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Key Takeaways. You can communicate an early stage idea to key stakeholders using innovation versus financial metrics. Next to validated learning you also need measurable business results to build a successful product. Measuring traction, the rate at which a business model captures monetizable value from its customers, is essential for growing your business. To launch a new feature or kick off a new marketing campaign you should craft experiments for breakthrough learning.
'Failure' should be removed from your vocabulary. In the book, Ash Maurya explores how entrepreneurs can collaborate with stakeholders to establish a business model for a new product or service using Lean Startup principles. It builds on top of his first book Running Lean, showing how to use experiments, measure business progress, and scale your startup.InfoQ readers can download.InfoQ interviewed Ash Maurya about what to measure when your startup is growing, how you can you find out if the business model that you have for your startup is worth pursuing, how to design and run good experiments, and the differences between lean sprints and agile/Scrum sprints. InfoQ also asked him for advice for entrepreneurs who want to scale their startup.InfoQ: Why did you write this book?Ash Maurya: Most new products fail simply because entrepreneurs fail to build what customers want.
The challenge is that you can't simply ask customers what they want, you have to extract it from them.My first book, Running Lean, tackled this problem. It described how to 'get outside the building' and engage customers - to first deeply understand their problems before building solutions.However, once these entrepreneurs got back 'inside the building', they faced a different challenge: how to communicate their findings in the language of their stakeholders. While learning and qualitative validation is key for testing the riskiest assumptions, it doesn't easily extrapolate to financial metrics like profit and ROI. So these entrepreneurs end up spinning different progress stories - one for their core team built on learning and build velocity metrics, and the other for their stakeholders built on 'any metric' that communicates growth.This leads to a dichotomy of progress stories that isn't healthy. Bridging this dichotomy was the goal of Scaling Lean.InfoQ: For whom is this book intended?Maurya: Startups are conversations.
While Running Lean was aimed at the 'entrepreneur to customer' conversation, Scaling Lean is aimed at the 'entrepreneur to stakeholder' conversation. This book is for entrepreneurs and their stakeholders.An entrepreneur is anyone charged with bringing a bold new idea to life under conditions of extreme uncertainty. This could be a startup founder, a corporate innovator, or a product manager.A stakeholder is someone who holds the innovation accountable. This could be a mentor, investor, domain expert, or a leader in the organization.InfoQ: Lean startup tells to use validated learning as the measure of progress when we're starting something new. What should we to measure when we want to grow?Maurya: Validated learning is critical for testing key assumptions and invaluable for keeping our unbridled passion for our products in check. But when this pursuit of learning is carried out at the expense of demonstrable business results, which is often the case, the analogy of 'a startup as an experiment' breaks down. We need to realize that the goals of scientists and entrepreneurs are not the same.The pursuit of raw knowledge is a scientific pursuit.
In that realm, learning is truly the measure of progress. But entrepreneurship is goal driven. Empirical learning is part, but not all, of the final goal: to build a repeatable and scalable business model before running out of resources.
While empirical learning is a key part of that process, unless you can quickly turn that learning into measurable business results (aka traction), you are just accumulating trivia.InfoQ: How can we measure traction, and how can we analyze data?Maurya: Coming from a business modeling mindset, I define traction as the output of a working business model. Specifically, traction is the rate at which a business model captures monetizable value from its customers.It's important to make the distinction between monetizable value and revenue.
Monetizable value is a key measurable customer activity that serves as a leading indicator for future revenue. If customers do enough of the first, the second takes care of itself.InfoQ: How can you find out if the business model that you have for your startup is worth pursuing?Maurya: We have traditionally reached for the mythical Excel spreadsheet where we pound away on the keyboard for hours with a goal of being able to tell a big story just within the realm of believability. The problem with this approach is that all these numbers distract us from our most critical assumptions. It's not the output, but the inputs to the spreadsheet that matter.
There are only a handful of key metrics that drive any business.In Scaling Lean, I share a five minute back-of-the-envelope calculation that uses Fermi estimates to ballpark the potential of any business model. The goal isn't precision, but estimation. The goal isn't building the model top-down, but bottoms-up.Instead of juggling hundreds of numbers, using just three-five inputs such as your pricing model, projected customer lifetime, acquisition rate, and minimum success criteria, you can quickly ballpark your business model’s output. If you can't make this model work on paper, you're going to be hard pressed to make it work in the real world.For an example, check out Chapter 2 in the excerpt.InfoQ: What suggestions do you have for measuring and getting insight into the progress that a startup is making?Maurya: Like taking a journey into uncertain terrain, we need to start with a rough ballpark destination. This is where the goal, or specifically your minimum success criteria, comes into play.
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Your minimum success criteria is the smallest outcome (typically a yearly revenue number) that would deem your project a success X years from now where X.
