Riskiest Assumption Testing

Thomas Nagels
3 min readJun 28, 2017

--

Recently I posted an update on LinkedIn on how the MVP (Minimum Viable Product) may not be the best tool for selecting a starting point for your innovation. RAT (Riskiest Assumption Test) was given as an alternative. Because this sparked quite some discussion (mostly off-line), I’m going a bit more in depth in this blogpost.

What’s wrong with the MVP?

Anyone who has created MVP’s before will know that early in the innovation process it is extremely hard to find the balance between minimal and viable. Put in too much effort and you increase the risk of to major losses. But if you don’t make it viable, you risk not getting usable feedback. There’s no way to win.

Secondly, calling it a “product” implies that it has commercial value, driving engineers to perfect it and salespeople to want to sell it. But it is not intended to be a finished product, ready for the market. This apparent contradiction typically results in MVP’s which are too large and still brought to the market to soon.

MVP’s are often not minimal, rarely viable and almost never products.
So stop calling them that.

Now I know that Eric Ries in the The Lean Startup says that you need to go to the market with “something” as soon as possible, and then figure it out from the feedback, but I don’t fully agree with that model. Sure, it might work if you are setting up a startup which has not defined its purpose yet, but in a mature business you need some sense of direction and you must stay in control of where you are headed.

Then what is RAT?

The “Riskiest Assumption Test” is the process of finding the riskiest assumptions in your (business) model and validating them. High risk assumptions have two traits: a high probability of being wrong and significant impact when they are.

Risk = Probability x Impact

Step 1: Find the Riskiest Assumptions

Start by building the business model for your innovation on the canvas of your preference. Some examples are:

On this canvas you will have a bunch of items, typically in the form of post-it’s, which need to be true for your innovation to succeed. These can be market related (is my revenue model realistic?) but also technical (can I build the features I need?).

A simple way to find your riskiest assumptions is to score each of these for probability and impact on a scale of 1 to 10. Multiply the scores for each of the items, and rank them from high-to-low. The items with the highest score are your riskiest assumptions.

Step 2: Test!

For each of the Riskiest Assumptions you set up a test. In some cases this can be technical (can I make this work?), in other you could even do market research. Counter to what you do with an MVP, the RAT is ideally set up so that you test the assumptions individually. The point being that you need to know how each of the assumptions influence the success of your product or service.

Step 3: Repeat

Innovation is an iterative process in which what is known or assumed changes the all the time. So, take a good look at your canvas on a regular basis to see what has changed and if your previous tests are still relevant.

Step 4: Build an MVP

Wait. What? An MVP? Yes. While an MVP is not a good tool to guide you in the early phases of the innovation process, it still is vital to go to market as fast as possible. That is where a (slightly redefined) MVP comes in. This Minimal Viable Product (or even MVS for Service) is actually the minimum you think can bring to market based on the assumptions you tested before. So this is a product (or service) and you do know what you minimally need for it to be viable, thanks to the RAT process.

Conclusion

An MVP is not the right tool to find potential weak points in your assumptions. The RAT process gives you lightweight, but systematic, way of doing this. Fortunately, the MVP still has a role in innovation. Once the riskiest assumptions are tested, the MVP will get you to market as fast as possible. It gives you the edge on the competition.

Originally published at thomasnagels.be on June 28, 2017.

--

--