The axiom of business is to maximise profits
The axiom of business is to maximise profits. This, in turn, requires keeping a close eye on revenues and costs. Revenues can be increased by capturing greater market share, such as building brand following or by introducing faster innovations. Costs can be reduced by cutting the factors of production, such as material inputs through a dematerialisation or replacing labour by robotics and AI, or by capturing greater economies of scale, which implies that the more you make of something, the cheaper it becomes on a per unit basis.
The logic of striving to get the most profit out of a limited number of offerings, is well entrenched in the prevailing business culture. However powerful the logic is, within an interconnected system that operates like a web of life, it overlooks many opportunities. It only sees what it knows, paraphrasing the German poet Johann Wolfgang von Goethe. In practice, the highest possible target for one parameter can only be achieved to the detriment of other interconnected factors. Imagine for a moment that a tree maximises its production of chlorophyll but neglects transpiration, which will result in it overheating. Or, a hen focused solely on laying eggs without paying any attention to raising chicks. It does not take a biologist to realise that a single focus on one outcome cannot only be detrimental to the system, worse it undermines long-term livelihood.
Maximising one parameter, to the detriment of all others
The tools typically used in business to calculate how to achieve the greatest possible profit are only capable of maximising one parameter – to the detriment of all others. Such an approach only gets the best out of one parameter and typically is incapable of recognising or minimising the associated adverse effects. This is the challenge with a linear approach: it creates blind spots that hide the negative impacts. This leads to unintended damage to the system, as our decision tools did not permit us to see the damage until it was done, and became too pervasive, then we need the consciousness and awareness to take action. As we know, correction often is late, sometimes it never comes and the burden of the damage is born by the community.
This is why a Blue Economy approach opts for Nature's principle of optimisation of the whole, rather than maximisation of a selected part. An approach of optimisation of the whole involves recognising the delicate balance among all the factors, to cultivate the greatest opportunities for the entire system. This approach ensures that we do not excessively focus on only one target, such as the profit derived from one or a limited number of products, or the amount of resource recycling. This helps us to eliminate blind spots from initiatives that, while they may well generate growth, profit and market share, also may create disguised and unwanted consequences.
Mapping the systems of systems
In order to do this, a Blue Economy approach maps the inputs and outputs to comprehend the systems of systems at play. Such an approach can simulate a range of new results, even ones we could not possibly have imagined at the outset. This may seem like magic, but it is rather a case of discovering and harnessing what there is now, or what was there all along, but not considered, nor accounted for. This can include stocks and flows of matter, money and energy and connections between phenomena that we previously did not understand. Once these sub-systems are mapped, it is possible to see how several initiatives, projects, businesses and communities are able to co-evolve, continually deriving more advantages and eliminating negative effects.
The power of The Blue Economy approach does not only lie in implementing a project, but rather in designing and creating a fabric of interrelated initiatives that co-evolve, strengthen the capacity to implement, reduce risks and optimise the output – in a way that generates more benefits. The discovery of opportunities within such a fabric of activity generates more benefits (both directly and indirectly) as a result of the non-linearity of the feedback loops and economic multipliers. The case of El Hierro, discussed throughout this book, provides an example of this, where what started as a fabric of economic activity that saw numerous once lost industries revived, along with solving the energy and water issue. This strategy, of optimisation and continuous seeking of ever-more value, generates a whole that is more than the sum of the individual parts, whereas a linear model is usually only exactly the sum of its parts, plus unintended or hidden damages.
Such an approach allows us to create a system where all can satisfy their basic needs. This inclusive optimisation model leads to the creation of a much bigger pool of resources and benefits, which makes it easier to engage everyone and obtain a broad commitment to co-evolve along “win-win-win” logic. This approach to optimisation offers transparency and leads to an open dialogue – a participative model. This model permits us to determine what the individual priorities are, how sub-systems determine their optimum, and adjust according to the feedback received, so that more resources are released to enhance other parts of the system and achieve the best possible outcome for all. The ideal level of the overall performance is continuously adjusted, so that it can co-evolve along with the available resources and the desired levels of satisfaction of an ever-increasing and diverse community – one that is fulfilling an increasing number of its basic needs, and continues to discover more of its innate potential.