is ‘in phase’ or ‘out of phase‘ – even happens in all machines and human activities like a group of people walking in the park or even in heart cells).

8. When they are in ‘sync’ things might be normally considered as ok i.e. the system is stable. When they are out of sync (or out of phase) it indicates an impending change, which might be desirable or undesirable.

9. The impending change is predicted by a sudden amplification of one of the relational parameter that tends to bring movement to a halt (consider friction either suddenly going up or down while walking and how it would immediately stop movement).

10. Such ‘out of phase’ and ‘amplifications’ are the hidden imperfections in any complex issue, identification of which help us solve or resolve any complex issue.