Decision complexity calculator

A decision can feel hard for all sorts of reasons: uncomfortable trade-offs to be confronted, uncertain possible future outcomes, inevitable resource constraints. This kind of hard is about the over-arching weight, or importance, of the choices you are thinking about.

Complexity, on the other hand, is different: it’s about how many moving parts you’re juggling together – options, criteria, people, timing – all at once.

A decision-making method can’t reduce the weight or importance of a hard decision. But it can clear away the complexity overload, so that what’s left is the choice itself rather than the struggle of keeping track of all the moving parts.

The Decision Complexity Calculator asks a few quick questions about things that genuinely drive decision complexity: approximately how many options you’re weighing up, how many criteria matter for your decision, how many people will have a say, and what’s at stake overall. Your answers are turned into a single read of where your decision sits on a complexity scale. From there, it recommends the best decision-making methods for you.

Decisions tend to outgrow gut feeling because of their complexity – when several potential complexity elements come together in your decision: lots of options, multiple decision criteria, many people involved, repeated applications, etc. That’s when relying on your instinct and intuition starts to let you down and structured decision-making methods come into their own.

Not for everything. A quick and simple approach (and your afternoon back) is sufficient for a low-complexity, low-stakes decision. As the saying goes, “you don’t need to use a sledgehammer to crack a nut.” But that’s usually not why most people are here!

If you’re working on a supplier procurement ranking exercise, shortlisting job candidates, prioritizing projects or allocating budgets or other scarce resources, that’s a more complex and important kind of decision.

A structured decision-making method justifies its place when the stakes are high and keeping track of all the associated trade-offs has outgrown what you can comfortably do in your head. The point isn’t to add a structured method for its own sake – it’s to match the required effort to the complexity and importance of your decision.

Not usually. Beyond a handful of criteria, extra detail often adds more “noise” instead of clarity. You end up splitting hairs on things that barely move the needle on the decision outcome while the actual things that matter get diluted. Psychology research on people’s working memory suggests most of us can juggle only 4-7 things in our minds at once, which is fewer than most decisions throw at us.

A good decision-making method doesn’t ask for more detail. Instead, it helps you focus your precious attention on the criteria that really matter – the ones that will actually help you to separate out and prioritize the options you’re trying to choose between.

They help by making your reasoning more consistent, transparent and defensible, including being potentially auditable. When judgment biases are lurking in your brain, they can lead you astray without you even noticing: you may anchor on the first option, favor the one that’s easiest to imagine, or overlook untested assumptions.

It’s better to set out your decision criteria and their weights explicitly – and to use a valid and reliable method for doing so. A structured decision-making method will not necessarily make you perfectly objective, but it will make your thinking more visible so you can inspect it and do your best to correct for biases.

The biggest risk with a group isn’t disagreement between its members. Instead, it’s that you don’t get to hear about such disagreements properly in the first place.

Best practice is to solicit people’s judgments independently before you all get into a meeting together, so that each person’s viewpoint is captured on their own terms rather than shaped by whoever speaks first or has the highest professional or social status.

Using valid and reliable group decision-making methods – e.g. group voting or a Delphi process – may sound like more work. But doing so usually means more productive group interactions. Also, you, as a leader, get to arrive at meetings with an understanding of where people align and where they genuinely differ, so discussions can focus on what actually needs resolving to build consensus.

Keep a clear record of the reasoning involved in reaching your decision, not just the end result – preferably by taking advantage of MCDA tools (like those offered by 1000minds) to keep track of the criteria you used, how much each one mattered, why each option scored the way it did and who was involved.

When the chain of decision-making logic is visible, two things happen: people who’d have chosen differently can still see the decision was reached fairly, and you can defend it later without having to reconstruct it from memory. A traceable decision is a durable one. It will survive new questions, new people, and the “why did we do this?” that inevitably, and appropriately, comes later.

Best practice is to match your decision-making method to the scale and scope of your decision, and not to its topic or area of application per se.

A small, low-stakes choice between just two options – e.g. whether to do something or not – needs little more than a simple pros & cons list. If you want to add more alternatives to your decision, it’s worth laying them out in a simple pairwise table or a more-advanced performance matrix.

On the other hand, many decisions include potentially dozens (even 100s or 1000s) of options, in one-off or repeated applications, multiple decision-makers and potentially other stakeholders whose viewpoints matter too. They need to reach consensus, and for the results to be communicated and perhaps defended. This is where a more structured and scalable approach like multi-criteria decision analysis (MCDA) pays off.

The Decision Complexity Calculator works these things out for you and recommends the best methods to use.

If you have repeated decisions to make, then a valid and reliable decision-making method will pay off over and over again. Finding such a method is itself an important decision worthwhile making! It will help you make better decisions immediately.

In addition, because your criteria are already defined, you can reuse them without having to start from scratch. A decision you face every quarter – which projects to fund, suppliers to shortlist, candidates to advance – stays consistent from one round to the next and each requires a fraction of the effort to repeat. You also build up a record of how your priorities have shifted over time, which is hard to reconstruct from memory or a trail of emails.

Yes! Franklin explained it in a famous letter to his friend Joseph Priestley in 1772.

Benjamin Franklin (1706-1790) was one of the Founding Fathers of the United States, famous for helping draft and sign the Declaration of Independence and for his diplomatic role during the American Revolution. He was also a renowned scientist and inventor for his experiments with electricity, lightning and bifocal glasses. Among other things, Joseph Priestley (1733-1804) is famous for discovering oxygen.

Franklin begins his letter by humbly reminding us that, although as individuals we may have different preferences, we can still use the same methods (regrettably, we don’t get to find out what Priestley’s decision is): “Dear Sir, In the affair of so much importance to you, wherein you ask my advice, I cannot, for want of sufficient premises, advise you what to determine, but if you please I will tell you how.” Making the decision rests with the person whose decision it is (Priestley) and comes from using a good method rather than being told what to do by other people.

Franklin’s method, which he called “moral or prudential algebra”, is credited as the first formal example of multi-criteria decision analysis (MCDA). For small-scale applications with just two options, Franklin’s method is as potent today as it was more than 250 years ago, but when there are more options to consider, more sophisticated and scalable decision-making methods are required.

MCDA, also known as multi-criteria decision-making (MCDM), is about making decisions when multiple criteria need to be considered together to rank or choose between potentially many alternatives.

A sub-discipline of operations research with foundations in economics, psychology and mathematics, MCDA is concerned with formally structuring and solving decision problems. Instead of scoring everything in your head, you set out the criteria explicitly, determine their relative importance, and see how each option measures up against them.

MCDA reduces biases from decision-makers relying on their gut feeling and group decision-making failures (e.g. groupthink) that almost inevitably afflict intuitive approaches. By making the trade-offs between criteria explicit in a structured way, MCDA results in better decision-making. Most MCDA methods are supported by specialized software, like 1000minds.

Spreadsheets are fine until the weights on your decision criteria start having to do the heavy lifting – which they almost always do. It’s usually relatively easy to determine how the options you’re evaluating are rated on the criteria, i.e. how they perform on each criterion.

However, it’s their weights – representing how much each criterion matters relative to other criteria – that get typed into your spreadsheet without much to back them up that are methodologically risky. If you can’t explain why one criterion’s weight is higher than another’s (and by how much), your decisions will be hard to defend.

MCDA depends fundamentally on applying valid and reliable criteria and weights reflecting decision-makers’ preferences (and potentially other stakeholders’ too). A structured method, commonly supported by specialized software such as 1000minds, derives these weights from peoples’ choices they can think through instead of from numbers pulled out of the air. By making the trade-offs between criteria explicit in a structured way, MCDA results in better decisions.

Once you’re beyond making decisions based on just a handful of options and criteria and involving a single decision-maker or a small group, making decisions reliably “by hand” (or in your head) gets increasingly difficult. This is where decision-making software comes into its own.

1000minds’ PAPRIKA method turns a many-sided decision problem into a series of simple pairwise trade-offs and combines them into a consistent, defensible ranking. It keeps a clear record of how you got there, so the result holds up to scrutiny later. It’s used across healthcare, government, universities and the private sector, including by the World Health Organization, Google and Deloitte.

Try 1000minds and see how the trade-offs, priorities and stakeholder perspectives behind your decision can be evaluated in one place. Sign up for a free trial or book a demo with our friendly team.