Build, measure, learn. They’re the fundamental building blocks of Lean Startup methodology. Critics equate this 3-part cycle with tossing half-baked products to consumers to see if they work – a mistake easily made if you don’t fill in the spaces between Build – Measure – Learn with a little common sense and a lot of communication.
But first, let’s clear up a miscommunication. This isn’t simply about building a product. It's about a lot more than that.
The goal of Build, Measure, Learn isn’t to build a final product, or even a prototype. It’s to learn as much as possible about your target audience, their pain points, price points, and possible solutions through incremental, iterative engineering. The value of approaching product development this way, rather than the waterfall model (in which a set of requirements leads to product design, followed by implementation, verification and maintenance), is that the product develops as a result of customer feedback from the beginning, rather than developing the product before sending it to Alpha and Beta testing.
Lean Startup methodology is a paradigm shift
When the purpose behind product development becomes to learn, instead of just to build, the paradigm shifts completely. Suddenly, building clever solutions is less important than asking the right questions of the right people, and listening closely to the answers. The unit measuring this type of progress isn’t what has been built, but rather what The Lean Startup calls “validated learning.”
This is why communication is the missing link.
If you aren’t communicating, collaborating and discussing what you measure, you won’t learn anything.
What is validated learning?
Validated learning is a rigorous method for demonstrating progress within the Build, Measure, Learn development cycle. When entrepreneurs adopt validated learning to focus on finding the right product to build, they shorten the development process by obviating alpha and beta testing altogether.
Build, Measure, Learn is the process by which you accomplish validated learning.
First, you build a minimum viable product – a product that essentially exists to test your hypothesis about what your customers want, need and will pay for.
Then you deliver that product to your ideal customers (not just to anyone, or your family members, but the people it’s designed for), and measure how they respond.
It's at this measuring stage, where Lean analytics really come into play and where things can go awry. It’s at this stage where communication tends to break down, questions go unanswered, and the most valuable feedback gets lost.
Lean Analytics metrics need to be clearly defined
Part of the issue is that the instruction “measure how they respond” is vague by the standards of any other metric. But it’s also an accurate description of the information you need, which will arrive as both qualitative and quantitative data. Then you have to decide on the implications that data has on your hypothesis, which is where communication, collaboration and discussion are key to successful Lean analytics.
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This is the step many developers miss in the rush to build the product they think the customers really want, but when PMs have the discipline to see what is there, rather than what they’d like to be there, the results are what product manager and author Laura Klein describes as “absolutely magical.” She says using qualitative research and data to make design and product decisions was revelatory.
“Closing that feedback loop made future product decisions so much better.” - Laura Klein
But data can be difficult to track, since it often comes from a number of different places, through multiple tools, which makes how you organize and share data just as important as how you collected it in the first place.
Lean Analytics requires organizing data for easy, accurate analysis and communication
Organizing your qualitative and quantitative data in ways that make them easily understood by everyone involved will help facilitate fruitful discussions about whether you should continue with your original hypothesis, or pivot.
Laure Parsons, Senior Product Manager at Notion presented on “Closing the gap between measure + learn” for Lean Startup Week 2016, making the point that communication, along with data-sharing, are crucial to the learning process.
Lean Startup Communication Checklist: Are you communicating?
- Does your whole team and company know why you are tracking these metrics?
- Do you have agreed-upon actions based on the results?
- Do you have to track down people to get the data?
- Does someone own the metric?
- Laure Parsons, Notion
When it’s time for discussion and collaboration, everyone should be able to find all of the data they need in one, central, shareable location. Too often, data is hoarded in a spreadsheet, or dispersed among many tools, making it difficult for anyone – much less everyone – to see the bigger picture. This is where having a tool like Notion, that integrates with data-gathering tools like Zendesk, PivotalTracker, JIRA, Intercom, Mixpanel, Github and more can prevent communication breakdowns before they begin.
This article is a guest post from Nichole Elizabeth DeMeré, SaaS Consultant & Customer Success Evangelist.