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The 6 steps to quality decision making
The real game is making decisions. Now. Without perfect information. In the middle of a VUCA (Volatile, Uncertain, Complex and Ambiguous) world. Wikipedia – VUCA
You really need to know the question you are trying to answer.
There are 3 components in framing the real question you need to answer:
1. Purpose 2. Perspective 3. Scope
Being clear on these delivers answers to questions such as:
- What problem are we trying to solve?
- What opportunity are we seeing?
- Why are we doing this and why now?
- How will we know if we are successful?
- What constraints exist?
- How could we fail?
Being clear about your purpose, your question, your objective, is perhaps the most important part of any key business decision making process.
The second thing you need to do is understand the options you really have. What are the alternatives? They have to be real and not theoretical. A decision can’t be better than the best alternative. It takes disciplined effort to identify real alternatives through different scenarios and remove all kinds of bias in the process (List of cognitive biases).
Good alternatives are:
- Based on viable realities which challenge cognitive biases
- Substantially different – not minor variations of each other
- Independently credible – must pass baseline feasibility
- Compelling – motivate at least one decision-maker
- Manageable in number – 3 to 4 usually better than 2 but 10 is too many
The third element of a great decision quality process is data.
Data is about the present and the past but decisions are about the future and its uncertainty.
And not all data is equal. You need relevant and reliable information. You need to consider:
- What information is relative and what is absolute
- What is perceived and what is real – that’s harder than you think for external data
- How valid is your historical data as the world changes quickly – is it valid
- What is the source and what is processed?
- What is the real value of that data – how many reputations are attached to its veracity?
- What do you need to know but don’t? Where is that data? Who has it, if anyone?
- Do you have enough data to make a decision? Sometimes there needs to be.
You rarely have all the things you think you need to make a decision. So how do you do that when you need to decide now?
Ultimately, it is about which of the alternatives across all viable scenarios do we choose, and why.
We value different things, differently. Some Values compete with each other. When alternatives deliver on some valued measures but not others, we need to assess what matters most. Strategy is important. Purpose and Vision should anchor you here.
We use business risk scenario models to give shape to viable future realities and capture our appetite for different alternatives. This step can expand to really validate viable alternatives, with some detailed and rigorous analysis, or, it can be more like a ‘back of envelope’ process, based on executive experience or existing paradigms.
Some of the worst decisions ever made stem from poor understanding of the real trade-off’s being made. (see Executive Summary Report of 644 prosecutions of corporate America since 2000 by State AG’s with $100b+ penalties)
Where uncertainty and complexity are high you need a robust and rigorous approach to see which alternative delivers the most of what you want. Gut-feel alone based on intuition and experience performs poorly over time.
Complex decisions use various tools to assess outcomes and probabilities to get to expected values. And financial models rarely manage decision quality well enough.
There are many tools that can help support key steps in the decision quality process. Some more well known ones include: Porter’s 5 Forces; McKinsey 7S Framework; 5 Why’s; Decision Tree and there are tools that can help create richer data sets, e.g. Monte Carlo method, while avoiding the familiar traps, e.g. Maslow’s Hammer.
The real challenge at this step of the process, however, is bias.
With over 200 different clinically types of bias and the frailty of human nature, it’s no wonder humans are often called out as terrible risk based decision makers and known weaknesses are regularly summarised in risk texts, for example: Operational Risk Management Best Practices A Complete Guide – 2020 Edition. However, my favourite recent book on this is the entertaining read by Dan Ariely Predictably Irrational, Revised – The Hidden Forces That Shape Our Decisions. The best summary I’ve read of mental models that help here is this list created by Gabriel Weinberg Mental models – a list.
To bring all this a little closer to the neuroscience, see some recent research papers which just scratch the surface but are illustrative of how behavioural neuroscience is helping us better understand what is going on in people’s heads as they make all manner of risk-based decisions:
- The neural basis of rationalization: cognitive dissonance reduction during decision-making – which is how, once we have chosen between two comparable alternatives, we then recast one as better than the other.
- This research suggests that emotions, and the ability to regulate emotions, play a critical role in quality decision making – The effect of emotion regulation on risk-taking and decision-related activity in prefrontal cortex
- Thinking like a trader selectively reduces individuals’ loss aversion ‘It is widely acknowledged that emotion plays a role in decision-making, drawing on evidence from numerous behavioral studies using emotional stimuli as well as physiological, neuroimaging, and lesion studies. For example, one study demonstrated that irrelevant emotional states induced by film clips could eliminate or even reverse the endowment effect (higher selling than buying prices – in Trading) in subsequent choices. The results clearly demonstrate an effect of emotional stimuli on decisions, even when these stimuli are irrelevant or below awareness.’
- Measuring individual differences in emotional sensitivity to probability and emotional reactivity to possibility (paid content) ‘Current theories of risk perception point to the powerful role of emotion and the neglect of probabilistic information in the face of risk, but these tendencies differ across individuals. We propose a method for measuring individuals’ emotional sensitivity to probability to assess how feelings about probabilities, rather than the probabilities themselves, influence decisions’.
- In this paper the authors describe the negative impact of scarce resources on the quality of decision making, especially compared with abundant resources – A scarcity mindset alters neural processing underlying consumer decision making
- And one for outside work – With over 70% of adolescent deaths each year due to risk-taking behaviors, such as reckless driving, this paper discusses evidence from developmental neuroscience suggesting that risk-taking behavior increases during adolescence partly due to relatively early functional development of brain regions involved in reward sensitivity – Mothers know best: redirecting adolescent reward sensitivity toward safe behavior during risk taking
There are many research papers concerning decision making and cognitive bias. However, once we can recognise some of our limitations here, we have the chance to make what will be, in reality, the best decision we can make at this point in time given all of the steps leading up to this point.
We will be clear on the question we are seeking to answer, we will have meaningfully identified the viable alternatives from which to select the answer, we will have obtained. Analysed and considered the best available data, we will have weighed up in a considered and balanced way all of the trade-off’s we need to address, and we will know we are making the best reasoned decision we can, clear of all of the biases we can identify and mitigate.
So what could go wrong?
Well, up to this point team engagement has been all about robust conversation, challenging points of view, data, logic. The more we have stress tested the process the stronger the decision will be.
But what often happens is there is no closure. People don’t move to the next phase – decision execution. People don’t move from debate to commitment.
Once the decision is made – the time for disagreement, for revisiting the inputs, is over. It is time to act.
Without action the value of the best alternative is only potential value. Irrevocable allocation of resources are required to execute a decision and make it complete. Thinking and doing are different mindsets.
Once you have made the best decision you collectively believe you could in the circumstances, then the only way to get the value you can from that decision is to execute as well as you can – with shared commitment and effort.
However, there are many hazards ahead.
Many businesses reward good outcomes rather than good decisions – so as soon as it seems the decision might be questioned – by the initial response, the environment, the difficulty of execution – many can second guess the decision quality process and challenge the quality of the decision.
At this point you need to have locked in your appetite to see this through. If there has been a major flaw in the decision quality process, of course you need to revisit. If the world shifts once you have made the decision (think Covid-19) then it is smart to revisit the process. But mostly, without material change to justify, you should stick to your course.
If the decision quality process is sound, then the slings and arrows from those sitting in the stands should not knock you from your path.
Many companies make great decisions but let distractions hurt confidence and undermine reason. There are some key observations about those that make great decisions and stick to them until there is real reason to revisit.
These companies recognise:
- Moving from thought to action can require courage, EQ above IQ
- Conflict is fuel for thinking, alignment is needed for action
- Uncertainty of thinking vs certainty of action
- That doing nothing, is still making a decision.
I’m not sure any of us fully appreciate all dimensions of the problem, or more realistically, the opportunity. I do know that to be relevant and valuable into the future, traditional operational or non-financial risk management needs to build upon a deep understanding of human behavioral science, the power of cognition and bias, environment, increasingly disruptive technology, and the power of competitive forces.
The drive to do more, achieve more, even in a VUCA world, remains strong and those who think hard, take calculated risks and invest – will, in general, do better.