This is a very useful approach to see life as a process of continuous learning. When we have this point of view, most things happen to us just to give us an opportunity to experience and to learn. This approach will definitely help to live a serene life.
In business, the learning is not an end in itself. Effective learning is a business design tool that enables quick and efficient exploration of complex business reality to achieve our organisation goals. This will help us to understand if we should invest in a solution, and if the answer is ‘yes’, which solution should we choose.
If we fail, just to learn something, we will run out of resources very soon and go out of business. Many failures do not automatically contribute to future success. A ‘Fail Fast, Fail Often’ approach has to be seen as a systemic and iterative exercise, where thinking and critical reflection steps must be taken first. By reflecting during actions and after actions have been taken, we are able to prepare for improvements in our business idea. Let’s say that clearly, Entrepreneurship is an intellectual exercise (too).
Let’s say that clearly, Entrepreneurship is an intellectual exercise (too).
In my opinion, it doesn’t matter if you are working on a new business idea (a startup or innovation) or you are trying to improve an existing one (exploitation of existing mature business). Whether you are an entrepreneur or a corporate intrapreneur, I think firstly you need to concentrate on your understanding of what your customers want and for what they are willing to pay for (you need to do this before you will build a new solution or upgrade existing one).
Secondly, you can start to look at a working business model.
Ash Maurya, one of the lean thinkers said: “The real job of an entrepreneur is to systematically de-risk that business model over time”. And that means you really need to test your assumptions early.
You might say, this sounds nice Witold, but why should I really care about it?
42% of startups don’t care enough about this and die because they work on products with no market need. If you are in the business for a while and you work with established organisations, you might think this problem is only start-up related. Here is an interesting statistic from studies of established organisations: 72% of all new products don’t meet their revenue targets. This illustrates the fact just because your company has been successful in the past, doesn’t mean it will succeed in the future.
Just because your company has been successful in the past, doesn’t mean it will succeed in the future.
Carrying out the right system of testing for new ideas is a big deal. Today is more about approach, which can be a good base on which to build a proper system.
Assumptions
Assumption – a belief or feeling that something Is true or that something will happen, although there is no proof.[1]
Most of our ideas are purely assumptions. And here is our challenge – from one side, we are triggered to attach ourselves to our ideas; from other, many of our initial ideas are just loose interpretations or hints of intuition and they don’t need to fit to the reality. For me, it sounds as a recipe for trouble.
- What might an assumption look like?
- People need my solutions
- There is a market big enough to support my business
- My solution is a game changer / will change how people do something
- Customers will pay for my new product
What is the problem with these statements? They are pure beliefs, they are axiomatic, unmeasurable, vague, optimistic, and untestable.
What needs be done then? There is a need to build a business hypothesis to be able to move forward.
Business hypothesis
Business hypothesis – something which needs to be true for your idea to work partially or fully, but hasn’t been validated yet.[2]
The big assumptions need to be split into smaller pieces and transformed into business hypotheses
How to build a strong hypothesis. You need to ensure your hypothesis:
- Is testable – it needs to be shown as true (then it’s called validated) or false (then it’s called invalidated) based on evidence.
- Is precise – it needs to be understandable and clear in what success look like.
- Is discrete – it is discrete when only describing the distinct, testable and precise thing you want to investigate
Let’s try to build a few good hypotheses. Start with a sentence: We believe that, :
- We believe that the majority of companies in the UK, which have an annual turnover of between £2 and £ 3 millions, will spend £20 thousand for search engine optimalisation services.
- We believe that, girls between 14-18 years, on average spend 10 hours per week using YouTube.
- We believe that we are able to build an advertising campaign, targeted to X group, which gives us valuable traffic (2 people out of 10 will make a purchase).
Only with strong hypotheses, can you design tests and experiments which can help you to verify your initial assumptions. Always start to test the most critical hypothesis first. Uber, a taxi company, had to verify two of the most critical hypotheses:
- Passengers would like to travel in a car with a stranger
- Drivers would like to transport strangers
If these two hypotheses were not true, Uber couldn’t happen.
Every test and experiment will build your understanding of the reality. Each interaction should lead to a continuation, a change direction, or, in the worst case, abandoning the idea. At some point in time, there will be enough evidence to limit uncertainty, mitigate risks and make a decision based on evidence.
A little case study to reveal potential in this approach
You are never too big, or too small to formulate and validate hypotheses. Do it as early as possible.
Bret Waters shares one of his experiences with testing assumptions. He taught entrepreneurial students at Stanford, where they worked on the „Uber for fresh-baked cookies” idea. In the beginning, students were sure that the prime target market was single guys with the munchies. Before building anything, they wanted to test it. They placed two different Facebook ads: one offering a new service described as cookies delivered to you, the other was described as cookies as a gift to friends and family. What happened next? Bret describe it this way: “The two ads were displayed more than 300,000 times on Facebook, and guess what? The cookies-as-gifts concept got more than twice the number of clicks. When we looked closer at the demographics of those who clicked on our ads, we were shocked to find that most of them were women over 50. That’s a huge insight in to the product/market fit. And the cost of that insight: $192 – $24 in stock photographs and $168 in Facebook ads. A generation ago, reaching a similar conclusion, we would have spent $100,000 on the services of an expensive market research firm” [3].
You are never too big, or too small to formulate and validate hypotheses. Do it as early as possible.
Citation:
[1] Oxford Dictionary
[2] The definition is from “Value Proposition Design” written by Alexander Osterwalder, Yves Pigneur, Greg Bernarda, Alan Smith. The approach to business hypothesising which I described was developed by Strategyzer.
[3] “How To Test The Assumption That People Actually Want Your Product”, Bret Waters, Forbes.
