With Design Thinking, prototypes, the famous MVP of the Lean Startup, and the notorious ‘get out of the building‘, we’ve learned that innovation ideas have to be confronted with their target users as soon as possible, and that the insights collected help us to refine the idea: test, learn, adjust, and iterate.
With his book The Right It, Alberto Savoia goes one step further, and takes us thoroughly through the process of testing an innovation idea: formulating the assumptions to test, imagining the suited pretotyping tools and activating them cheap, and interpreting the results wisely.
Alberto Savoia joined Google, as first Engineering Director, and Sun Microsystems, when the two companies were just startups. He founded three technology startups of his own. Capitalizing on amazing successes as well as painful market failure, he shifted his focus on developing a set of tools to make sure innovators are building the right it, before they build it right.
I loved reading his book, and how he makes testing so practical, and something you can’t fool. I’ve picked up a few takeaways that I’d like to share with you.
1. The law of market failure, and The Right It
Failure is the most likely outcome. Most new products will fail in the market, even if competently executed. The law of market failure tells us that up to 90% of new ideas will fail soon after launch. For an innovation idea to succeed, all key factors must turn out right, and that’s a lot of rights in a row: right A x right B x right C, etc.= Success. On the other hand, all it takes for something to fail is for a single key factor to go wrong: right A x right B x wrong C, etc.= Failure. If a successful outcome depends on n key factors being right, there are 2n-1 ways to fail, and only 1 way to succeed.
Most projects fail for three reasons: Failure due to Launch (sales, marketing, distribution), Operations (implementation), or Premise (people don’t care) = FLOP.
The Right It is an idea for a new product that, if competently executed will succeed in the market. The Wrong It is an idea for a new product that, even if competently executed, will fail in the market. You only chance for success is to combine competent execution with a product that is The Right It.
2. Thoughtland, and Data
Most of the so-called market research is not done in the actual market, but in fictional environment called Thoughtland. You cannot determine if an idea is The Right It just through thinking. It has to be discovered through experimentation in the real world. The four trolls of Thoughtland are: the lost-in-translation problem (idea not tangible), the prediction problem, the no-skin-in-the-game problem (not a vested interest, no stake in the outcome), and the confirmation-bias problem (seeking evidence confirming your opinion). Instead of dependable, objective, and actionable data, Thoughtland coughs up fur balls of subjective, biased, misguided, and misleading opinions.
Data beats opinions. Data has to be fresh, relevant, trustworthy (with known provenance), and statistical significance. Don’t try to present personal experiences or one-off stories as data! Other’s people data (OPD) are not sufficient, and should not be a substitute for collecting your own data (YODA).
3. The Testing Toolbox: thinking tools, pretotyping, and analysis tools
A. Thinking tools help clarify your idea and identify the data your need to collect
Clarity of thought is paramount. The Market Engagement Hypothesis identifies your key belief or assumption about how the market will engage with your idea. Formulating the precise definition and finding proof of existence of that market demand is the challenge. XYZ Hypothesis expresses refutable, testable, and measurable assumptions: at least X% of Y will Z. X% of Y is a percentage of your target market. Z is what you expect them to do: share their email, accept a phone interview, click on the ad, leave a pre-order deposit, complete pre-sales, or buy the product. Hyperzooming is to zoom until you have a version xyz of the hypothesis, that is actionable and testable right now: take a huge market, and zoom it until you have a small, local, but representative subset of it.
B. Pretotyping are to test your idea in the market, so you can collect YODA efficiently
Once you’ve invested that much time and money to develop something, it becomes really painful to call it quits, even when the actual market response is negative. So you tend to keep going, adding new features and making tweaks, hoping that somehow the situation will turn around. Its’ an expensive and dangerous spiral.
Pretotype describes an artifact that precedes a prototype. Pretotypes are designed primarily to validate, quickly and cheaply, if an idea is wort pursuing and building in the first place. Some pretotyping techniques include The Mechanical Turk, the Pinocchio, the Fake Door, the Facade, the YouTube, the One-Night Stand (inc. pop-up store), the Infiltrator, the Relabel. I encourage you to modify, adapt, and combine these basic techniques to best fit your idea. Every idea deserves to be pretotyped, and there’s (at least) a pretotype for every idea.
A pretotype must produce YODA with skin in the game, it can be implemented quickly, and cheaply.
C. Analysis tools help you interpret the data you collect with objectivity and translate that data into decisions
You need to calibrate data collected and interpret it before you can use it to reach a conclusion on which to base a decision. The skin-in-the game caliper gauges people’s commitment to the new product: before you put a lot of skin in the game on your idea, make sure you can get some skin in the game from your target market. Depending on the type of evidence (opinion, surveys, email address, phone number, time commitment, cash deposit, order placed), the caliper will display different skin-in-the-game points.
The TRI meter is a graphic tool designed to take the results from each pretotyping experiment, put it against your XYZ and xyz hypotheses, and judge the degree to which the YODA supports the likelihood that your idea is The Right Idea.
Test a little before you invest a lot, or even better test a lot before you invest a lot! As a rule of thumb, you need to design and run a bare minimum of three to five experiments, and several more if executing the idea involves a significant risk (e.g., quitting your job or betting the company).
4. Deciding which tools to use, and the Logical Sequence
Think globally, test locally (limit distance to data). Testing now beats testing later (optimize hours to data). Think cheap, cheaper, cheapest (reduce dollars to data). Tweak it and flip it before you quit it (tweaks beats pivot!).
The pretotype planning canvas illustrates the logical sequence of innovating in short cycles: describe the idea, identify Market Engagement Hypothesis (MEH), formulate XYZ hypothesis, then hypozoom into xyz, review pretotyping experiments to validate hypothesis (MEH), prioritize based on distance, time, and dollars to data, run the experiments, analysis with skin-in-the-game caliper and interpret results with TRI meter, tweak it and iterate. If you keep at it, unless you are really unlucky, you will eventually find yourself staring at a TRI meter with idea arrows pointing to Likely or Very Likely.
Last questions to ask yourself: is this idea The Right It for me? Is this idea The Right It for the world? Think beyond business, and go for the Right Right It. Look for an idea that, if competently executed, will not only be successful in the market, but will also be meaningful to you and beneficial to the world. Then do It justice and build it right.