Western culture is focused on success. The mass media strengthens this message. In advertisements, TV and on the covers of magazines we can see beautiful, smiling, healthy and happy people of success. They are everywhere. It’s really easy to forget that this world is not real - it is artificially created.

Even if the media are showing real cases of people who have succeeded, they usually don’t show what is behind the success (hard work, number of attempts, the time-consuming process of building skills, etc.).

The concept of failure, and learning from it, isn’t part of the education system (at least it wasn’t, when I was at school - I’m observing some positive changes here). Failure is seen as an unpleasant event that occurs as a result of unpreparedness or some lack of ability in certain areas. Failure is not widely accepted in our culture. I think it’s often seen as a weakness.

Entrepreneurship, innovation, and the myth of constant success

But hey, can we be always right? Can we always succeed? I hope the answer is obvious for you: no.
What if we can include failure in the systemic and iterative research of the business environment?

But hey, can we be always right? Can we always succeed? I hope the answer is obvious for you: no.
What if we can include failure in the systemic and iterative research of the business environment?

Today I would like to write about an approach known as “Fail Fast, Fail Often” which is, in my opinion, probably the most misunderstood business concept among agile approaches.

What "Fail Fast, Fail Often" really means

First of all, we need to make a distinction between a big failure and a small failure.

“Failure, to fail - lack of success in doing or achieving something”, Oxford Dictionary.

Big failure vs small failure

What is a big failure? You are likely to see a big failure when the costs of failing are very high, or when failure is so serious it is difficult to deal with the consequences. For me it could be a big investment in a product or service that nobody cares about or it could be bankruptcy of the company. It could be an organisational breakdown (for example, if the most valuable people in a company leave). This is definitely not the kind of experience we want to have; it is something to avoid.

Of course, this can happen to anybody. If the worst happens, there is nothing else but to treat it as a lesson. Learn how to avoid similar situations in the future (actually, it is very interesting how many entrepreneurs have gone through very serious trouble before they have achieved business success).

A big failure is something we definitely want to avoid. It is not a desired outcome.

What failures are we looking for then?
Small failures inside controlled experiments, so we can learn quickly and reduce risk to the business model.

From assumptions to evidence: business design validation loops

I hope you agree with me that we are not able to be 100% right all the time. We might not be able to generate the final solution on the first attempt. In the beginning, we might not be able to understand the business environment or the customer segment as well as we need to (especially if the world is fast-changing and when our ability to use the past experiences is limited).

All we can do is:

• Avoid failure, masking it with detailed plans. If this happens we can see failure as an unpleasant experience which should be abandoned as soon as possible and might be excused in some way.
• Take it as a part of a learning process - embrace it as a means to learn and improve and accept this as a necessary part of the process, a part of continuous learning.
  
  

The the assumptions of the new idea need to confronted with the reality as quickly as possible. And, if the assumptions were not right – this is the kind of fail that we are talking about.

If we have an idea, we need to confront its assumptions with reality as quickly as possible (we don’t want to fall in love in our idea). There is always a chance our assumptions are not right, and this is the kind of failure we are talking about.

If we realise early on, that our assumptions are not true (fully or partially), we can improve our idea, and then check our new assumption against reality again.

If we realise early on that our assumptions are not true (fully or partially), we can improve our idea, and then check our new assumptions against reality again. This becomes a validation loop. In business design, we turn assumptions into testable hypotheses, run lean experimentation, and gather real-user feedback cycles.

It is quite possible that we will need to repeat this many times before our initial idea fits reality well, and we will have enough evidence to be quite sure that the idea will be successful. In practice, that evidence is built step by step through customer discovery, value proposition validation, and business model validation. That sequence is what turns entrepreneurship from guessing into evidence-based decision making.

If our idea is not good enough we want to know it as quickly as possible. If something is going to fail, we want it to fail quickly. Only then can we evaluate it, learn from it and build a better version. We want to fail quickly. Again it’s not a goal; sometimes the right solution cannot be simply found on the first attempt.

If we want to learn quickly, we need to check our assumptions against reality often. When a lot of little steps are taken, it is easier to capture the learning quickly, and it helps to find an optimal path faster. And before we will find it, some attempts will not be successful. It’s a part of the process, it’s not desired, but it’s accepted. We want to fail often.

The true aim of “Fail Fast, Fail Often” is to reduce risk, especially the risk of a big failure.

The true aim of “Fail Fast, Fail Often” is to reduce risk, especially the risk of a big failure.

The need for a system: from random failure to evidence-based experimentation

If you want to produce good evidence quickly, to be able to learn and make a good decision, you need to test your assumptions in a systemic way. If you test your assumptions without the proper structure, you will fail happily again and again without a well-structured outcome.

That structure can be simple: define a hypothesis, run a small test, capture the learning, and repeat. Over time, this becomes a culture of evidence-based decision making.

I will write a bit more about building the right system in future articles.

I hope you all fail successfully!