The concept of test and learn is part of our daily lives. From our earliest years, we are familiarized with the act of learning and improving by continually testing and doing. However, when it comes to the world of business, the experience is not always straightforward. In this article, we will explore the test and learn approach, demonstrating how it can fuel growth and pave the way for success.
What is a test and learn culture?
A test and learn culture can be described as the practices that are used to experiment new concepts and ideas. These actions involve engaging with a limited number of customers/stakeholders. The goal is to evaluate the impact on different aspects, such as productivity or sales. In essence, test and learn is all about formulating hypotheses, scrutinizing results and make data-driven decisions.
This approach doesn’t view failure as a drawback, but as a crucial step towards growth. When you test and fail, you will keep all the information that prevent you from repeating the same mistakes. As a result, progress becomes an ongoing journey.
Thanks to the rise of big data and machine learning, businesses have been putting this into practice, becoming a famous approach that not only optimizes operations but also fuels growth.
How to develop this culture in a company?
Test and learn is a philosophy that is not (yet) present in every business. Consequently, many employees feel stressed and unmotivated when they fail to achieve desired results. Often, this is a consequence of the lack of tolerance inside organizations. Many view testing as a waste of resources and failure as a sign of inferiority and inadequacy. However, test and learn increasingly popularity has made many teams wonder what the results would be if they were to use it.
In order to truly integrate this approach into a business, several crucial steps must be taken:
Inspire everyone: praise each team member for their contribution to team work. Sharing achievements and failures is good for the team. Everyone will have a spirit of belonging, and they will feel motivated to grow and become even better. Transparency is essential for building a cohesive and successful team.
Don’t be afraid of showing it all: companies are always seeking new ways to increase sales, optimize customer experience and reduce expenses. By constantly testing new ideas, you’ll be getting new insights on what works best and what might be the direction for the future. By presenting all the collected data, we will make decisions more clearly, and adjust them to the current situation.
Be prepared to fail without hitting the brakes: viewing failure as a learning opportunity rather than a setback is key. Progress also occur when things don’t go as planned. We should keep and share information about the bad experiences in order to prevent repeating the same mistakes. Even after many missteps, it is vital to keep motivated and continue with the experiments.
Progress is not linear: Despite not being a linear progress, test and learn experiments are a great source of data that can be used to improve performance in various industries, including marketing, product development, and customer service. The secret lies in perseverance and not giving up.
By incorporating these principles, businesses can create a culture of continuous improvement, driving growth and success even in the face of adversity.
Characteristics of a test and learn culture
When looking at an organization that embraces the test and learn approach, we can identify some features that they follow. One of the most important is the fact that they see data as the base for their decisions. Rather than solely relying on their intuition, they interpret information and make informed decisions based on this data.
Another important feature is the perspective on failure. In these organizations, they consider it an important part of the process, and it is openly communicated between team members. By continuously learning (even by failing), businesses encourage people to move forward.
Advantages and disadvantages of test and learn approach
The secret to success frequently lies in anticipating what will come next. Companies that conduct tests continually evaluate outcomes are usually better prepared. Among the advantages of this approach are:
- Fast adaptation and reaction: when conducting small experiments, it is possible to assess what the implications are and shift the action if needed. As a result, customers are better understood and decisions are faster.
- Stay ahead of the curve: companies can learn what works better and change according to customer’s needs. This is particularly important if your competitors are not as proactive in their approach.
- Leading innovation: by encouraging new ideas, people tend to be more creative and see problems/obstacles differently. This means that they are constantly looking for new ways to improve.
However, it is important not to forget that there are some disadvantages as well:
- Needs a considerable amount of data: preparing to test and analyze the results effectively can be challenging. First, you need to make sure that you are collecting the relevant data. Secondly, it is vital to interpret the data correctly and apply it when needed. Finally, these activities can be time-consuming and may demand considerable financial investment.
- Finding a balance between experiment and stability: testing is important, but you cannot be misled by it. Once you get an outcome, you must put it into practice. Otherwise, information will get lost, and you’ll be investing in something without seeing results.
The key to mastering this approach lies in striking a balance between the pros and cons. This way, it is easier to deal with complex situations effectively.
Putting it into action
The excellent results of the test and learn approach speak for themselves. There are many examples around us of successful companies that base their actions on this culture. Jeff Bezos from Amazon, even stated that the key to innovation is experimentation. Whilst doing this, it is likely that the result will be different from our initial expectations, but that’s when we learn the most.
When Amazon became more than a profitable book selling, Bezos decided to build large warehouses in many places. At first, his decision made stock prices go down, but in the long term it helped Amazon becoming the leading company we know today.
Netflix provides another successful example of learning from data. Regardless of the cost of experimentation, they know that it’s worth the effort. In one of their articles, they explain that when taking A/B tests, their results “or other causal inference approaches are near-requirements for decision-making”. They use the data to truly understand their members and discover how to entertain them better. As they stated, “because Netflix tests all ideas, and because most ideas are not winners, our culture of experimentation democratizes ideation”.
If you are inspired by these examples and want to start applying this culture, here is a step-by-step guide:
- Describe your problem and what you want to solve
- Formulate a hypothesis about what you think might be the outcome of your experiment
- Project the experiment and the steps you’ll take
- Experiment the different variables
- Look at the collected data and analyze it
- Swing into action by implementing your changes or start all over again to test new options
The process might take longer than expected, but with time results will begin to appear, making it easier to put into practice.
With no risks comes no reward
A test and learn approach values experimentation, ongoing learning and data-driven decision-making. As highlighted, failure is not a negative aspect. On the contrary, it is viewed as an opportunity to grow and learn.
Organizations that adopt this culture are better prepared to tackle new ideas and challenges. Recently, the evolution of software has yielded a wide array of A/B testing tools and experimentation platforms, making them more accessible to various industries and professions.
If you are still questioning the importance of the test and learn culture, remember that “if there is no risk, there is no reward”.
