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Zusammenfassung von Start at the End

Name: Start at the End
Rating: 4.3 (145 reviews)
Author: Matt Wallaert

Matt Wallaert

How to Build Products That Create Change

4.3 (145 Bewertungen)

26 Min.

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Product Management Design

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What’s in it for me? Learn a systematic, scientific approach to designing products and services.

When a new product or service is successful, it doesn’t just make a lot of money; it changes the world. That might sound dramatic, but consider the iPhone when it debuted. It didn’t just move a lot of units; it fundamentally changed the way we interact with our mobile devices, integrating them into our everyday lives in many different ways. In other words, it transformed our behavior.

That’s why behavioral modification should be at the forefront of our minds when we approach the task of designing new products and services. Instead of just thinking about how we can sell stuff, we should take a step back and ask ourselves, what’s the behavior we’re trying to promote? Or to put it a little more poetically, what kind of reality are we trying to create?

From there, we can work backward in designing new products and services. That’s what Starting at the End is all about. Drawing on behavioral science, these blinks offer a systematic approach to product and service design.

In these blinks, you’ll learn

how to sum up your vision of a new reality into a single, powerful statement;
how to create a map of the influences on your potential customers’ behavior; and
how to use that map to modify those influences and thereby transform the world.

To begin the Intervention Design Process, you need to identify and validate a potential insight.

The process of assessing how we can modify our potential consumers’ behavior is called the Intervention Design Process, or IDP. It begins with a special type of observation called a potential insight. When you have one of these insights, you’re perceiving a gap between the world as it is (the real world) and the world as you want it to be (the ideal world).

To make this somewhat abstract definition more concrete, let’s dig into an example. Back in 2012, when the author was helping Microsoft develop the search engine Bing, he and his team had a potential insight: it seemed like children weren’t using search engines at school anywhere near as much as one might expect.

At first glance, children, schools and search engines should have been a perfect combination. After all, children are brimming with questions, schools are supposed to foster their curiosity and search engines can help them answer nearly any question they might have. In an ideal world (at least from Bing’s perspective), they would be conducting numerous online searches per day (preferably on Bing, of course). But the team suspected a gap between the real world and the ideal world; something was driving a wedge between the two.

Now, the keyword here is “suspected.” At this point, no one at Microsoft had any empirical evidence to support the notion in question; it was just a hunch. That’s why it was a potential insight; it hadn’t yet been confirmed as an actual insight.

For all anyone at Microsoft knew at the time, their hunch could have been wrong, and the gap they were perceiving could have been a figment of their imagination. In that case, it would have been a waste of time, money and energy for the company to throw resources at solving a problem that didn’t exist. That’s true of any potential insight, so it’s crucial to test your insight.

To do that, you need to seek out quantitative or qualitative validation of your insight. For the author and his team, that meant collecting data about children’s internet usage at school – an example of quantitative validation. It also meant going to schools and watching kids’ computer usage in person – an example of qualitative validation.

It turned out their hunch was correct: on average, each student was conducting less than one search per day. The gap between the ideal world and the real world was proven to exist; their insight was validated.

If the same can be said of your insight, you can now proceed to the next step of the IDP.

The next step of the Intervention Design Process is drafting a behavioral statement.

So far, you’ve identified the gap between the world as it is and the world as you’d like it to be. Your next step is to write up a formal description of the ideal world you want to create.

This is called a behavioral statement, and it can be broken into five components. The first is the behavior you’re trying to promote. Usually, it boils down to purchasing and using your product or service. For example, when Uber launched its ride-sharing service in 2009, the behavior the company wanted to promote was, well, taking an Uber.

Now it’s time to map out the pressures influencing your target population’s behavior.

Thanks to your behavioral statement, you now have a precise description of the ideal world you’re trying to create. The next step is to start figuring out how to make it a reality!

Here, we begin with two basic premises. First, there must be certain factors holding people back from engaging in the behavior in which we want them to engage; these are inhibiting pressures. Second, there must be certain factors encouraging people who are engaging in the behavior; these are promoting pressures.

The pressures that promote and inhibit behavior are fluid and complicated.

If you’re conscious about your health, the high calories and sugar content of a pack of M&Ms are probably going to be a pretty significant inhibiting pressure, dissuading you from eating them. But if you’re feeling hungry or experiencing a blood sugar crash, they could also be a promoting pressure, tempting you to gobble them down.

Here we encounter an example of a counter-rational pressure – a pressure that can go in either direction, contrary to what a rational observer might expect. These counter-rational pressures are context-dependent. For example, M&Ms have a playful, lighthearted branding that features anthropomorphic candy characters. In the context of a kid’s party, that branding is a promoting pressure – but at a romantic dinner, it would probably make them feel pretty out of place; their branding would then become an inhibiting pressure.

A pressure map gives you a full picture of why your target population is behaving the way it’s behaving.

Let’s say you’ve finished mapping out your target behavior’s inhibiting and promoting pressures. On a whiteboard, you may have drawn a picture of the behavior in the middle, surrounded by downward arrows for each of the inhibiting pressures and upward arrows for each of the promoting pressures.

You can now see at a glance the balance of forces surrounding the behavior. The more the promoting pressures outweigh the inhibiting pressures, the more likely people will be to engage in the behavior. Conversely, the more strongly the inhibiting pressures push down against the promoting pressures, the less likely people will be to engage in the behavior.

Think about how to change the pressures that are influencing your target population’s behavior.

At this point in the IDP, you’ve mapped out the inhibiting and promoting pressures that surround your target behavior. As a result, you now know the balance of power between the two sides.

To promote your target behavior, you need to alter that balance of power to make it more favorable to the reality you want to create. You can’t directly force people to engage in the behavior in which you want them to engage – but you can indirectly nudge them in one direction or another by manipulating the pressures that surround them.

Next, you need to conduct an ethical check on the behavior you’re trying to promote.

Now that you’ve come up with some possible interventions to promote your target behavior, you’re probably going to be feeling pretty eager to go out into the field and put your ideas into action.

But hold on – before you move forward, you need to hit the pause button and conduct an ethical check. After all, what you’re setting out to do is to influence people’s behavior. Now, that can be a good thing; just think of anti-smoking campaigns. But it can also be a very bad thing, like the ads that glamorized smoking in the first place.

You also need to conduct an ethical check on the interventions you’re contemplating.

Let’s say you’ve done an honest ethical check and you’ve confirmed that your target behavior matches your target population’s goals and motivations, that the benefits of the behavior outweigh the costs and that you’ve been transparent in making this determination. All’s well and good; now you can move forward with your interventions, right?

Well, not so fast. It’s not just your target behavior that you need to check; it’s also the interventions themselves. Remember the old caveat: the ends do not justify the means. Even if your target behavior is totally laudable, that doesn’t necessarily mean your interventions are ethical. For example, you could try to convince people to get a flu shot by sending them scare letters telling them they will die if they don’t get one, but that would be a pretty unethical intervention.

Now it’s time to conduct some pilot studies of your interventions.

When you reach the final step of the IDP, you enter it with a handful of possible interventions that you think might foster the behavior you want to promote. Now it’s time for the rubber to hit the road and see if they work.

But you don’t want to spin your wheels too fast here. In theory, you could take one of your possible interventions and roll it out right away on a nationwide or even international scale. But what if it doesn’t work? That’s a lot of wasted time, energy and money. Plus, what about the other four possible interventions you might have come up with? You probably don’t have the resources to try out all of them on a large scale. But if you don’t test them all, you’ll never know which one is the most effective.

Finally, you need to conduct more formal tests of your interventions; then you can decide which ones to implement.

Assuming you’ve collected data for one of your pilot studies, you and your team now have some sense of whether or not the intervention you’re looking at is a promising one. Your sample size will have been pretty small, so you can’t be very certain of your results at this stage. But with at least some degree of certainty, you can now make a statement like, “this intervention seems to increase people’s engagement in our target behavior by 20 percent.”

In scientific parlance, the degree to which you’re certain about a statement like this is called your data’s p-value. Counterintuitively, the lower the value, the higher the certainty. If your p-value is 0.05, that means there’s a 5-percent chance your data are wrong and therefore a 95-percent chance they’re right.

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Worum geht es in Start at the End?

Start at the End (2019) provides a highly practical, step-by-step approach to designing products and services that make an impact on the world. Drawing on behavioral science, the process begins with a simple question: How do we want our potential consumers to act? It then works backward to figure out how to make that vision a reality.

Wer Start at the End lesen sollte

Start-up employees looking for a way to shake up their industry’s playing field
Leaders of established companies looking for their next big idea
Entrepreneurs interested in applying behavioral science to their pursuit of business

Über den Autor

Matt Wallaert is a behavioral scientist and entrepreneur. As the chief behavioral scientist at Microsoft and the Clover Health insurance company, he has developed his unique approach to designing products and services through hands-on, real-life experience in multiple fields of business. Start at the End (2019) is his first book.

Kategorien mit Start at the End

Psychology Entrepreneurship Technology & the Future

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