Organizations need to be able to access, coordinate and integrate knowledge more efficiently than ever before to make sense of the complex and unpredictable forces shaping business conditions. Often knowledge is sourced from diverse yet interconnected networks of individual experts and organisations. In this environment, it is hard to ensure that decisions are based on the best available knowledge and do not work against one another. More alliances and inter-organizational partnerships and various contractual relationships with individuals broaden the range of perspectives and values to be considered, which makes it even harder to determine what a “good” decision looks like.Decision making is an intrinsic part of business activities. Appropriate organisational decisions rely on having the right knowledge in the right place at the right time, to be able to act effectively. “Right” knowledge may be different for every decision –some can be made on surface knowledge, some required more investigation to develop an evidence base, some more reliant on deep expertise, and others need creative insight, intuition and judgement (Snowden and Boone, 2007, Bennet and Bennet, 2008). Knowledge is raw material, work in process and deliverable in any decision (Holsapple, 2001).
(Yates and Tschirhart 2006, p422). Yates, J. F. and Tschirhart, M. D. (2006) "Decision-making expertise", Ericsson, K. A., Charness, N., Feltovich, P. J. and Hoffman, R. R. (Eds.) The Cambridge Handbook of Expertise and Expert Performance. New York, Cambridge University PressWe picked this definition because “the specification of beneficiaries is critical, implicating what is arguably the single feature of decision problems that distinguish them most sharply from more general problems –differences among people in the values they attach to decision results”. But, more complex inter-firm relationships and different contractual relationships with individuals mean identifying the beneficiaries of a decision and what they value is becoming more challenging.
Barney, J. (1991) "Firm resources and sustained competitive advantage", Journal of Management, Vol. 17, No.1, pp. 99-120.Prahalad, C. and Hamel, G. (1990) "The core competence of the corporation", Harvard Business Review, Vol. 3, No.79-91.Stalk, G., Evans, P. and Shulman, L. (1992) "Competing on capabilities", Harvard Business Review, Vol., No.57-69.Teece, D., Pisano, G. and Shuen, A. (1997) Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533.Underpinning theory – RBV / KBV / dynamic capabilities.Organisational success comes from constructing and consolidating distinctive resources and capabilities over the long term. Dynamic capabilities enable adaptation and sustainability. (Barney 1991, Prahalad and Hamel 1990, Stalk et al 1992, Teece 1997)
Cyert, R. M. and March, J. G. (1963) A Behavioral Theory of the Firm, Prentice Hall, Englewood Cliffs, NJ.Eisenhardt, K. M. (1999) "Strategy as Strategic Decision Making." MIT Sloan Management Review, Vol. 40, No.3, pp. 65-72Tetlock, P. E. (1991) "An alternative metaphor in the study of judgement and choice: people as politicians", Theory and Psychology, Vol. 1, No.4, pp. 451-475.Hammond, J. S., Keeney, R. L. and Raiffa, H. (2006) "The hidden traps in decision making", Harvard Business Review, Vol. 84, No.1, pp. 118-126.The psychological school of research into decision making starts from the cognitive mechanisms people have developed to cope with their environment - the heuristics that speed up decision making but have potential traps associated with them (Tetlock, 1991). Here, the predictive thinking patterns that underpin the heuristics risk introducing bias, examples being the confirming evidence bias (seeking information that supports own point of view and avoiding information that does not) and the sunk-cost bias (making choices that justify past choices) (Hammond et al., 2006). Examples of BiasAnchoringGiving disproportionate weight to the first information received (2)Status-quoPreferring alternatives that preserve the status quo (2)Sunk-costMaking choices that justify past choices (2)Confirming-evidenceSeeking information that supports own point of view and avoiding information that does not (2)
Snowden, D. J. and Boone, M. E. (2007) "A leader's framework for decision making", Harvard Business Review, Vol. 85, No.11, pp. 69-76.Simple decision making contextsStructural capital to support decision making can be most readily formulated. However, ensuring that the systems and processes are used effectively is not necessarily straightforward as cognitive and emotional biases come into play so appropriate human capital investments need to be made alongside the structural capital development. Technology advance in the 1960s and 1970s led to decision support systems that aim to improve consistency in this simple context. For example, decision tree type methods which systematically explore the implications of alternatives can be converted into readily accessible software applications. Artificial intelligence systems focus on well-defined problems and have been particularly effective in operational environments (Yim et al. 2004). Complicated decision making contextsIn Snowden and Boone’s “domain of experts” where complicated decisions are being made and more than one right answer is possible, research has tended to focus on the individual as decision maker. Naturalistic Decision Making” (NDM), revolves round the extremes of expert-based decision-making.As expertise is dynamic, experts need to keep their knowledge base up to date and continue to refine their thinking about how to apply knowledge for impact. Being an effective reflective practitioner is an important characteristic of becoming an expert. This enables the expert to seek out opportunities for deliberate practice to improve their level of expertise, benefit from exposure to new experiences, and build mental models that incorporate new knowledge (Klein 1997). Experts can use technology systems that codify and structure explicit knowledge as a “scaffold” to support their decision making (Pech and Durden 2004). Some companies even try to replace human experts with technology based structural capital investments to extend the reach of their knowledge. Knowledge based expert systems can be effective for operational and tactical decisions, capturing the structure of a knowledge domain by codifying human expertise and integrating it with other computer systems such as forecasting and reporting systems (Yim et al. 2004). Complex decision making contextswe have to “assume that complex problems are managed, not ever fully solved”. Organizations also need ways to ensure that the “right problem” is explored. This means considering multiple perspectives and areas of disagreement. The public sector provides some of the most complex environments for decision making because social policy problems, often labelled “wicked”, are unbounded in time, scope and resources. They are inherently complex because they involve unpredictable interdependencies. Structural capital investments in new collaboration technologies can help support decision making by facilitating multi-participant issue articulation. Relationship capital investments create the collaborative links with diverse external stakeholders. In a business context, strategic decisions fall predominantly within this complex domain. Approaches are needed that build the capacity for collective sensemaking, challenge cognitive biases, manage political differences regarding what is valued and experiment to find patterns in the situation (Eisenhardt 1999). Human capital investments to develop the capacity of individual decision makers need to be supported by structural capital investments in processes that support collective learning about how to make decisions in these contexts.
The framework remained robust at this exploratory research stage
Henley business school improving organisational decision making