The search has begun! How do we deal with the complex world we live in today? Imagine you are out in the wild on a foggy night with a touch? Do you need a better compass, a telescope, a weather meter or a an information-rich map? How about enlisting the help of machine intelligence and learning? Perhaps, your purpose is the link between simplicity and complexity in the way you approach the problem?

Well, scientific research such as those done by New England Complex Systems Institute and Santa Fe Institute have found that there is universal simplicity in complexity, taking into account all its characteristics of heterogeneity, randomness, noise, feedback loops, emergence, self-organisation, path dependence, sensitive dependence on initial conditions, tipping points, fractals, scaling etc. From stock markets, bee hives, brains, social networks to cities, economies and the universe, all of them are driven by a common underlying fundamental principle, that of a probabilistic computational strategy that lead to the evolution of complexities we observe all around us today. So is universe a computer? And evolution a computation? Regardless of the complexity and enormity of the problem you are grappling with at home or at work, you can take advantage of these recurring patterns to get a firm hold of the situation.

How can simple laws explain organised complexity?

Conventional scientific reductionism is useful but does not provide the complete picture: it tells us how but not why, insiders but not outsiders, content but not context. It offers little insights into the construction and relationships of parts, which is where complexity abounds, #LinesNotBoxes, #BetweenTheDots that matters.

The question to ask is not why does complexity arise in nature but a more interesting question is why do simple structures exist at all?

The reality is that in the 4th Industrial Revolution we are living in right now, the world is increasingly becoming more uncertain, complex and inter-connected. The way to manage such a situation and be agile in response to both internal organisational or external market or regulatory changes is not to add yet more complicating rules and requirements that attempt to anticipate every possible outcome through extensive planning but instead to figure out the small number of key forces at work and leverage their interaction effects. We call this the simplexity approach first coined by Jeffrey Klugger 2008. A similar concept to Pareto’s 80/20 rule. We have to learn that the best decisions are only probabilistic and no matter what we do we cannot guarantee success. We can only deals with the present not the future. So don’t work out how things should be but deal with how things are.

From chaos and complexity to clarity and simplicity - the Simplexity Way.

Improving health is a good example. One can make it complicated by identifying a long list of factors and remedies, or make it overly simple by seeking a magic bullet in the form of vitamins and prescription pills. Or one can go the simplexity route: eating a healthy diet, exercising three times a week and getting eight hours of sleep every night.

Pragmatically, to achieve agility among many other strategic objectives of efficiency, effectiveness, sustainability etc, we assert that enterprises need to focus only on the universal fundamentals— the rocks, leaving the stones and then the sands to sort themselves out in a self-organising manner. Those fundamentals are: firstly organise themselves into 4 conceptual parts of Direction, Operation, Transformation and Support so that there is clarity of accountability, secondly connect the elements of its structural and transformational information, methods, artefacts, culture and environment for the former and motivation, guidelines, measures and assessment for the latter so that there is coherency, and thirdly conducts regular health assessment using a maturity model so as to be able to accurately describe the presence, of the relationships ("between the dots") among the above elements we can change in the present, where we can monitor the effects of those change, and out of that subset where would success be probable or failure teaches us something.

Would you join our quest ?