Making a decision. Sounds easy, right? Actually, a lot of people and teams struggle to make decisions – and it’s not getting easier. With more and more data and other information available, people can easily fall into the trap of information overload and analysis paralysis.

Of course, some decisions are harder to make than others – because of pressures of time, or complexity of understanding the options, or the potential impact of each option. The greater the perceived risk and trade-offs of making the wrong decision, the harder the decision making process. It’s usually impossible to remove all risk from a difficult decision making process – but at least bringing them out in the open to discuss as a team, and understanding them are good starting points.

There are various frameworks which can be used to help teams make better decisions. Breaking down the process of making a decision, most situations follow a surprisingly similar flow

• Definition: What is the actual decision that needs to be made? Is it clear to all those participating in the decision making process? Let’s get everyone aligned as a first step
• Context: What’s the context in which we’re having to make this decision? Are we conscious of what’s going on around us?
• Options: Then, you need to consider the options available. Don’t forget to include the option to do, or decide, nothing – sometimes this is a perfectly legitimate option. Many people stumble at this stage because they feel they don’t have enough information – or they have too much information. As a leader, you need to make a call as to when to make the decision. There will always be more information out there, so watch out for people in your team who may be using this as a ploy to delay the decision, or not make one at all. You are likely to have to live with some ambiguity as you will never have ‘all the information’.
• Consequences: Take some time to understand the consequences of each option you’ve listed
• Prioritise: Prioritise the list of options – as you place one option above another, sense-check that the decision higher up the list is a ‘better’ outcome than the one below it. Then take the decision that tops the list.
• Review: Take time to review the decision you are making. The timing of the review will depend on each situation – but it’s a critical part of the process to ensure you make better decisions in the future.
• Action: Take action on the back of the decision. Think about how to get ‘buy-in’ from stakeholders who weren’t involved in the decision making process for whatever reason.

A side-benefit of following – and documenting a complex decision making process, as well as helping teams make better decisions, is that it can also act as an audit trail.

Some classic decision making errors to watch out for

1. Haste Over Wisdom:
   • Error: Making decisions hastily without sufficient data or consideration.
   • Impact: Deciding in haste often leads to regrets, as critical information may be overlooked or hastily dismissed.
2. Narrow Perspective Pitfall:
   • Error: Restricting the analysis to a narrow perspective, potentially addressing the wrong issue.
   • Impact: Prejudging or confining the decision within inappropriate frameworks hinders a holistic understanding, leading to misguided choices.
3. Over-Confidence Trap:
   • Error: Placing excessive confidence in the decision itself or an overestimation of one’s understanding of the issue.
   • Impact: Overconfidence can lead to complacency and blind spots, jeopardizing the accuracy and effectiveness of the decision.
4. Rules-of-Thumb Pitfall:
   • Error: Relying on simplistic frameworks or shortcuts for important decisions instead of conducting thorough analysis.
   • Impact: Using rules-of-thumb may lead to suboptimal outcomes, as decisions based on inadequate analysis are more prone to error.
5. Filtering Flaw:
   • Error: Screening out unpleasant findings or data that contradicts preconceived notions.
   • Impact: Filtering introduces bias, distorting the decision-making process and potentially leading to choices that are not grounded in objective information.
6. Juggling Complexity:
   • Error: Managing multiple variables or pieces of information without a solid analytical framework.
   • Impact: Without a structured approach, attempting to juggle numerous factors in one’s mind can result in confusion and the oversight of critical details.

Questions to help frame the decision making process

The questions below might help improve the quality of the decision making process you’re about to embark on:

• Can we agree on how we’re going to make this decision? Is it clear to everyone in the room?
• Are the right people involved in this decision?
• Historically, has this decision had to have been made before by a similar group in a similar situation?
• Does the decision we make on this issue affect any other decisions we’ve made?
• Do we really need to make this decision? Linked to the point above, it may be that the decision not to decide is a legitimate way forward.
• Do we understand the timing of this decision making process? What time pressures are real, and why?

Ultimately, if this is a difficult decision to make, then there’s probably no ideal outcome – life can be like that! Dealing with the consequences of a decision you and/or your team has made is part of being a leader (or decision-maker).

Decision trees as a tool

Decision trees can be great tools to better structure decision making – especially if you’re working as a team to make a decision.

Understanding Decision Trees: A Powerful Decision-Making Tool

A decision tree is a visual representation and analytical tool that helps businesses make informed and strategic decisions. In essence, it resembles a flowchart, where each node represents a decision, and each branch represents the potential outcomes of that decision. This structured tree-like model assists in evaluating various alternatives and their consequences, aiding businesses in choosing the most optimal path forward.

Here’s a simple but clear example (source: @levikul09 on Twitter/X https://tinyurl.com/22vcv3sm)

They can become much more sophisticated depending on the situation – more examples below, but the essence of the decision tree is exactly the same, however complex it is.

Key Components of a Decision Tree:

1. Root Node: The starting point that represents the initial decision to be made.
2. Decision Nodes: Branches emanating from the root node that represent choices or decisions at various stages.
3. Chance Nodes (Probability Nodes): Points in the tree where the outcome is uncertain, and probabilities are assigned to each potential outcome.
4. End Nodes (Terminal Nodes): The ultimate outcomes or results of following a specific path through the decision tree.
5. Branches: Connections between nodes that represent the progression from one decision or event to another.

Example of Decision Tree Usage in Business:

Consider a retail business deciding whether to introduce a new product line. The decision tree can assist in evaluating the various factors influencing this decision and predicting potential outcomes.

Root Node:
The initial decision is whether to launch a new product line.

Decision Nodes:

1. Market Research:

• If the market research indicates high demand, proceed to the next decision node.
• If the market research indicates low demand, abandon the idea.

1. Competitor Analysis:

• If the competitors are not offering a similar product, proceed to the next decision node.
• If competitors have a similar product, consider the next decision.

1. Production Cost:

• If the production cost is manageable, proceed to the next decision node.
• If the production cost is too high, abandon the idea.

Chance Nodes:

1. Marketing Success:

• If the marketing campaign is successful, proceed to the next decision node.
• If the marketing campaign fails, assess the impact on the next decision.

1. Consumer Response:

• If consumers respond positively, proceed to the next decision node.
• If consumers respond negatively, reassess the situation.

End Nodes:

1. Launch Product:

• If all previous decisions and chance events lead to positive outcomes, the business decides to launch the new product line.

1. Do Not Launch:

• If any critical decision or chance event leads to a negative outcome, the business decides not to launch the new product line.

Benefits of Decision Trees in Business:

1. Structured Decision-Making: Decision trees provide a structured framework, making complex decisions more manageable and understandable.
2. Risk Assessment: By incorporating probability nodes, decision trees allow businesses to assess and quantify risks associated with each decision.
3. Resource Allocation: Businesses can optimally allocate resources by evaluating potential outcomes and focusing efforts on decisions with the highest likelihood of success.
4. Scenario Analysis: Decision trees enable businesses to analyze multiple scenarios and understand the potential impact of different choices on overall outcomes.

Further reading

• The tweet from @levikul09 which we cite above is a great starting point for more on decision trees.
• For a more business-like example, here’s a decision tree summary of how Slack decides whether to send a notification, written by @matt_chandler. Whilst more ‘professional’ than the one above, you can see how it follows the same principles.
• IBM have an ‘IBM-style’ explainer on decision trees here.
• Harvard Business Review have a great article on using decision trees, with a few great examples.