In Obliquity, John Kay argues that success may be best achieved indirectly. When the goal is non-trivial, the environment unpredictable, and the system in which we are operating is complex, then top-down working, planned to completion, is fragile.
He recommends that we instead proceed obliquely, taking small steps, making choices opportunistically, and accepting that we do not have all the information or all of the control we might feel we want.
Kay presents numerous examples of people and organisations that have done well with the oblique approach and some that have suffered when their indirect strategy straightened up. That's not to say the direct approach can't work or that it is a mistake to apply it to some situations, just that the set of real-world scenarios where directness is a good first choice is pretty constrained.
It doesn't take much imagination to see the strong parallel between obliquity and agile software development. Likewise, from a testing perspective, the idea of a high-level mission helping to determine in-the-moment, intertwined, strategic and tactical decisions makes my exploratory testing feel very compatible with obliquity.
That sense is strengthened by Kay's comparison of direct and oblique approaches to problem solving (click to enlarge):
It's interesting to explore the edges of the oblique approach. For example, perhaps it is less applicable in act-right-now emergency situations, or those where there is a strict regulatory process or standard operating procedure.
Maybe direct action in a crowded market would gain a competitive advantage that an oblique approach would miss.
It might also be more challenging to impose metrics on an oblique approach than one where scheduled goals met or artefacts produced can be counted. This overlaps with testing and with knowledge work in general.
One final thought: I wonder whether Kay's examples suffer from survivorship bias. The answer is almost certainly yes, but that doesn't detract from the central idea: that an iterative, exploratory, approach to work, keeping high-level goals and constraints in mind, can be a sensible way to proceed through ambiguity and complexity.
I've pulled out a few quotes from the book below.
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They were playing what I now call Franklin's Gambit, after the American polymath Benjamin Franklin. He wrote: 'so convenient a thing it is to be a reasonable creature, since it enables one to find or make a reason for everything one had a mind to do.' (p. xi)
The identification of high-level objectives, intermediate goals and basic actions is relevant in many contexts. (p. 40)
High-level objectives are typically loose and unquantifiable ... achieved only by translating them into intermediate goals and states and thereby reducing them to specific tasks (p.41)
The objective was to facilitate trade links, the goals was to improve sea links between Atlantic and Pacific ports, an action was the building of the Panama Canal. (p. 41)
Objectives, goals, and states evolve together because learning about the nature of high-level goals is a never-ending process. (p. 63)
The process in which well defined and prioritised objectives are broken down into specific states and actions whose progress can be monitored and measured is not the reality of how people ... build good businesses.
If the world were like Sudoko, decision making could be tackled in a ... direct way [...] The game of Sudoko is closed, determinate, tractable and has a clear-cut objective. (p.64)
The task of interpreting an objective or a goal is not just part of the job of the good artist or teacher but the principal part. The definition of the objective or goal is not separable from the means by which that objective or goal is achieved ... (p. 78)
The planned, centralised solution [often fails] because the planners did not possess the local knowledge held in the community ... (p. 84) (This has strong echoes of Seeing Like a State which I have not read yet but is covered wonderfully by Brian Marick's deep review in his Oddly Influenced podcast.)
Marks and Sieff recognised the need for those who carry out actions and seek goals to do so with an understanding of higher-level objectives. They must internalise, at least in part, the values that underpin the target. (p. 87)
When new data arrives ... we always have the problem of whether to treat it as new data about the parameters of the model or new data about the relevance of the model. (p. 108)
Roosevelt ... understood that the scope of his authority was inescapably limited by the imprecision of his objectives, the complexity of his environment, the unpredictability of the reaction of others and the open-ended nature of the problems he faced. [He must] proceed by choosing opportunistically from a narrow range of options. (p. 129)
Machiavelli understood that to be an effective decision maker it was wise not to seek public credit for the success of your decisions. (p. 136)
[Teachers] monitored adherence to the rules they taught and saw such adherence more often in the novices [than the experienced practitioners]. They looked knowledgeably for directness and could not recognise the success of obliquity ... (p. 145)
[Successful people tend to] describe their experiences rather than explain them ... they repeat John Paul Getty's explanation of his business success: 'Strike oil.' They do not tell us the secret of their achievements because they do not know. (p. 147)
The oblique decision maker is not hung up on consistency and frequently holds contradictory ideas simultaneously. (p. 162)
... if the model of the problem is inappropriate, the mistakes of the model cannot be easily revealed within the model itself. (p. 166)
Judgement and experience teach us which models to use on which occasions. (p. 166)
When faced with a task that daunts you, a project that you find difficult, begin by doing something. (p. 175)
Image: https://flic.kr/p/2pz1h1F