product development process

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e. to “develop” them). If the goal is to develop solutions that are centered first and foremost on people and their real needs, such strategies cannot be postponed, for example, to the commercialization phase – when the solution has already been developed – but must be implemented in parallel with the development of the solution. A key step in applying the Lean Startup method is to feed a continuous flow of feedback between the startup and its customers during the , to ensure constant learning and to verify every single hypothesis underlying the business idea .


In order to reduce waste, all of this must happen as early as australia telegram data n the product development phase, and sometimes even before the product itself is created. The operational process of the Lean Startup method is therefore effectively represented in the so-called “ lean learning cycle ”, also known as the build-measure-learn cycle . lean-learning-cycle What is “built” in each cycle is a solution, an experience, an experiment that has the purpose of quickly testing, on the market, one aspect of the offer after another ( MVP ). We must avoid thinking about the “finished product” and instead orient ourselves towards the idea of ​​MVP (Minimum Viable Product) , a minimum product that brings value, created in the shortest possible time and that can be tested to return data.


This MVP is developed with short iterations, frequent releases with the aim of always carrying out small experiments, products that verify the validity of the strategy with respect to the idea and the vision. Testing this solution produces concrete data, which the entrepreneur compares with previously established appropriate metrics: this comparison brings out new information (i.e. learning), which only the entrepreneur and his team possess and which fuels the competitive advantage, translated by the startup into exclusive benefits for its market. At this point the cycle begins again, to test a new aspect of the idea or modify the experiment if the results are not satisfactory.