Match your decision tool to the current decision.

And that's what this tool can do. It helps you figure out when you should use which type of tool. On the basis of three questions, you identify which of 7 categories the decision you are considering belongs to and which tools you can use that can reduce the uncertainty surrounding the decision.

We have the tool from an HBR Toolkit which is very aptly named: Deciding how to decide (2013) by Hugh Courtney, Dan Lovallo and Carmina Clarke. This is just a brief description, if you want to go more in depth, I would recommend you to read the entire hbr article.

The model consists of three questions:

• Is the full causation known? That is Do you know what it takes for the decision to be successful?
• Are the results of the decision known? To what extent can you predict the possible outcomes?
• Should I gather more knowledge? How centralized is the relevant information (ie inside or outside the organization)?

To answer these questions, the authors set up a series of auxiliary questions you can consider to get a clearer picture of the diagnosis of the decision. We review them below:

Is the full causation known?

The strength of the knowledge you have about causal relationships between critical and economic conditions, what the authors call your causal model, is decisive for how good decisions you make. One way to test the strength of your causal model is to consider whether you can with high certainty formulate a series of "if-then" statements about the decision. An example from the text: “If our proposed new process technology lowers costs by X % and we are able to gain Y % of the market shares, then we should invest in this technology.

Furthermore, you should consider whether you can describe an economic model in which you can insert different assumptions. Eg. how much the technology lowers costs and how much of the market share you can achieve.

As the authors say, for the vast majority of strategic decisions, there is no specific causal model. In some cases you will be able to give a fairly clear overview of critical risk factors and in others you may be completely in doubt as to which framework the situation should be inserted into.

Consider:

• Do you understand what combination of critical factors will determine whether your decision leads to success or not?
• Do you know what goals you have to achieve before it becomes a success?
• Do you have a precise understanding of – almost a recipe for – how you achieve success?

Are the results of the decision known?

Sometimes it is possible to predict an outcome with reasonable certainty, e.g. when the company has made similar decisions many times before. Other times, one can predict a range of outcomes. When there is great uncertainty, it is often the case that managers cannot describe what results a decision can lead to.

Consider:

• Can you define a range of outcomes that could potentially result from your decision
• Can you measure/judge the probability of each outcome?

Should I gather more knowledge?

By answering the questions below, you can get an overview of what type of information you need, and not least which tools you can use with the greatest results.

Consider:

• Is the information you need centralized or de-centralised? That is is it available in the organization or do you have to go outside?
• If decentralized: Do you have access to the experts who have the knowledge you need?
• Is it possible and does it make sense to use crowdsourcing to collect parts of this knowledge?
• Is it possible to gather knowledge from the crowd without releasing confidential information?

With this knowledge in hand, follow the information map below to find out which tools match your decision.