The essence of a startup lies in converting ideas into products. As customers interact with products, they provide valuable feedback and insights. The feedback can be qualitative such as what customers like and what they don’t like, and quantitative such as how many people use the product and find it valuable.
As we discovered in part 1, startups build products that are experiments, and the outcome of such experiments is learning to develop a sustainable business. This learning is more important than money, awards, or press mentions, as it can impact and reshape a startup’s next set of ideas, which is why in part 2, we will be exploring this process through the build-measure-learn feedback loop.
The above diagram of the build-measure-learn feedback loop is pivotal to the Lean Startup model. That being said, many individuals have professional training highlighting one feedback loop element. In terms of engineers, it’s learning to build products efficiently as possible. Many entrepreneurs focus their time on producing the best product ideas, the best designed initial product or paying attention to data and metrics. However, Eric Ries stated that none of these activities is essential; instead, what’s important is to minimize the total time with the help of the feedback loop. This is vital to steer a startup.
When applying the scientific method to a startup, you must discover which hypothesis to test. Eric Ries calls them the leap of faith assumptions, and the two most important assumptions are the value hypothesis and the growth hypothesis. These lead to tuning variables that control the engine of growth of a startup. Each startup iteration attempts to ignite the engine to see if it will run. Once it runs, the process continues and shifts into higher and higher gears.
Once you’re clear about the leap of faith assumptions, you must first enter the build phase immediately with a minimum viable product (MVP). The MVP lacks many features that might prove to be necessary eventually. Although an MVP requires minimum effort and the least amount of development time, it requires additional work in specific areas, like having the ability to measure its impact.
In the measure phase, the biggest challenge is deciding if the product development efforts are leading to actual progress. Remember, if you’re building a product that nobody wants, it doesn’t matter if you did it on time and on budget. Therefore, Eric Ries suggested a method called ‘innovation accounting’, a quantitative approach that allows you to see if your engine tuning efforts are successful. Moreover, it will enable you to create learning milestones which are an alternative to the usual business and product milestones.
Finally, there’s the pivot. After completing the feedback loop, you’ll encounter the most challenging question any entrepreneur faces: whether to pivot the original strategy or continue. If one of the hypothesis is wrong, you should make a significant change to a new strategic hypothesis. Although the feedback loop goes in order as build-measure-learn, planning actually works the other way around – you first need to figure out what you must learn, use innovative accounting to discover what you should measure to know if you’re gaining validated learning and then find out what is the product you must build to run the experiment and get the measurement. All the techniques that will be discussed in part 2 are based on minimizing the total time by the feedback loop.
We will now explore the chapters in part 2 in detail to understand the feedback loop.
Any business plan begins with assumptions. It sets out a strategy that takes those assumptions as accurate and continues to show how to achieve the company’s vision. As the assumptions are initially not proven to be accurate and are always wrong, a startup’s early efforts aim to test these assumptions immediately.
What traditional business strategy shines best at is helping managers discover what assumptions are being made in a particular business. The first challenge for an entrepreneur is to build an organization that can test these assumptions effectively. The second challenge is testing assumptions without forgetting the company’s vision.
Many assumptions in a business plan are common. These are firm facts established from previous industry experience or direct deductions. Therefore, by considering that these assumptions are accurate is what makes them ‘leaps of faith’ as the success of the whole company lies on these assumptions. However, as Eric Ries pointed out, most leaps of faith appear as false beliefs. When businesses make such assumptions, they try to make the business look less risky by convincing investors, employees or partners to come on board.
There is nothing wrong with basing strategies on comparing with other companies and industries. In this manner, you’ll be able to discover assumptions that are not leaps of faith. Venture capitalist Randy Komisar’s book ‘Getting to Plan B’ discussed the concept of leaps of faith comprehensively by using a framework of analogs and antilogs to plan strategy. He explained the analogs and antilogs concept by using the iPod as an example.
He stated, “if you were looking for analogs, you would have to look at the Walkman”. Komisar further said that “it solved a critical question that Steve Jobs never had to ask himself: Will people listen to music in a public place using earphones? We think of that as a nonsense question today, but it is fundamental. When Sony asked the question, they did not have the answer. Steve Jobs had [the answer] in the analog [version]”. Thus, Sony’s Walkman was the analog. Jobs then had to accept that although people were ready to download music, they were not prepared to pay for it. However, the leaps of faith assumption were that people would pay for music which was indeed correct.
As we discussed before, there are two types of hypothesis: the value creation hypothesis and the growth hypothesis, which are two leaps of faith. Firstly, to understand a new product or service, you need to discover if it’s value creating or value destroying. Eric Ries refers to value instead of profit as entrepreneurs, including people who start not-for-profit social ventures, individuals in public sector startups and internal change agents who don’t judge their success based on profit. Moreover, many profit-making organizations, in the short term, are value-destroying. For example, organizers of Ponzi schemes and fraudulent or misleading companies.
This is similar for growth. Regarding value, entrepreneurs need to understand the reasons behind a startup’s growth. Many value-destroying types of growth need to be avoided, such as a business that grows based on continuous fund-raising by investors and hefty paid advertising but doesn’t build a value-creating product. Eric Ries addresses such businesses as a ‘success theater’ as they use the appearance of growth to make it seem like they are successful. Thus, innovation accounting helps to differentiate such fake startups from real innovators. Accounting judges new ventures based on the same standards it uses for well-established companies, but these are not trustworthy predictors for a startup’s prospects.
Like traditional accounting, innovation accounting requires a startup to have and maintain a quantitative financial model that can be used to study progress carefully. However, in the initial days of a startup, there is insufficient data to make a detailed guess about what this model might be like. As a result, a startup’s earliest strategic plans are possibly based on good intuition. To convert that intuition into data, entrepreneurs should “get out of the building” and start learning, just like Steve Blank famously quoted.
The importance of building strategic decisions based on a direct understanding of the customers is one of the main principles that Toyota is based on. At Toyota, this is based on the Japanese term ‘genchi gembutsu’, one of the essential phrases in the lean manufacturing vocabulary. In English, it’s translated as “go and see for yourself”, so business decisions are based on deep direct knowledge. Thus, through this concept, to understand any business problem, you need to go see for yourself directly. Therefore, relying on other people’s reports on the problem is unreasonable. You can use your direct observations to test the customers’ assumptions about a product.
Although numbers can be convincing, people can be convincing too. Their behaviour can be measurable and changeable. As Steve Blank taught entrepreneurs for years, the facts you need to collect about customers, markets, suppliers and channels only exist “outside the building”. Startups, therefore, need broad communication with prospects to understand them, so you need to get out of the building and get to know them!
Firstly, you must ensure that your leap of faith questions or assumptions is based on reality and that the customer has a real problem worth solving. For example, when Scott Cook invented Intuit in 1982, he envisioned that one day customers would use their computers to pay bills and track their expenses. He didn’t start with market research but randomly called people and asked a few questions about how they managed their expenses.These questions were asked to answer his leap of faith question – do people find it frustrating to pay bills physically? Indeed it did, and this early validation gave him the green light to start on a solution.
These early conversations did not go about product features of a proposed solution as the average customers at that time didn’t know how to use personal computers to have an opinion on whether they’d want to use them in a new manner. These conversations were with mainstream customers and not early adopters. Yet, the conversations provided valuable insight and that if Intuit could find a solution to this problem of paying bills physically, there could be a mainstream audience for which it could build a huge business.
The goal of early contact with customers is not to gain fixed answers but to clarify that you understand your prospect and the type of problems they have. Based on that, you can make a ‘customer archetype’, a brief document that tries to enlighten the proposed target customer. The customer archetype is an essential guide for product development. It ensures that every product team’s daily vital decisions are consistent with the customer the company is trying to please.
There are 2 significant risks when entrepreneurs conduct market research and communicate with customers. Entrepreneurs of the just go for it philosophy is impatient to start and don’t want to waste time analyzing their strategy. They instead want to start building the product immediately, mainly after a few lousy customer conversations. Unfortunately, since customers don’t know what they want, it’s easy for such entrepreneurs to fool themselves that they are on the right track.
On the other hand, other entrepreneurs face analysis paralysis by continuously changing their plans. In this situation, talking to customers and studying research reports are useless. The problem with most entrepreneurs’ plans is not based on not following sound strategic principles, but the facts they are based on are inaccurate. Unfortunately, most of these mistakes cannot be detected easily as they depend on the communication between products and customers.
Thus, if too much analysis is dangerous but none of the analysis can lead to failure, when should entrepreneurs stop analyzing and start building? The answer is the minimum viable product which will be looking at in the next chapter.
Many entrepreneurs focus their time on producing the best product ideas, the best designed initial product or paying attention to data and metrics. However, as Eric Ries stated, none of these activities is essential; instead, what’s important is to minimize the total time with the help of the feedback loop. This is vital to steer a startup.
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