Satisficing In Startups

Economics is not very fashionable among startup founders, and with good reason – the field of study doesn’t always translate well into actionable, practical knowledge. Domain, technical, and marketing expertise can be far more important for the success of a startup project.

That said, some economic concepts can give you valuable mental models that can help you think about problems more efficiently. Satisficing is one of them, as it helps you understand the decision-making process of different stakeholders in your project, including yourself.

When discussing the decisions that consumers make, classical economists simplify to make their lives easier – they assume that consumers are perfectly rational (homo economicus) and that they have access to perfect information.

Both assumptions can easily be challenged.

First, in the real world, people are affected by various cognitive biases (i.e. they are not perfectly rational) and need to make decisions under imperfect information.

Second, acquiring information is costly and has diminishing returns – the time you invest in acquiring information doesn’t have a linear correlation with the amount of good information you are able to find. This means that in order to make any decision at all, you need to make them under imperfect information, and the earlier you cut your costs of acquiring new information, the better.

This is why behavioral economics introduces the concept of satisficing – rather than maximizing the cost-utility function in order to make the best consumption decision, people are realistically following the path of least resistance.

Satisficing has a couple of different implications for startups, depending on what startup challenges you are dealing with.

For example, it reveals that the “build it and they will come” cliché is simply wrong and might ruin your project if you adhere to it. Even if the utility of your solution is objectively better, your customers don’t have perfect information.

In other words – they don’t know about your product and its utility for them, and they aren’t willing to invest efforts into acquiring that knowledge.

This reveals how important reaching people and educating them of the utility you offer is to the success of your project, and how the perceived utility can be much more important than the objective utility.

Another good example is the “make everything perfect before you launch” mistake. Just as your consumers, as a founder you lack perfect information. This means that by definition you cannot make your product perfect, as you don’t know what a perfect product is, and acquiring this knowledge has a cost with diminishing returns.

Instead, you need to make your product “good enough” and launch sooner rather than later. Going through this process as quickly and cheaply as possible will leave more resources to iterate and find product-market fit without having to rely on perfect information – rather, you would rely on empirical observations.

In summary, understanding deeply the concept of satisficing would let you escape the trap of thinking you have perfect knowledge regarding your project and how it interacts with the world and would let you make decisions in an imperfect-information framework that helps you manage your risk and resources better.