Navigating Uncertainty

Navigating Uncertainty

Navigating Uncertainty 558 344 Exploristics

By Kim Hacquoil, Exploristics CDSO

In our daily lives, we’re constantly faced with choices that impact our future. Some of these decisions may be relatively small, low impact ones like picking a restaurant for dinner or which film to watch. Others might seem bigger and more impactful like deciding what career path to follow or choosing between different investment options. Regardless, decision-making is an integral part of human existence. The complexity of these decisions can vary widely, but when the stakes are high or the choices particularly challenging, a systematic approach called decision analysis can be a game-changer.

What is decision analysis?

Decision analysis is a disciplined and structured process for making choices in the face of uncertainty. It’s not a crystal ball or magic wand to solve all problems, but rather a toolkit of methods and techniques that help individuals or organisations make informed (and hopefully better) decisions. At its core, decision analysis combines scientific principles with practical reasoning to guide you through the decision-making process.

Breaking down decision analysis into easy steps

It can help to ask yourself key questions to break decisions down into manageable steps:

1. Formulating the Problem: What is the decision you are considering?

The first step is to clearly define the decision problem. This sounds obvious but misidentifying the problem to solve or if the problem you’ve chosen is too broad can cause problems later down the line.

2.Identifying Alternatives: What are the choices you are considering?

With any decision, you need to have alternatives. These are the different courses of action available to you. Some options might be more valid or preferable than others but nonetheless, they are still an option.

3.Gathering Information: What are the potential outcomes or consequences of each choice?

To make an informed decision, you need data and information. This step involves collecting data on the possible outcomes, likelihood, and any relevant factors that might influence your decision.

4.Quantifying Uncertainty: Are there uncertainties or risks involved?

One of the strengths of decision analysis is its ability to deal with uncertainty. You assign probabilities to various outcomes to express your degree of belief in their likelihood. This step helps you incorporate uncertainty in your decision-making process which can be key to making better, data driven decisions.

5.Evaluating Alternatives: How do I assess and compare the alternatives?

Using mathematical techniques, such as decision trees or utility functions, you can assess the expected value of each alternative. This quantifies the potential outcomes and helps you make an objective decision.

6.Sensitivity Analyses: How do I test the robustness of my decision?

Decision analysis recognises that your input data or information might not be perfect (even if you include uncertainty). Sensitivity analysis allows you to test the robustness of your decision by varying key parameters to see how they affect results.

7.Making a Decision: How do I make a good choice?

Based on your analysis, you choose the option that best aligns with your objectives and risk tolerance. It may not always be the one with the highest numerical value; it depends on your individual preferences and circumstances.

8.Implementing and Monitoring: How do I assess the impact of my decision?

Once you’ve made a decision and put it into action, it’s important to continue to monitor the situation. Decision analysis doesn’t end at the decision-making stage; it’s an ongoing process.

Real-world applications of decision analysis

Decision analysis isn’t just a theoretical concept; it’s a powerful tool used in various fields:

  • Business: Companies use decision analysis to evaluate new projects, investments or marketing strategies.
  • Healthcare: Clinicians use it to make treatment decisions, considering factors like patient preferences and medical uncertainties.
  • Environmental Planning: Decision analysis helps to assess the potential impacts of environmental policies and projects.
  • Public Policy: Governments use decision analysis to inform policy choices with long-term consequence.

Benefits of decision analysis to clinical development strategies and trial design

Clinical development is fraught with high uncertainty, high risks and numerous different options. Therefore, employing a systematic approach to decision-making through decision analysis has huge potential for people working in this area. It offers:

  • Clarity: Decision analysis forces you to explicitly state your objectives and alternatives, ensuring clarity in your decision-making process from the beginning. This is key for the designing of clinical programs to ensure that you are answering the key scientific or regulatory questions of interest.
  • Risk Mitigation: By quantifying uncertainty and assessing potential outcomes you can make decisions that are more robust and less likely to lead to undesirable consequences. Identifying and quantifying ways to de-risk clinical programs will ensure you optimise the process and reduce the overall risk of clinical development.
  • Efficiency: Decision analysis helps you allocate your resources efficiently by focusing on alternatives with the highest expected value. With high attrition rates for drugs making it through to regulatory success, numerous different pathways to get there, and constraints on resources, utilising a decision analysis approach will ultimately get more effective treatments to patients faster.
  • Transparency: The process is transparent, making it easier to communicate the rationale behind your decision to stakeholders. Often the key decision-makers with regards to budget and program/portfolio level are not the ones who develop the clinical development plans and study designs. Therefore, its key to provide them with reassurance that a rigorous, systematic and consistent approach has been used for decision-making.

A logical approach supporting complex development decision-making

Applying decision analysis for tackling complex choices and navigating the often-uncertain waters in clinical development is a valuable tool for optimal decision-making. Whether you’re an individual facing a crossroads in how to approach a specific problem or part of a team with broad and critical business decisions to make, the structured and logical approach of decision analysis can lead to more informed and ultimately more successful outcomes. So, next time you find yourself at a decision point, consider employing the power of decision analysis to illuminate your path forward.


Read more:

Designing clinical studies for success

Estimands, the what and how of drug discovery

Estimands, opportunity or risk for drug developers?

Estimands in clinical trials

Dicing with Design: Four insights from the sinking of the Vasa

Designing clinical studies for success and not failure

Shifting the development paradigm with innovative trial design

Revolutionising clinical trial design with in silico studies

Statistical Consulting Services

Watch more:

Common causes of clinical trial failure

Can pharma learn from development in other industries?

Matching trial objectives to design via the estimands framework