Start at the End

In today's fast-paced world of product development and innovation, creating something truly impactful goes beyond just making money. The most successful products and services don't just sell well - they change the world by transforming human behavior. Think about how the iPhone revolutionized the way we interact with mobile devices and integrated them into our daily lives. This is the power of behavioral modification, and it should be at the forefront of our minds when designing new products and services.

"Start at the End" by Matt Wallaert offers a systematic, scientific approach to designing products and services with behavioral change in mind. Instead of focusing solely on sales, Wallaert encourages us to take a step back and ask ourselves: What behavior are we trying to promote? What kind of reality are we trying to create? By starting with the end goal in mind and working backward, we can create products and services that truly make a difference.

This book introduces the Intervention Design Process (IDP), a step-by-step method for product and service design that draws on behavioral science. Through this process, you'll learn how to:

1. Summarize your vision of a new reality in a single, powerful statement
2. Create a map of the influences on your potential customers' behavior
3. Use that map to modify those influences and transform the world

Let's dive into the key ideas and steps of the Intervention Design Process to help you create products and services that not only sell but also change behavior and make a lasting impact.

Step 1: Identify and Validate a Potential Insight

The first step in the Intervention Design Process is to identify and validate a potential insight. An insight is a perception of a gap between the world as it is (the real world) and the world as you want it to be (the ideal world). It's important to note that at this stage, your insight is just a hunch or suspicion - it hasn't been confirmed yet.

Let's look at an example to illustrate this concept. When the author was working with Microsoft to develop the Bing search engine, he and his team had a potential insight: children weren't using search engines at school as much as one might expect. On the surface, it seemed like children, schools, and search engines should be a perfect match. Kids are naturally curious, schools are meant to foster that curiosity, and search engines can help answer almost any question. In an ideal world (at least from Bing's perspective), children would be conducting numerous online searches per day at school.

However, the team suspected there was a gap between this ideal world and reality. Something was preventing children from using search engines as frequently as they could be. This hunch was their potential insight.

It's crucial to remember that at this point, there was no empirical evidence to support this notion. It was just a suspicion. That's why it's called a potential insight - it hasn't been confirmed as an actual insight yet.

The danger of acting on unconfirmed insights is that you could waste time, money, and energy trying to solve a problem that doesn't actually exist. That's why the next step is so important: validation.

To validate your insight, you need to seek out quantitative or qualitative evidence. In the case of the Bing team, this meant:

1. Collecting data about children's internet usage at school (quantitative validation)
2. Visiting schools and observing kids' computer usage in person (qualitative validation)

Through this process, the team confirmed their hunch: 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, validating their insight.

This step is crucial because it ensures you're addressing a real problem or opportunity, not just an imagined one. It also provides a solid foundation of evidence that you can draw upon in later stages of the process.

When you're working on your own product or service, take the time to thoroughly validate your insights. Don't rush to solutions based on assumptions. Gather data, conduct observations, and make sure you're addressing a real gap between the current reality and your ideal world.

Step 2: Draft a Behavioral Statement

Once you've validated your insight, the next step in the Intervention Design Process is to draft a behavioral statement. This statement is a formal description of the ideal world you want to create. It's a crucial step because it clearly defines your goal and provides a framework for all your future efforts.

A well-crafted behavioral statement consists of five key components:

1. The behavior you're trying to promote
2. The population whose behavior you want to change
3. The motivation behind the behavior you're encouraging
4. The preconditions or limitations on when and how people can engage in the behavior
5. The data by which you'll measure whether the behavior is taking place

Let's break down each of these components using the example of Uber when it launched its ride-sharing service in 2009:

1. Behavior: The behavior Uber wanted to promote was simple - taking an Uber ride.

2. Population: Uber's target population was quite broad - essentially everyone who needed transportation.

3. Motivation: The motivation behind the behavior was the desire to get from point A to point B.

4. Preconditions: To use Uber at the time of its launch, people needed:

   • A smartphone with a mobile internet connection
   • An electronic form of payment
   • To live in San Francisco (as the company initially limited its rollout to this city)

5. Measurement: Uber would measure success by the number of rides people took with their service.

Now, let's combine these components into a single, powerful sentence:

"When people want to get from Point A to Point B, and they have a smartphone with connectivity and an electronic form of payment and live in San Francisco, they will take an Uber (as measured by rides)."

This behavioral statement encapsulates Uber's vision for its ideal world. It clearly defines who they're targeting, what behavior they want to encourage, under what conditions, and how they'll measure success.

When crafting your own behavioral statement, consider these tips:

1. Be specific: The more precise you are, the easier it will be to design effective interventions later.

2. Be realistic: Remember to include relevant preconditions. Your product or service won't be usable or desirable for everyone in every situation.

3. Focus on the behavior: Your statement should center on the action you want people to take, not just the features of your product or service.

4. Include measurement: Define how you'll know if you're successful. This will guide your data collection and analysis later on.

5. Keep it concise: Try to capture all the essential elements in a single sentence. This forces you to focus on the most important aspects of your goal.

Your behavioral statement will serve as a north star throughout the rest of the Intervention Design Process. It will guide your research, help you identify relevant pressures, and inform the design of your interventions. Take the time to craft it carefully - it's the foundation upon which you'll build your efforts to change behavior and create your ideal world.

Step 3: Map Out the Pressures Influencing Behavior

With your behavioral statement in hand, you're now ready to dive deeper into understanding why people are or aren't engaging in your target behavior. This is where pressure mapping comes in - a crucial step in the Intervention Design Process that helps you identify and visualize the forces influencing your target population's behavior.

The basic premise of pressure mapping is that there are two types of pressures at play:

1. Inhibiting pressures: Factors that hold people back from engaging in the desired behavior
2. Promoting pressures: Factors that encourage people to engage in the desired behavior

Your task is to identify these pressures and map them out. Let's use the example of M&Ms to illustrate this process:

Promoting Pressures for eating M&Ms:

• Taste: M&Ms are delicious, which is a strong motivator for many people.
• Visual appeal: The bright, varied colors of M&Ms make them visually attractive.
• Convenience: M&Ms are easy to eat and portable.
• Brand recognition: The M&M brand is well-known and trusted.

Inhibiting Pressures against eating M&Ms:

• Health concerns: M&Ms are high in sugar and calories, which may deter health-conscious individuals.
• Availability: If M&Ms are not easily accessible, people are less likely to eat them.
• Cost: The price of M&Ms might be a barrier for some people.
• Dietary restrictions: People with certain allergies or dietary requirements may avoid M&Ms.

It's important to note that pressures can be rational or irrational. For example, the colors of M&Ms don't affect their taste or nutritional content, but they still play a significant role in making the product appealing. These irrational pressures can be just as powerful as rational ones in influencing behavior.

Moreover, pressures are often fluid and context-dependent. Take the calorie content of M&Ms, for instance. For someone who's health-conscious, this might be an inhibiting pressure. But for someone who's hungry and needs a quick energy boost, it could actually be a promoting pressure.

This fluidity introduces the concept of counter-rational pressures - those that can go in either direction, contrary to what a rational observer might expect. The playful branding of M&Ms is another example: it might be a promoting pressure at a child's birthday party but an inhibiting pressure at a formal business meeting.

Even seemingly straightforward pressures like cost can be more complex than they appear. While the price of M&Ms might be an inhibiting pressure for many, it could be a promoting pressure for others who associate higher cost with higher quality or status.

Given this complexity, it's crucial not to rely solely on intuition or assumptions when mapping pressures. Instead, base your pressure map on empirical research and validate it with evidence. This might involve:

1. Analyzing existing data on consumer behavior
2. Conducting surveys or interviews with your target population
3. Observing people in real-world situations
4. Running small-scale experiments

Remember, if you did a thorough job with the insight validation phase, you should already have a wealth of data to draw from for your pressure mapping.

When creating your pressure map, consider using a visual representation. You might draw your target behavior in the center of a whiteboard, with arrows pointing up for promoting pressures and down for inhibiting pressures. The length or thickness of the arrows could represent the strength of each pressure.

This visual representation allows you to see at a glance the balance of forces surrounding your target behavior. If the promoting pressures outweigh the inhibiting pressures, people are more likely to engage in the behavior. If the inhibiting pressures are stronger, people are less likely to engage in the behavior.

Understanding this balance is crucial because it sets the stage for the next phase of the Intervention Design Process: designing interventions to shift the balance in favor of your desired behavior.

Step 4: Design Interventions to Change Pressures

Now that you have a clear picture of the pressures influencing your target behavior, it's time to think about how to change them. This is where the rubber meets the road in the Intervention Design Process - you're going to design interventions to alter the balance of pressures and make it more favorable to the reality you want to create.

Remember, you can't directly force people to engage in the behavior you want. Instead, you can indirectly nudge them by manipulating the pressures that surround them. There are two main approaches to this:

1. Decrease the inhibiting pressures
2. Increase the promoting pressures

Your task now is to come up with ideas for possible interventions that accomplish these objectives. Let's continue with our M&M example to illustrate this process:

Decreasing Inhibiting Pressures:

• To address health concerns, you could develop a low-sugar or sugar-free version of M&Ms.
• To improve availability, you could expand distribution to more locations or offer online ordering with quick delivery.
• To tackle cost issues, you could introduce smaller, more affordable packages or run promotions.

Increasing Promoting Pressures:

• To enhance taste appeal, you could introduce new flavors or improve existing ones.
• To boost visual appeal, you could create special edition colors or allow customization.
• To leverage brand recognition, you could launch creative marketing campaigns or partnerships.

When brainstorming interventions, aim for a substantial number of ideas - around 20 is typical at this stage. Don't worry about feasibility or cost at this point; the goal is to generate a wide range of possibilities.

Once you have your list of potential interventions, the next step is to narrow them down to a more manageable number, typically around five. One effective way to do this is by combining interventions that address multiple pressures at once.

For example, let's say you're working on increasing flu shot uptake in the black community, as the author did with Clover Health. You might have identified several inhibiting pressures related to distrust of the medical system. Instead of addressing each of these separately, you could combine them into a single intervention: partnering with trusted community leaders, like church pastors, to promote flu shots and address concerns.

These combinatory solutions are what you're looking for at this stage of the IDP. They allow you to tackle multiple pressures efficiently and can often lead to more impactful interventions.

When selecting your final set of interventions to test, consider the following criteria:

1. Potential impact: Which interventions do you think will have the biggest effect on changing behavior?

2. Feasibility: Can you realistically implement these interventions given your resources and constraints?

3. Alignment with your goals: Do these interventions support your overall mission and values?

4. Novelty: Are you trying something new and innovative, or just rehashing old ideas?

5. Measurability: Can you easily track the effects of these interventions?

Remember, the goal at this stage is not to find the perfect solution, but to identify a set of promising interventions that you can test and refine. Be creative, think outside the box, and don't be afraid to challenge assumptions about what might work.

Also, keep in mind that sometimes the most effective interventions aren't about adding something new, but about removing barriers. For instance, if a major inhibiting pressure is the complexity of using your product, simplifying the user interface could be a powerful intervention.

Lastly, as you design your interventions, always keep your behavioral statement in mind. Every intervention should directly contribute to achieving the behavior change you outlined in that statement. If an intervention doesn't clearly support your goal, it might not be worth pursuing, no matter how interesting or innovative it seems.

Step 5: Conduct an Ethical Check

Before you rush headlong into testing and implementing your interventions, it's crucial to take a step back and conduct an ethical check. This is a vital step that's often overlooked in the product development process, but it's essential for ensuring that your efforts to change behavior are responsible and beneficial.

Remember, what you're setting out to do is influence people's behavior. While this can be used for good - like anti-smoking campaigns - it can also be harmful if not done ethically. The ethical check helps ensure that your interventions are aligned with the best interests of your target population.

There are three main questions to ask during your ethical check:

1. Does the behavior you're promoting match the goals and motivations of your target population?

This question ensures that you're not trying to manipulate people into doing something that goes against their own interests or desires. For example, if you were a tobacco company trying to convince people to smoke, you'd be promoting a behavior that conflicts with most people's fundamental goal of staying healthy.

2. Do the benefits of the behavior outweigh the costs?

Even if a behavior aligns with some of people's goals (like "looking cool" in the case of smoking), you need to consider whether the overall benefits outweigh the costs. In the smoking example, the minor benefit of perceived coolness is far outweighed by the severe health risks.

3. Are you being transparent about your motivations and research methods?

This question helps prevent the manipulation of data or research to make a behavior seem more beneficial than it really is. If you find yourself needing to be sneaky or hide information to make your behavior seem worthwhile, it's a clear sign that you're treading on ethically shaky ground.

It's not just your target behavior that needs an ethical check - your interventions themselves should also be scrutinized. Even if your end goal is laudable, using unethical means to achieve it is not justifiable. Apply the same three questions to each of your proposed interventions:

1. Do the interventions align with people's goals and motivations?
2. Do the benefits of the interventions outweigh any potential negative impacts?
3. Are you being transparent about how these interventions work?

For example, if you were trying to increase flu shot uptake, sending out scare tactics or false information would be unethical interventions, even if they resulted in more people getting vaccinated.

When conducting your ethical check, it's important to be honest and objective. It can be tempting to rationalize or downplay ethical concerns, especially when you're excited about an idea or under pressure to deliver results. However, maintaining ethical integrity is crucial not just for moral reasons, but also for the long-term success and sustainability of your product or service.

If you find that your behavior or interventions don't pass the ethical check, it's time to go back to the drawing board. This might mean redefining your target behavior, rethinking your interventions, or even reconsidering whether this is a project you want to pursue at all.

Remember, ethical behavior change is about empowering people to make informed choices that benefit them, not manipulating them into actions that primarily benefit you or your organization. By conducting a thorough ethical check, you ensure that your efforts to change behavior are not only effective, but also responsible and beneficial to society.

Step 6: Conduct Pilot Studies

Now that your interventions have passed the ethical check, it's time to put them to the test. This is where the rubber really meets the road in the Intervention Design Process. However, it's important to approach this phase strategically to maximize learning while minimizing risk and resource expenditure.

The key here is to start small with pilot studies. A pilot study, or pilot for short, is a small-scale preliminary study conducted to evaluate feasibility, time, cost, adverse events, and effect size (statistical variability) in an attempt to predict an appropriate sample size and improve upon the study design prior to performance of a full-scale research project.

Here's why pilot studies are crucial:

1. Resource Efficiency: Testing on a small scale allows you to gather valuable insights without committing significant resources. If an intervention doesn't work, you haven't wasted as much time, money, or effort as you would have with a full-scale rollout.

2. Multiple Testing: You likely have several potential interventions at this stage. Pilot studies allow you to test all or most of them, rather than having to choose just one or two for a larger implementation.

3. Refinement Opportunity: Pilots give you the chance to identify and iron out any kinks in your interventions before scaling up.

4. Risk Mitigation: If an intervention has unexpected negative effects, the impact is limited due to the small scale of the pilot.

When conducting pilot studies, it's important to embrace what the author calls "operational dirtiness." This means you're not trying to implement the intervention in the most efficient or scalable way possible. Instead, you're focused on testing the core concept of the intervention with as little disruption to your organization as possible.

For example, let's say one of your interventions involves sending personalized recommendations to users. In a fully scaled version, you might use an AI-powered system to generate and send these recommendations automatically. But for the pilot, it might be more practical to have a team member manually create and send the recommendations to a small group of users. This approach is "operationally dirty," but it allows you to test the core concept (personalized recommendations) without investing in complex technology upfront.

When designing your pilot studies, consider the following:

1. Sample Size: Your sample should be large enough to provide meaningful data, but small enough to manage easily. The exact size will depend on your specific situation, but often a few dozen to a few hundred participants is appropriate for a pilot.

2. Duration: Pilots should be long enough to observe the effects of your intervention, but short enough to get results quickly. This could be anywhere from a few days to a few months, depending on the nature of your intervention and target behavior.

3. Measurement: Clearly define how you'll measure the success of your intervention. This should align with the measurement component of your behavioral statement.

4. Control Group: If possible, include a control group that doesn't receive the intervention. This allows you to compare results and more accurately assess the intervention's impact.

5. Feedback Mechanism: Build in ways to gather qualitative feedback from participants. This can provide valuable insights beyond just the quantitative data.

As you run your pilots, collect data diligently. You're looking for indications that your intervention is having the desired effect on behavior. However, remember that due to the small sample size, you can't expect extremely precise or definitive results at this stage.

In scientific terms, you're looking for a p-value of less than 0.20. This means there's at least an 80% chance that your results are not due to random chance. While this level of certainty wouldn't be sufficient for academic research, it's often good enough for practical product development purposes.

After running your pilots, you should have a sense of which interventions show promise. You might be able to make statements like "This intervention seems to increase engagement in our target behavior by about 20%." These results will guide your next steps in the Intervention Design Process.

Step 7: Conduct Formal Tests and Implement

After your pilot studies, you should have a clearer picture of which interventions show the most promise. Now it's time to put these interventions through more rigorous testing before making final implementation decisions.

Formal testing differs from pilot studies in several key ways:

1. Larger Sample Size: You'll work with a bigger group of participants, which allows for more statistically significant results.

2. Longer Duration: Formal tests often run for a longer period, giving you a better understanding of the intervention's long-term effects.

3. More Controlled Conditions: You'll likely use more sophisticated experimental designs, possibly including randomized controlled trials.

4. Operationally Clean: Unlike the "dirty" pilots, formal tests should implement the intervention in a way that's closer to how it would work at full scale.

The goal of these formal tests is to confirm the results you saw in the pilots and to get a more accurate measure of the intervention's effectiveness. You're also testing the feasibility of implementing the intervention on a larger scale.

When conducting formal tests, pay attention to the following:

1. Statistical Significance: Aim for a p-value of less than 0.05, which is generally considered statistically significant. This means there's a 95% chance that your results are not due to random chance.

2. Effect Size: Beyond just statistical significance, look at how large the effect of your intervention is. A statistically significant but tiny effect might not be worth implementing.

3. Operational Feasibility: Evaluate how well you're able to implement the intervention at this larger scale. Are there unexpected challenges or costs?

4. User Feedback: Collect and analyze feedback from participants. This qualitative data can provide valuable insights beyond the numbers.

5. Unintended Consequences: Watch for any unexpected effects of your intervention, both positive and negative.

After conducting your formal tests, it's time for the final step: deciding which interventions to implement fully. This decision should be based on a thorough cost-benefit analysis. Consider factors such as:

• Effectiveness: How much does the intervention change the target behavior?
• Cost: What are the financial and resource costs of implementing the intervention?
• Scalability: How easily can the intervention be rolled out to your entire target population?
• Alignment with Goals: How well does the intervention support your overall objectives?
• Potential Risks: Are there any potential downsides or risks associated with the intervention?

It's possible that multiple interventions prove worthy of implementation. In this case, you might choose to roll them out in phases, or even implement them simultaneously if they're complementary.

Once you've made your decision, it's time to create an implementation plan. This should include:

1. Timeline: When and how will you roll out the intervention(s)?
2. Resources: What people, tools, and budget are needed?
3. Training: Do team members need to be trained on new processes?
4. Communication: How will you inform users or customers about any changes?
5. Monitoring: How will you track the ongoing effectiveness of the intervention?

Remember, implementation isn't the end of the process. Continue to monitor the effects of your intervention and be prepared to make adjustments as needed. The world is constantly changing, and what works today might need tweaking tomorrow.

By following this systematic approach - from identifying insights, through ethical checks and careful testing, to thoughtful implementation - you maximize your chances of creating products and services that not only succeed in the market but also genuinely improve people's lives by changing behavior for the better.

Conclusion

"Start at the End" by Matt Wallaert provides a comprehensive, scientifically-grounded approach to designing products and services that truly make a difference by changing human behavior. The Intervention Design Process (IDP) outlined in the book offers a step-by-step guide for moving from initial insights to implemented solutions.

Let's recap the key steps of the IDP:

1. Identify and Validate a Potential Insight: Begin by recognizing a gap between the current reality and your ideal world, then validate this insight with data.

2. Draft a Behavioral Statement: Clearly define the behavior you want to promote, who you're targeting, and how you'll measure success.

3. Map Out the Pressures: Identify and visualize the promoting and inhibiting pressures influencing your target behavior.

4. Design Interventions: Create potential solutions that could shift the balance of pressures in favor of your desired behavior.

5. Conduct an Ethical Check: Ensure that your target behavior and interventions align with people's best interests and are transparent in their approach.

6. Conduct Pilot Studies: Test your interventions on a small scale to gather initial data on their effectiveness.

7. Conduct Formal Tests and Implement: Run more rigorous tests on promising interventions, then decide which to implement based on a thorough cost-benefit analysis.

By following this process, you can create products and services that don't just sell well, but actually change the world by transforming human behavior. The IDP encourages us to think beyond features and sales figures, focusing instead on the real-world impact we want to make.

One of the most valuable aspects of this approach is its emphasis on evidence-based decision making. From the initial insight validation to the final implementation decision, the IDP pushes us to rely on data rather than assumptions or hunches. This not only leads to more effective solutions but also helps to mitigate risks and avoid wasted resources.

The ethical check step is another crucial element that sets this process apart. In a world where technology and marketing can be used to manipulate behavior in harmful ways, this ethical consideration ensures that our efforts to change behavior are responsible and beneficial to our users.

Moreover, the IDP's focus on understanding and manipulating pressures provides a powerful framework for thinking about behavior change. By mapping out the forces influencing our target behavior, we can design more targeted and effective interventions.

However, it's important to remember that the IDP is not a one-time process. The world is constantly changing, and so are the pressures influencing people's behavior. Successful product and service design requires ongoing monitoring and adjustment. We must be prepared to revisit our assumptions, update our pressure maps, and refine our interventions as we learn more and as circumstances change.

In conclusion, "Start at the End" offers a valuable toolset for anyone looking to create products and services that make a real difference. By starting with the end goal in mind - the behavior we want to change - and working backward through a systematic, evidence-based process, we can design solutions that not only succeed in the market but also contribute positively to society.

Whether you're an entrepreneur launching a startup, a product manager in a large corporation, or a social entrepreneur trying to solve community problems, the Intervention Design Process can help you create more impactful, ethical, and successful solutions. By changing behavior, we can indeed change the world - one product or service at a time.