In a previous article, we set out some techniques to ensure clarity of objectives for any critical decision in your organization. But as well as defining goals, leaders need to understand and respect what decision scientists call ‘constraints’ – the lines that can’t be crossed, and the types of side-effects of any consequence that won’t be tolerated.
In risk critical industries from financial services to healthcare, regulations guide professionals on the constraints that should shape their decisions – particularly for reasons of safety, ethics and legitimacy. For example, banks have capital requirements to protect both themselves and the financial system from collapse. The aviation industry is subject to intense safety protocols and ongoing checks. But regulation can lead to a focusing on specifying ‘means’: steps which have to be taken – or are prohibited. And an equal focus for decision-makers should be specifying the range of outcomes that they do not want, how deeply they wish to avoid them, and why.
Embedding a thorough understanding of such constraints and their underlying rationale is essential or effective decision-making. But it requires engaging with complex areas such as risk appetite and grappling with the practicalities of practical constraints that tie our hands. How many organisational leaders know and factor in the capacity of their staff to absorb new information or protocols in a specific period of time? How good are we at tracking the mental health impacts of different roles and shaping support accordingly? How well do management teams understand their capacity to manage a certain number of programmes or staff? In public services, how clear are we on what decision scientists call ‘equality constraints’ – for example, our tolerances for different geographic areas or populations getting different levels of service?
There are a variety of techniques to ensure decision-making takes account of constraints. For example, for high stakes decisions, it can be worth investing in complex mathematical models (constrained optimization modelling). But progress can be made by following three simpler steps:
- Ensure you have a standardised decision-making process or ‘checklist’ for high value or regular decisions – and that this includes consideration of decision-making constraints. Processes and checklists may need to vary depending on the type of decision you are making.
- Where possible, quantify different constraints to support improved decision making. Ideally, ensure information systems provide visibility on how constraints are evolving over time, ideally using intuitive stories and visualisation techniques.
- For critical constraints affecting high value or repeated organisational decisions, ensure that everyone in the organisation is aware of them
Sometimes understanding what you can’t or aren’t willing to do is as vital for effective decision-making as understanding what you can do.