Posted on March 13, 2016
Steve Blank writes on his blog:
The team confused the goal of the MVP, (seeing if they could find a delighted farmer who would pay for the data) with the process of getting to the goal. They had the right goal but the wrong MVP to test it. Here’s why.
The teams’ hypothesis was that they could deliver actionable data that farmers would pay for. Period. Since the startup defined itself as a data services company, at the end of the day, the farmer couldn’t care less whether the data came from satellites, airplanes, drones, or magic as long as they had timely information.
That meant that all the work about buying a drone, a camera, software and time integrating it all was wasted time and effort – now. They did not need to test any of that yet. (There’s plenty of existence proofs that low cost drones can be equipped to carry cameras.) They had defined the wrong MVP to test first. What they needed to spend their time is first testing is whether farmers cared about the data.
An oldie, but goodie on Steve's blog that remains relevant to all startups and product/service builders.
MVPs are difficult to get right. It's easy to overreach or shoot for the wrong thing. Thankfully you don't have to be perfect, but you certainly don't want to do more work than necessary whenever it's avoidable. After all, more work is harder. It's also riskier. You never know what you're going to learn during the MVP process.
Read the linked story
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