If you are asking this as a very senior person, it’s really hard to get people to be very honest with leaders and managers and so you have to accept that at some level your first step might actually be to…

But let’s go beyond that, suppose you’re asking people who are essentially your peers what happened with this past project, and they’re still giving you these very generic answers…

For the complete answer, watch my video:

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If people say they want something – and they have expressed that intent and they talk about why it’s valuable – but they don’t follow through, it’s because…

For the complete answer, watch my video:

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First of all, don’t take silence as agreement or understanding. It never is.

When people agree, they say: “yes and I have this other idea…”

When people are silent in meetings or even in 1:1 conversations, it usually means…

For the complete answer, watch my video:

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Let’s think about the worst-case scenario which is where you come into this team, you start jumping in, and everyone around you is thinking “this manager is the worst…”

So how do we prevent that from happening?

For the complete answer, watch my video:

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Let me guess, you’re hearing things like:

• I’m not sure that metrics logging is accurate.
• Or you probably didn’t talk to the right customers.
• Or that doesn’t agree with this market research that I found earlier.

So try this…

For the complete answer, watch my video:

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But what about the hypothesis that hasn’t quite been validated? There are many times when this happens:

Some positive signals + You assuming you were right = Something that looks like a validated hypothesis — but isn’t. Let’s call it a “Wishful Thinking” Validation.

A validated hypothesis has the following components:

• Customer confirms that there is a problem.
• Customer doesn’t accept it the problem as “that’s life” or “it’s beyond my control.”
• Customer is already investing resources (time, money, learning curve) into trying to solve this problem.
• Customer is already investing behavioral change into trying to solve this problem.
• Customer does not have any constraints that prevent them from trying this solution.
• Customer pays money / gives a credit card # / signs a letter of intent / commits to learning or training / agrees to a pilot program

In many cases, you may need to invest time, money, and resources before you can get to that last component. But if you’re honest with yourself, you can spot an invalidated hypothesis much sooner.

So what does an invalidated, or “wishful thinking” validation actually look like?

It can be hard to tell the difference between “yes!” and “maybe…” responses. That difference can waste a ton of your money and time.

I’ll list out some examples of “maybe” vs. a “yes!” responses. Let’s use Freda and Jasper, both of whom have already told us that they need to lose weight.

Customer confirms that there is a problem

Freda: “I’ve gained 20 pounds over the last few years, and I feel awful. I have to lie down to zip up my jeans!”

Jasper: “I’ve gained 20 pounds over the last few years, and I feel awful. I had to move my belt out another notch this morning!”

Yep, both of them have a problem.

Customer doesn’t accept it the problem as “that’s life” or “it’s beyond my control.”

Freda: “It’s so hard; I’m so busy with work and kids and volunteering. But I know it’s possible to lose weight, and I just have to make the effort.”

Jasper: “It’s so hard; I’m so busy with work and kids and volunteering. I guess that’s why everyone I know gets heavier after age 35…”

…but Jasper sees this situation as normal. If he doesn’t lose weight, he’ll still be the same as his peer group.

Customer is already investing resources (time, money, learning curve) into trying to solve this problem.

Freda: “I joined my neighborhood gym and signed up for a trainer. It’s expensive, but if I know what I should be doing, I’ll be more likely to keep it up, unlike last time.”

Jasper: “Yeah, I really should lose some weight — that’s why I’m really interested to see what your product is, maybe it can help me!”

Don’t confuse aspirational thinking (“I wish I was the type of person who did X”) with customers ready to take action (“I wish I had tools to help me do X better/faster/more effectively”).

Customer is already investing behavioral change into trying to solve this problem.

Freda: “I started taking the stairs instead of the elevator. I used to drink 3 or 4 sodas a day, now I’m down to 1 and water or tea the rest of the time. I feel like that’s not enough, though.”

Jasper: “When did you say your product will be ready? I can’t wait — I just need something to kickstart me into action and then boom, I’ll really get serious about this.”

Jasper will never be serious about this. Jasper is still riding the elevator one floor up to the vending machines. Jasper will never pay you anything.

Customer does not have any constraints that prevent them from trying this solution.

Freda: “I’m lucky my family is supportive of my goals and, even if they don’t like it much, they won’t revolt at me spending more time exercising and keeping less junk food in the house.”

Jasper: “Well, it’ll depend. My kids are such picky eaters, I don’t think I can convince them to try kale or couscous. And, of course, my wife has us on a pretty tight budget with the current economy…”

Jasper has external stakeholders who will sabotage this sale.

The thing is, both of these people can sound genuinely concerned and eager and enthusiastic. Tone alone could entirely fool you. Emotion is important — certainly, with lack of emotion you’ll have a hard time selling — but behavioral indicators are much stronger.

If you offered a pre-order option, there’s a good chance Freda would give you her credit card number. Jasper would not. Are your prospective customers Fredas or Jaspers? If the latter, something — either your product or your market — needs to pivot.

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My default answer is to push teams towards starting with customer interviews and general observations and research.

Why? Because most teams don’t naturally seek out customer understanding. And once your team starts the activities they prefer (coding, spec’ing, designing), it’s especially hard to build the habit of customer development. Customer development is also a lower-risk activity, which is reassuring to big enterprise orgs.

That said, the point of Lean is to avoid waste and learn as quickly as possible, and sometimes starting with customer development is not the quickest path to learning.

When do we build first and use quantitative data to guide us?

Quantitative data — what you get from telemetry or A/B testing — is the only way to prove that what you built had the desired impact, moved the desired metrics.

But it won’t tell you why a solution worked (or didn’t work). And it doesn’t guide you towards what to try next. “Throw spaghetti against the wall and see what sticks” is not the way to learn quickly and avoid wasting perfectly good pasta.

Starting the loop with “build” — BUILD-MEASURE-LEARN — is great when you have a really strong idea of what to build to solve the problem.

It doesn’t make sense if you’re not really sure what the problem is, or you don’t have a clear idea of how to solve it.

When do we start by learning, and wait a bit for that learning to guide what we build?

Qualitative data — what you get from customer interviewing or ethnography — is the tool to use when you don’t fully understand the customer’s problem, the environment they operate in, or how they explain their processes and limitations.

(note that “our backlog is full of customer requests/feedback” is not the same as understanding customers’ underlying problems / behaviors!)

When you’re still asking “what?” and “why?”, you’ll waste less time by starting the loop with “learn” — LEARN-BUILD-MEASURE.

But that’s just the starting point…

There’s a reason it’s a loop. Regardless of what technique you used to start solving a problem, the way you continue to evolve it to build a better solution is to combine qualitative and quantitative data. Customer development and metrics; research and telemetry; interviewing and testing.

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