Good decision-making depend on understanding what goals the decisions serve, and what information and processes we will use to make that decision. It is not unknown for decisions to be made in haste, or with poor understanding of the context, or miscontrue external influences.
An example is mismatching the evidence generation process, used to provide clinical research evidence of a product’s value to payers, with the stage of decision-making by the payer. Payer decision-making is a gated, binary process; that is to say, it has a linear structure of stages, and at each stage (gate), it is a yes/no decision. Failing at a gate (getting a no) means the product goes no further. What this process looks like is important. Not understanding it means that the wrong evidence is provided at the wrong time, betraying a lack of understanding of how information is used.
Clinical workflow is also a decision-making process so we need to know how clinical decisions are made. The same applies to how patients make decisions around their use, or not, of their medicines (called adherence).
We also know about the risks of groupthink, and its impact on the quality of decision-making. Methods designed to challenge thinking are important to ensure that the right problems and issues are being addressed. In policy making environments, this involves critical issues as policy making processes usually lead to legislative processes, and the use of instruments (laws, penalties, etc.) to enforce the law: getting this wrong can lead to policy gaming, or non-compliance. Commercially, this can mean that the decisions reflect personal preferences or influences, rather than an evidence-informed assessment of what the real commercial options are. Tools such as Devil’s Advocacy, Red Team are well-established approached used to ensure high quality decision-making.