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Thread: MVP - how to deliver Customer Value with agile approach

  1. #1
    GunLoad Trainee BoshkolElsa's Avatar
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    Default MVP - how to deliver Customer Value with agile approach

    MVP - how to deliver Customer Value with agile approach - some thoughts - derived by Eric Ries - LEAN Startup


    In the context of Lean Startups, the concept of the Minimum Viable Product (MVP) is a central tenet of the Lean Startup methodology, which was popularized by Eric Ries.
    The Lean Startup approach advocates for a systematic, scientific method for creating and managing successful startups, emphasizing validated learning, rapid iteration, and a build-measure-learn feedback loop.

    Here's how the MVP fits into the Lean Startup framework:

    Build-Measure-Learn Cycle:

    Build: The first step is to develop a minimal version of the product—this is the MVP. The emphasis is on speed and efficiency in building only the essential features required to test the initial hypotheses about the product.

    Measure: Once the MVP is released, key metrics are collected and analyzed. This could include user engagement, conversion rates, user feedback, and other relevant data. The goal is to gain insights into how users are interacting with the product.

    Learn: Based on the measured data, the startup learns valuable lessons about the product's strengths, weaknesses, and how well it meets user needs. This learning informs the next iteration of the product.

    Validated Learning:
    The MVP is a vehicle for validated learning. It helps entrepreneurs test their assumptions and hypotheses about the target market, customer needs, and the viability of the product in a real-world environment.
    Rapid Iteration:

    The Lean Startup methodology encourages rapid iteration based on feedback. If the MVP reveals that certain features are not resonating with users or if there are unexpected issues, the team can quickly pivot or adjust their strategy without investing significant time and resources.

    Risk Reduction:
    By releasing a minimal version early in the development process, startups can reduce the risk of building a full-fledged product that may not find market acceptance. If the MVP fails to gain traction, the impact on resources is minimized.

    Continuous Improvement:
    The process doesn't stop with the first MVP. The Build-Measure-Learn cycle continues iteratively. Subsequent versions of the product are developed and released, each incorporating improvements based on the insights gained from user feedback and data analysis.

    In summary, in the Lean Startup context, the MVP is a strategic tool that enables startups to test their hypotheses, gather data, and make informed decisions about the future direction of the product.
    It aligns with the core principles of Lean Startup methodology, which seeks to eliminate waste, optimize learning, and build products that customers truly want.


    see more: Minimum viable product (MVP)
    https://en.wikipedia.org/wiki/Minimum_viable_product

    From Wikipedia, the free encyclopedia
    This article is about the product development strategy. For the pilot episode of Silicon Valley, see Minimum Viable Product.
    A minimum viable product (MVP) is a version of a product with just enough features to be usable by early customers who can then provide feedback for future product development.[1][2]

    more explanations. ...:
    What is Minimum Viable Product (MVP)?
    A minimum viable product (MVP) is a concept from Lean Startup that stresses the impact of learning in new product development. Eric Ries an american author has written about the MVP as that version of a new product that allows a team to collect the so called "maximum amount of validated learning about customers" and doing so - doing this with the least effort .. thinkable.

    see eric ris "lean startup" This validated learning has an impact on the form of whether the customers will actually purchase some developed products.

  2. #2
    GunLoad Trainee VitaCoupa's Avatar
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    In MVP software development, this approach focuses efforts on features that have been confirmed by user feedback, rather than assumptions about user preferences. This continual refinement based on actual user responses allows startups to enhance their software more efficiently and tailor it more precisely to market needs.

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