We worry, it’s natural. But, in the words of Bobby McFerrin, ‘Don’t worry, be happy‘ when you’re making decisions!
We read a lot about foresight as a way to enable organisational resilience. Decision-makers being given access to early warning systems that allow organisations to become proactive instead of reactive – the type of systems that analyse data and information to pick up tremors, disturbances in complex environments, and amplify them for decision-makers; allowing them to weight their threat or risk and develop an appropriate course of action.
If only it was that simple. Foresight. The crystal ball that shows us the future. You turn on your iPad/phone or, to remove my Apple bias, Android device, open ‘The future today’ app, a bargain at 69 pence for the lite version; though deep analysis, including light signals that have not yet reached Earth from the extremities of our solar system, requires the full version at a cost of £1069 (updates are free, but the alien encounter version is not due out until 2014 and will cost a further £500).
This idea of developing organisational resilience through foresight is flawed. It is reliant upon people making evidence based decisions and, as we know, people are fallible. In the first instance decision-makers are dependent on systems that present the right data or information in order to overcome availability heuristic, and, even when the best data or information is presented, the decision-maker has to overcome the affect heuristic.
Now, let’s focus on two particular domains, complicated and complex, and their impact on our decision making capability. The idea of organisational foresight leads to a complex domain and probability based decision making over rational, certainty based decision making. In simple terms, as data and information becomes available to the decision-maker it becomes more familiar and the decision maker begins to visualise the problem; they begin to see patterns in the data or information, making the potential event seem more probable. The decision maker then attempts to attribute a decision weight to a perceived threat or risk based on rational reason; the problem is that rational reasoning is problematic outside of an ordered domain.
Research by Daniel Kahneman has proven that in the complex domain the decision weight becomes skewed, with decision-makers giving too much credence to highly improbable events. The table above is based on Kahneman’s research and demonstrates that beyond the rational domain decision-making, especially around threats or risk, is fallible and we have to question our ability to trust our own instincts.
The problem with the complex domain leads us back to availability and affect heuristics; the more time spent considering any given environmental disturbance, the more familiar it becomes; the more familiar, the more the decision maker worries,; the more worry, the more real it becomes in the mind of the decision maker; the more real it becomes, the more real the threat; the more real the threat, the greater the feeling of loss and the greater weighting it receives in the decision-making process. What Kahneman demonstrates is that we worry too much about improbable events. This can lead organisations to spend huge amounts of money to mitigate a risk that is overweighted by the worrying of the human mind.
From a KM perspective, where do you want to put your resources? Should we focus on the probable or the improbable? Is resilience determined by our ability to negotiate the improbable or the probable?
The concern, going back to the table, is that the decision weight drops off, in comparison with the certainty of the complicated domain, when the probability increases – we over weight the improbable and under weight the probable. Now that’s a threat worth considering!