Organizations exist primarily to solve problems – generally they pick a given domain of interest, identify a cadre of problems they will solve and often, in the form of a mandate prescribe the formulation of the solution to that problem.
Unfortunately for many organizations such as NGOs this is a disasterous method for initial structuring. Problems like poverty, gender inequity or climate change are not static entities whose assumptions are constantly true over a period of years. Mandates, as they commonly exist for charities and non-profits – especially small-scale, locally focused ones concretize a functional fixedness in the thinking of the organizational members which destroys creative problem solving. However, firms also suffer from that same calcification through the enforcement of “core competencies” – which are intended to be descriptive of the current capacity of the firm but instead become normative parameters for service or product diversification.
Conversely, some mandates are so vague they provide no way to distinguish between competing solutions. Specifically, the mandates don’t provide any way to contextualize innovation within the culture of the organization – how people do their work, the perceptions of members’ and the established norms at play within the organization. This is especially evident in the deployment of technology within many groups. New, fanciful technology is installed with the intention of “revolutionizing the way the organization works.” These applications are generally left derelict because it does not integrate cleanly within the current system. Moreover, technology that has been entrenched often remains because members are not engaged to discuss how technology could improve their work – such tasks are left for upper-level managers and consultant-experts who are often totally disconnected from the on-the-ground practices – referring instead to irrelevant and dated documentation crafted by a different group of removed, decontextualized technical experts.
Intellectual problems can be distinguished into two categories – insight problems and algorithmic problems. Everyone has an intuitive understanding of the difference – algorithmic problems are those with clear goals, established rules and a prescriptive process for their completion. Arithmetic problems are the stereotype for this category, but there are others, such as how to fix the problem of a flat car battery, changing a lightbulb or quench your thirst under mundane circumstances.
Insight problem solving is the hallmark of what William James called sagacity – wisdom, rather than knowledge. These problems are what some would call “non-linear” or “lateral.” The solutions are unobvious at first, but, once described are generally easy to understand by those who understand the problem. The solutions are famous, often to the point of being folkloric – Newton’s concussive fruit or Archimedes’ wet bathroom floor for example. The psychologist Karl Duncker conducted experiments on this kind of problem, famously he presented subjects with a box of candles, a box of tacks and a box of matches. Subjects were asked to find a way to affix the candle to the wall, light it and prevent wax from dripping onto the table. This required subjects to circumvent the “functional fixedness” of one of the boxes as a container and use it as a shelf by affixing it to the wall with tacks.
Importantly, Duncker and others have done hundreds of variations on this experiment, of relevance is the role of incentives. External incentives to complete the task diminished performance – offering a reward made people take longer to complete the task relative to those not offered a reward.
So, external incentives erode performance in insight problem solving, as does the phenomena of functional fixedness. This is true of individual people, what relevance does it have for groups?
Traditional organizations attempt to solve the problem of group cognition by centralizing it. Recruitment discovers talented, intelligent people and sticks them up top – they become the “brains of the operation” with the remainder of management relegated to autonomic nervous functioning – keeping the operation smooth until signals from the central nervous system change that behaviour. This worked well when the environment in which organizations operated moved at speeds with which it could cope. Humans have nervous systems attuned over evolution to the speed of operation of the physical world – we have no equipment, biologically speaking, to deal with, say, the speeds of computers.
Traditional organizations implicitly took an approach to cognition that resembles the approach taken by Good Old-Fashioned Artificial Intelligence (GOFAI) researchers for modelling cognition. Simply describe the problem domain, generate a theoretical solution, connect the dots. To describe the problem domain, simply recall all information about similar problems, identify past solutions and transform as necessary for context. The problem domain must simply be defined comprehensively and formally in an interperable fashion to the organization/computer. This was common-sense in the 1950s amongst AI researchers like Hillary Putnam or Jerry Fodor and is standard operating procedure for corporations, governments and NGOs today (crack open an organizational theory textbook and the painful, noble failure of GOFAI haunts the pages).
It didn’t work – we got avocado-coloured appliances but they couldn’t think. AI researchers then believed that computing power would solve the problem – having the ability to search that problem and solution space and connect those dots lay it simply doing everything faster. This sounds like many business-management fads, “lean, lateral teams” or the marketing buzz of acronym-laden business software CRM,CMS,ERP,BPM,OLAP and the conventional assumptions of strategy (react faster to the world around you) and the role of the web (get your word out faster, understand the statistics faster). Everyone wants to get their inputs faster, believing that a rapid-fire iterative observe-react cycle will solve the problem.
Xenon Pylyshyn, Daniel Dennett and Jerry Fodor can tell us why this thinking is folly – the underlying structures are broken, speeding up non-cognition will no render you cognition – though it might render a sufficient facsimile that you don’t pursue the real solution. The missing component, the real “secret sauce” of this kind of issue is relevance realization. Insightful people are able to put their finger on what is relevant in a given circumstance quickly and easily – they don’t explore the combinatorially explosive solution space of all possible vectors, they go straight for the goods.
To be successful, organizations must do the same thing, they must have processes in place to identify the relevant factors that will guide the formulation of the solution – no individual can do this because no individual can be expected to comprehend the information required. Even if one isolates only the relevant information for a given problem, for an organization of any scale, this exceeds the human capacity to comprehend – we’ve broken the biological barrier to cognition. Thus, the key to an adaptive, sustainable organization is system for collaborative, distributed insight problem solving through a system structure of relevance realization.
How to establish such as system, and the principles guiding its elaboration, are the subject of a future post.
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