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.
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They follow a trajectory that is oblique. Obliquity describes the process of achieving complex objectives indirectly.
In general, the oblique approaches recognise that complex objectives tend to be imprecisely defined and contain many elements that are not necessarily or obviously compatible with each other, and that we learn about the nature of the objectives and the means of achieving them during a process of experiment and discovery.
An oblique approach recognises that what we want from a home, or a community, has many elements. We will never succeed in specifying fully what they are, and to the extent that we do, we discover that they are often incompatible and inconsistent. The interactions between a home and its occupants, or between the people who make up a community, are complex and uncertain. The experience of both previous and current problems guides the search for answers. Many people contribute to the outcome, and even after that outcome has been realised none of them necessarily
holds a full understanding of how it came about.
We deal with complex systems whose structure we can understand only imperfectly. The problems we face are rarely completely specified, and the environment in which we tackle them contains irresolvable uncertainties.
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’.
Applied to geopolitical events, or complex businesses, the methods collapsed. These latter problems are best tackled, not by moral algebra, but obliquely: they involve high-level objectives achieved through adaptation and iteration, with constant rebalancing of incompatible and incommensurable components that are imperfectly known but acquired as the process goes on.