GOD is Truth
This blog isn’t ecumenical in nature. Still, it is about answering big questions and seeking truth and understanding.
At Solve Next we preach “achieve change by formulating and testing hypotheses, drawing conclusions, and doing that again. And again. And again”.
Imagining, building, running, and growing what’s next is a journey of discovery from uncertainty to certainty. A problem-solving adventure that takes you from assumptions about a problem and its potential solutions to knowing what the problem is and which solutions are best.
To complete your journey—that is, to have a known and workable solution, to a known and understood problem—you must be able to answer “Yes” to the Three Killer Questions (in that order):
Killer Question No. 1: “Is it wanted?”
Killer Question No. 2: “Is it doable?”
Killer Question No. 3: “Is it worth it?”
When the answer to any of these is “No” you have three choices:
Run small bets to gain insights about how you might get to “Yes.”
Reformulate your customer pain/solution hypothesis.
Kill it, spin it out, put it on ice, or partner with someone who makes it possible to get to a “Yes” you cannot get to on your own.
And remember, never accept a “Yes” or “No” at face value.
Always ask the Killer Question: “How do we know?”
Think of it as your inner Enthusiastic Skeptic to keep your Boundless Optimist in check.
“Yes, it’s wanted!”
“Really? How do we know?”
“Yes, it’s doable!”
“Really? How do we know?”
“Yes, it’s worth it!”
“Really, how do we know?”
Too often, we get to “Yes” by relying on AAA Data. Now, that might sound awesome—but it’s not. AAA Data is a sure-fire way to fool yourself and others into undeserved confidence.
Anecdotes offer insights and starting points, but they are not statistically significant, so it is unreliable to extrapolate a “Yes” from them.
Assumptions express what we believe, feel, and think, but they are not data, so, like anecdotes, they can provide us with starting points, but they are proof of nothing that yields a “Yes” that cannot be trusted.
Alternatives substitute someone else's data as an answer to your question, but they are not born from your hypothesis, so the “Yes” they produce may be irrelevant. Not to mention, alternatives are frequently out of date, and like fish, data that isn’t fresh stinks and should be avoided.
To answer the question, “How do we know?” in ways that are relevant, trustworthy, and significant, you must turn to GOD.
You must Gather Own Data.
Moving and Making Your Way to GOD
Over the past two decades, we have found our client’s truest path to GOD is found through two of the Think Wrong Practices: Move Fast and Make Stuff. They learn by doing.
Two ways we recommend you find GOD are:
Interview, interview, interview.
Our partners at Mach49 insist that each of their New Venture Teams formulate a hypothesis about who their customer might be, what severe pain they are living with, the cost or consequence of living with it, how the team might solve the problem, and the value of solving it to the customer.
Then the team conducts interviews with hundreds of those potential customers to validate their hypothesis. That is to increase their confidence in the assumptions that have provided a starting place—and to move towards knowing.
When can you honestly say you spoke, in person, to hundreds of people to seek answers to The Three Killer Questions?
Listen and Learn
Listen to this episode of the Hanselminutes Podcast, featuring Cindy Alvarez, author of Lean Customer Development, to learn more about how to validate your product and company ideas through customer development research—before you waste months and millions on a product or service that no one needs or wants.
Download the worksheet from the Think Wrong Matters Most Redux Drill to capture your customer/solution hypothesis. Then have some open-ended conversations with potential customers to validate or invalidate your assumptions.
Prototype, prototype, prototype.
Mach49’s New Venture Teams start with open-ended interviews, listening for what customers are telling them about their pains—and the costs of those—before they ever put a proposed solution in front of them.
Once they start feeling confident enough about their is it wanted assumptions, they start adding simple drawings to those conversations. With the introduction of drawings they are shifting from learning why the customer might want the solution to how might the solution best be delivered to those customers—if it can be delivered at all.
By making—in this case, a picture—the team can learn even more about whether the solution is wanted—and how it might be delivered. They start to learn things from their prospective customers that increase or decrease their confidence in their is it doable assumptions.
Share simple drawings of different scenarios with prospective customers, then observe and learn from how they react to them.
Share higher resolution drawings and models with prospective customers, then observe and learn from how they respond and interact with them.
Bring a Minimal Viable Product to market, then learn—shift from high confidence in your assumptions to certainty (knowledge)—if the solution is wanted, doable, and worth it based on what people do, rather than what they say.
Build to Learn
In this 2013 blog, “An MVP is not a Cheaper Product, It’s about Smart Learning,” Steve Blank explains why it is important to be clear about the goal of your MVP.
Click here to use the Think Wrong Name It Drill to bring your customer/solution hypothesis to life.
Be a Fundamentalist
Move Fast and Make Stuff activities produce data. But creating 1s and 0s is not enough. What matters is that the data—what you are learning—is relevant, trustworthy, and significant. If it isn’t, the answers to the Three Killer Questions run the risk of being irrelevant, untrustworthy, and insignificant.
To avoid that fate, you must not only believe in Gather Own Data, practice Gather Own Data— and convince others to do the same.
Once your team commits to GOD, and practices it consistently, you’ll radically increase your chance of successful outcomes because great decisions are founded in truth not faith.
Learn the techniques from this blog and many more to bring better decisions to your organization, here.