A Step by Step Guide to Test & Validate Your Business Idea
In the previous article, we have discussed the initial steps in arriving at a validated business idea. In this article, we will discuss further steps to achieve the same. The following are the steps continued from part 1 of this article.
Once you have put your assumptions, you prioritize them in the order of their importance for making your business idea successful and the evidence that you have for supporting those assumptions.
All the assumptions are put in the suitable sections of the box shown below based on their relative importance and the evidence.
Evidence is real proof to prove your assumption.
Here it should be noted that the evidence to support your assumptions should be based on the data that you get from your real customers and not just the facts from the internet or other source.
Facts can be like “50% of the urban population is concerned about the waste disposal” while the real data is “the actual percentage out of this 50% who have really tried to do something to solve the waste disposal problem”.
- Here the assumptions that fall in the top right quadrant are the riskiest ones as they are important but you have little or no evidence to prove them. Hence if these assumptions turn out to be false, the business idea will fail.
- The assumptions that fall in the top left quadrant are also important but you have put them here because you think that you have strong evidence to support them. Ask yourself if you really have strong evidence. Check and recheck to make sure the evidence is really strong and justifiable.
Once you have put your assumptions in the graph above, take note of those assumptions that fall in the top right quadrant of the box above. As already stated, these are your riskiest assumptions.
You then turn only these assumptions into hypotheses. The book “Testing Business Ideas” by Alexander Osterwalder and David J. Bland describes that good hypotheses are assumptions that are testable, precise, and discrete.
Testable – when it can be proved to be true or false based on the evidence.
Precise – when it can precisely describe what you really wish to achieve.
Discrete – when it describes only one distinct, testable, and the precise thing you want to investigate.
Suppose that you have a business idea of providing predictive maintenance service to electronic goods-producing companies using IoT (internet of things).
The following table clarifies the meaning of testable, precise and discrete:
It’s important to note that you choose to turn very few (only 2 or 3) and not all assumptions into hypotheses because if they turn out to be wrong, there is no reason to proceed further and test each one of those assumptions. You may then choose to pivot or switch to an entirely different business idea.
While writing the hypotheses, it’s important to be quite specific about your assumptions. Initially, you have written your assumptions in a general way. But now you become more specific by mentioning the geography, demography, industry type, etc. whichever applies to your assumptions based on ‘testable, precise and discrete’ characteristics.
In this step, you design and choose an experiment to get the evidence for each of the chosen hypotheses described in step VI. There is a list of experiments given by Strategyzer (in their book, “testing business ideas”) where you can choose from. Examples are email campaigns, customer interviews, simple landing pages, paper prototypes, clickable prototypes, letter of intent, split test, 3D print, etc.
There are also other experiments given by Innovation Games like ‘speed boat’ or ‘buy a feature’ that you can use.
Choose the one which is most suitable for testing your hypotheses. While choosing experiments, keep the following points in mind:
- Choose the experiment that is cost-effective and quickly produce evidence.
- While starting, you have little or no evidence for a particular hypothesis. Hence it’s always preferable to choose the experiment that allows you to quickly obtain the evidence. Here your only goal is to get the evidence (even if it’s a weak one) to ensure that you are moving in the right direction.
- As your hypothesis moves towards confirmation, you may choose experiments that produce stronger evidence to prove it.
To understand the above points, take the same example of providing predictive maintenance service to electronics goods-producing companies.
- Suppose your important hypothesis, “head of maintenance departments of electronic goods-producing companies are desperate to get rid of the problem of frequent breakdown of critical machines” has no evidence in the beginning.
- Your only goal, then, is to know that this is truly a problem for the electronic goods-producing companies. Thus you can choose to conduct customer interviews as your initial experiment.
- After conducting interviews, you come to know that your hypothesis is correct. Now your next step is to validate and you can do it by seeking a letter of intent from your customers to see if they would actually pay you for your offered service.
Once you have chosen your experiment, you now put all your data on a sheet of paper (called a test card by Strategyzer). The data is written in 4 steps as follows:
- You write your hypotheses
- Then you write the test that you will perform to verify your hypotheses. The test is performed with the experiment that you chose in step VII above.
- Then you write the metrics that you will use to measure the outcome of step (b). For example, the metric can be the conversion rate that tells you the number of prospects that convert into your customers.
- Finally, you write the Criteria that define your success. Criteria is based on the value of the metric that you expect to prove your hypotheses through the test that you perform in step (b)
Note that the test cards are prepared for each of the hypotheses that you have selected. It’s explained with the help of an example below:
Once you are done with step VIII and achieve the metric value that you had expected by implementing the test card in the real world for each of the chosen hypotheses, you may now conduct the next set of experiments to produce stronger evidence for validating your hypotheses as explained in step VII.
The more you conduct different experiments for your business idea, the more you reduce the risk of failure. The choice of experiment-type depends on your hypotheses.
In step I through IX, you have validated your desirability and viability assumptions. Now you have data-backed evidence that customers need/do not need your offering (desirability) and will pay/ not pay you for it (viability). But whether you can build your offering or not (Feasibility assumption); still remains unanswered.
If your desirability and viability hypotheses are proved to be wrong, you need not test your feasibility hypotheses. But if they turn out to be correct, you can proceed further.
Thus in this step, you sketch you business model canvas first. Your assumptions are:
- Related to Key Activities Section: “we can perform & manage all key activities to build our business.” (A Feasibility Assumption)
- Related to Key Resources Section: “we can acquire and manage resources like intellectual property, human resources, etc. and also technologies that are required to build our business.”(A Feasibility Assumption)
- Related to Key Partners: “we can create a required partnership to build our business.” (A Feasibility Assumption)
After you have written your feasibility assumptions, you follow steps V to IX to validate them in the same way as you did for desirability and viability assumptions.
To Wrap Up
Testing your business idea is an important activity before you start to build anything. Building before testing puts you at a higher risk of moving in the wrong direction and eventually ending up with a failure. The above approach guides you systematically and scientifically and also help you to reduce your risks drastically while pursuing your business idea.
Do you feel there is something more to be included? Kindly write to us. We will be more than happy to consider your valuable suggestions.