The environment— social, commercial, natural— in which we operate changes over time and as we interact with it. Our knowledge of that complex environment is necessarily piecemeal and imperfect. And so objectives are generally best accomplished obliquely rather than directly.

The general strategy is to tackle problems by adaptively translating the objective into intermediate goals and states— completing blocks— and basic actions— finding individual numbers. That strategy iterates, adapts, retreats when attempted solutions proves less promising than they appear. The methods of analysis that come naturally to us are oblique, and we do not use or enjoy direct, mechanical approaches. Anyone who buys a computer program to solve a Sudoku problem has missed the point of the game.

Because the process of achieving high-level objectives is necessarily iterative in this sense, the path to these objectives is bound to be oblique.

When you cannot measure something, said Lord Kelvin, ‘your knowledge is of a meager and unsatisfactory kind’.

Good decision making is pragmatic and eclectic. Oblique approaches rely on a toolkit of models and narratives rather than any simple or single account. To fit the world into a single model or narrative fails to acknowledge the universality of uncertainty and complexity.

And this story repeats itself through the history of management science; almost every classic of the literature seems to have described a way of adapting systems to a more complicated world, and then to have become obsolete itself. If you look past the slogans and think about what things like ‘management by objectives’, ‘focus on core competences’ and so on actually mean, they are all different ways of advising executives to restructure their businesses so that they don’t generate complexity faster than it can be managed.