For decades now, we have seen motivational texts in books, newspapers, and social media that ask us not to be afraid of failure. The whole point is to allow yourself to pick yourself up and move forward, which is quite a noble goal in itself if you ask us. But there is a lot more to the science of failing, and it’s about time the industry stops brandishing its cowardice and opts for more experimentation and slightly risky behavior.
When you experiment more, you fail less. So, naturally, the executives and authorities in all industries should just begin experimenting! It’s going to decrease their chances of failure! But experimentation comes with the risk of losing the money it took to set up the experiment and the time that was ‘wasted’ because, ultimately, the experiment was a failure. However, failing less does not necessarily equate to not failing at all. The goal is to make failures cost-effective while still allowing us to learn what we can from the experiment. Experimentation does not have to be a one-off event that puts everything the company has worked for at risk; this approach very evidently creates losses for the company and will be very risky to execute. The key is to enact small experiments from time to time. They can be done at a smaller scale, not incur financial losses, and many of them can be performed alongside actual work, so no time is lost either.
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How To Experiment More?
We are taught how to conduct experiments in high school, and no matter where we go from there, experimentation always plays a role. To experiment effectively, here are the steps you should follow:
- Established a well-defined hypothesis, preferably one that is supported by some statistical data. Try to conduct surveys or collect statistics before designing the experiment.
- Develop a context for your experiment where you define the dataset and whether you will be picking it up from a pre-existing database or test the situation out by yourself.
- Make sure you have some theoretical evidence to back up your experiment, it will help you address the validity of the results while also helping you keep track of the variables.
- Carefully design the experiment by defining variables, planning the setup and the equipment, and describing the protocol.
- Put the experiment in place as you have designed it.
- Test the equipment.
- Do a trial run
- Start experimenting.
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A thoroughly researched and well-designed experiment in itself greatly reduces the chances of failure. If enough failsafe measures are taken, there will also be much fewer monetary losses as well.
While this is an exhaustive list of the steps you need to take to experiment, with the help of digital simulations, going through all these steps has become infinitely easier. Here are some steps you can take to ensure that the chances of failure or the cost of failure are greatly reduced:
- Pretotyping – It refers to a quick experiment that aims to test ideas at a low cost while still gathering enough data to build a valid prototype.
- Scouring Test Sites – Real-world locations can act as test sites for conducting controlled experiments.
- Testing Small Codes – Have a team test out small application codes and do a test run of new features before introducing them
- Simulation Software – This software, including MatLab and OpenSim, is integral to creating simulations you can eventually test out.
The cloud computing system, which is swallowing up organizations by the hundreds, is now integral to experimentation in organizations. One of the major benefits of cloud technology is that it is scalable and low-cost. So experimenting with the help of cloud computing can enable organizations to spend a small fraction of money to test out new inventions or services. Since the cost of failure in cloud experimentation is so little, the development teams in organizations actually feel a sense of curiosity and excitement and adopt a much more problem-solving and convenience-oriented approach to their business by experimenting and testing everything they can.
Another excellent way to utilize the cloud for experimentation is by ensuring that developers take their time to experiment slowly and surely, instead of creating large-scale, risky situations where failure is not an option. Incremental progress is always better since it provides an opportunity to learn, and there is little chance of massive failures.
How To Fail Less?
Failing less refers to curbing the eventual damage of failure and not decreasing the infailure count. The Google Graveyard and Microsoft Morgue are two prime examples of services and products that have essentially been ‘killed’ by their respective manufacturers since they did not perform well enough in the market or because their time had come. So if two of the biggest organizations in the world that are ruling the digital world as we know it can proudly display their failures, we can understand that they might be onto something.
Controlled, small-scale experiments that can help you test features and new innovations without incurring heavy losses are the key. Remember that all good experiments are well-planned, and a failed hypothesis can be just as useful as a hypothesis that passes.
In nothing, then a failed experiment will stop the cascade that will lead you to test out something your experiments were building. Sometimes, failures will also help you change your approach to an experiment. All of these changes are necessary for innovation, and our world, at present, is thirsty for innovation.
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Conclusion
It is common to dismiss failures or be chilled to the bone just at the thought of one. However, failures are integral to the establishment and progress of any organization or even an individual. If we accept the inevitability of failures and use them as a stepping stone to layout experiments in the future, it will eventually help us progress. Remember, the goal is not to reduce the eventual count of failures; it is to reduce the ultimate damage caused by failures in terms of time and money.
Further blogs within this how to conduct agile experiments category.