Uncovering unknown unknowns: Towards a Baconian approach to management decision-making

Abstract

Bayesian decision theory and inference have left a deep and indelible mark on the literature on management decision-making. There is however an important issue that the machinery of classical Bayesianism is ill equipped to deal with, that of "unknown unknowns" or, in the cases in which they are actualised, what are sometimes called "Black Swans". This issue is closely related to the problems of constructing an appropriate state space under conditions of deficient foresight about what the future might hold, and our aim is to develop a theory and some of the practicalities of state space elaboration that addresses these problems. Building on ideas originally put forward by Francis Bacon (1620), we show how our approach can be used to build and explore the state space, how it may reduce the extent to which organizations are blindsided by Black Swans, and how it ameliorates various well-known cognitive biases.

Scenarios in the strategy process: a framework of affordances and constraints

“…Prior long-term trends do not reveal their discontinuities and disruptions in advance. While black swans or wild cards are, irrespective of their low probabilities, at least imaginable, no decision maker can preempt "unknown unknowns" [50]. Not even the preconditions for the occurrence of the yet feasible event can be known.…”

‘Till the Muddle in my Mind Have Cleared Awa’: Can We Help Shape Policy Using Systems Modelling?

“…Rosenhead, ; Barber, ). However, this is easier said than done since, ‘Surprise is an unavoidable fact of life, and the assumption that decision makers can anticipate every eventuality that might befall them is highly demanding’ (Feduzi and Runde, , p. 272). Hence the comic but insightful observation that the advice ‘Expect the unexpected … is a) glib, and b) a contradiction in terms’ (Adams and Perkins, , p. 195).…”

Uncertainty: A Diagrammatic Treatment

“…Feduzi and Runde (2014) question the coherence of such 'unknowable unknowns' in a Bayesian framework, which requires a known state space. 9 They can only make sense as 'knowable unknowns', i.e.…”

“…The kind of institutional arrangements which are identified as the source of missing information in the mainstream approach (such as administered prices, or central bank support for banks facing liquidity problems) can provide a stable environment which reduces uncertainty (just as Coase, 1937, analysed institutional structure at the firm level as a mechanism for dealing with uncertainty). 14 _________________________ 13 A subsequent large literature has developed, particularly in the management field, on conventions to support decision-making under uncertainty (Feduzi and Runde 2014). 14 See also McKenna and Zannoni (2001), who pursue this tack in direct response to Coddington's, 1982, charge of nihilism and Dow and Dow (2011), who explore the way in which animal spirits can be molded by institutions and conventions.…”