MVP and Early Validation
During the recent 10xelerator startup class, I had the opportunity to work with each of the teams and deliver focus to the MVP goals they were working toward. This was in week 1 of the startup accelerator program – the point where they were shaping the target outcome of their 10-week sprint for growing the business.
My goal for each team consult was to understand the handful of assumptions these founders made when talking about their business, identify the most critical items and distill them down to data points they can validate. The critical data points are easy to spot. They are the variables in your business model spreadsheet that if they go to zero so does your business (and one can only go to zero – thank you, Dave McClure!).
Find the Hypotheses in a Startup Pitch
Each founder shared his or her pitch again. The same basic story they told 10X to get into the accelerator. The same pitch they gave investors to raise funding. How they sold partners on the concept to get them excited about the upcoming product. Those stories are full of the assumptions that will take their product from vision to dominant business. Each assumption (aka hypothesis) is a key step toward the survival of the business. The sooner we prove or disprove those assumptions, the sooner we’ll know if the current vision is viable.
The stories tend to follow a format like this:
- There’s this problem ___________.
- My solution of _________ will solve it.
- We’ll do ___________.
- This ___________ will happen.
- And then ___________ will happen.
- Then the company turns profitable, gets acquired, scales…
The “will happen” blanks interested me the most.
Most of us are pretty good about understanding the premise of a Minimum Viable Product. Getting to the leanest possible proof of concept is still hard, but the concept is not foreign. It’s the fun part of thinking about your technology and how it’s going to solve this massive problem.
The things that “will happen” aren’t just the steps into the unknown; they are often the uncomfortable areas of selling, marketing, distribution and business models. These tests are for the boring aspects of building the business that have an impact. I also don’t believe they can be separated from your business MVP.
All Validation May Not be Product Driven
One company had a very cool back-end mobile technology that they wanted to showcase with an app. Their story was along the lines of “Consumers have this app on their phone, and then they do this…” The “do this…” part didn’t worry me. It was simple and exciting. What they were delivering would easily be experienced – if they got the app on the phone. How were they going to get the app on the phone?
That became the jumping off point of the discussion. While it was incredibly helpful, the product wasn’t inherently viral. App stores are cluttered and crowded. The team was hard-core engineers and not promoters. There was blocker after blocker for that initial assumption. We spent much of our time solving for how users were going to discover this technology so that rest of the story could truly happen.
The Questions to Ask in Lean Product Management
There are fundamental questions for which we’ll need the answers. We have to know the total addressable market, and the serviceable market. We need to show how our product will make a m
eaningful difference. That’s our pitch and passion right?
The product specific questions will follow this kind of path:
- – Is there really a market for the problem you see?
- – Are there indicators that the need is on the rise?
- – Can you describe the users of your solution?
- – Where will your product make money?
- – How will you support those paying customers?
The formula is similar in most cases, while the specific questions will be unique to your startup. If you don’t have your own mentor network to help work through your assumptions, here are some tools that can get you thinking on your own.
- Business Model Canvas
- Lean Startup Machine Validation Board
- Steve Blank’s Customer Development Manifesto
What does your early validation system look like? Share your thoughts in the comments below.