Commonalities among the leading applied behavioral science frameworks

Applied Behavioral Science is a field filled, some might even say overloaded, with frameworks. While this is partly due to the many nuanced attributes of applying Behavioral Science at scale, it is also due to the many competing forces between non-profits, consulting firms, and thought leaders. It is no wonder that one of the most common challenges that I hear from new entrants in the field is where do I get started?

The power of frameworks

Before introducing the aggregate framework, let's start by articulating why the applied behavioral science field significantly benefits from utilizing frameworks. Behavioral Science has many aspects, each filled with great academic literature that one can dive into when necessary. This vastness makes it a valuable field, but it also allows one to over-focus on a specific area without looking at the holistic picture. This is the first benefit that frameworks bring; they establish guardrails on what should be in scope for a single project. Providing a process to follow reduces the likelihood of deviating down an irrelevant path. Having a complete plan to follow also encourages proper resource planning. The best applied Behavioral Science frameworks all have some flow to them.

These guard rails add two critical additional benefits, avoiding necessary steps and ensuring an ideal experimental approach. Providing a series of phases an individual should take ensures that they take the correct steps to create an effective solution. By ensuring that a well-structured experiment has followed the proper preliminary steps, one can also generate evidence that, while not at an academic level, can still be much more helpful than stakeholders making decisions with intuition alone.

Finally, utilizing Frameworks allows the behavioral researcher to communicate what work they will be doing, what phase they are in in the midst of the project, and what to expect at the conclusion. Creating interventions and other behavioral solutions will be a foreign concept for many. Instead of distilling the entire field into a presentation, one can easily communicate what they are planning to do using a simple framework. Checking in with stakeholders at each step of the framework improves the quality of the results, as everyone will have a basic understanding of why the work was completed.

Framework commonalities

With a solid understanding of the benefits of utilizing a framework, you are ready to go out and find a framework that best suits your work. Upon a quick scan of the most popular frameworks created by the leading applied Behavioral Science consulting firms and thinkers, you will recognize that many of them share the same steps. While the creators may have undertaken some copying, many of these were released around the same time, indicating original thought. For me, it is further evidence that the same standard path is generally helpful for most applied behavioral scientists. At the conclusion of this article, I will break down a few of the most popular Frameworks and how they slightly differ in their applicability. For example, Steve Wendell's framework is excellent for people in the tech field, whereas Ideas42 is one of the most straightforward across all domains. (Link to a great example of their work in practice [Page 47]).

I am introducing an aggregate framework to overcome the indecision that may arise from all of the different frameworks. This approach is a summation of the previous frameworks and intends to serve as a starting ground as you determine how exactly you plan to approach intervention development. This aggregation framework begins with understanding the context and explicitly defining the action which an individual should be doing and what they are doing instead. After understanding the environment, the next step is developing an intervention intended to change an individual's environment to yield a different Behavior. With the solution in hand, the third step is testing it with a small group to understand whether or not it creates the intended effect. The final step is tweaking the solution to maximize its impact and then releasing it to a broader audience.

Understanding each phase

Understand current vs. actual behavior and choice environment

Any behavioral change solution, at its core, intends to alter an individual's action. It is best to take this in two phases: First, the solution architect must break the problem being solved into the specific behavior currently being taken and the intended new behavior. Secondly, one must understand the context in which the end-user makes a decision. This research includes the individual's history, the environment where it is taking place, and any cultural factors that may influence a choice.?

By understanding the decision intended to occur and what choice is happening instead, you can think about how to increase the cost of the current, ill-advised decision or increase the benefit of the better choice. Doing this requires a thorough understanding of all factors leading to an individual's perception of each option. One must complete this step with detail as it sets up all of the following phases with the correct data to create an effective solution that addresses the root issues and decreases unintended consequences.

Ideal Behavior vs. Actual & Environment Examples

• Personal - When I wake up I go to my phone for a half hour instead of heading to the gym. My phone is right next to my bed and I use it as an alarm clock thus I am on it in the beginning. I never leave my workout clothes out so it takes mental allergy in the morning to find them and get dressed.
• Business Internal - When employees work from home, they repurpose the commute time towards work rather than taking well-being activities which will lower stress and burnout. The company expects employees to change their behavior without any communications of the sort, there is no utilization of tools to set up artificial barriers around work.
• Business External - After a customer purchases a device, they use it for a short period of time while it is novel but then do not retain on the platform past a month. The company has focused much of the onboarding experience on a big splash to really wow the user of what is possible. It recommends the most popular apps to the user but don't do anything afterwards to ensure that they find something which they want to continue using.

Develop an intervention to change behavior

The next phase takes the context you have gathered and focuses on creating a solution to change behavior. In Behavioral Science jargon, this is the intervention. Any cheats to an individual's environment is an environment if it ranges from something as simple as changing a default option to a multi-step solution such as a new onboarding flow. In developing this solution, you will need to draw on the context you have previously gathered to ensure that you are addressing the root issue and not just changing a surface characteristic.?

Ideally, you will create multiple intervention ideas that attack the behavioral change from different pathways. Brainstorming sessions with your stakeholders and potentially end customers or users is another way to ensure solutions connect to reality. These interventions should also be deployable in your current environment; if some are ideal but require significant investments before being realistic, mark them for a backlog. Keep the ones for this specific project aligned with those you could release within the next month.

Intervention Examples

• Personal - Use a screen limiter on my phone in the mornings and layout my clothing to have them waiting for me in the mornings.
• Business Internal - Utilization of tools that create artificial boundaries, communications and role modeling from leadership, reinforcement when things go well.
• Business external - Onboarding experience that understands a user's interest before the big splashy content, after the primary experience user is immediately brought into an app which is tailored to their preferences. If that works, reinforce, if it doesn't try new ones. Make sure they have an app which the are retaining usage within one month.

Pilot the intervention and measure its effect

With interventions designed, it is time to get them in front of your users to see how effective they are at curbing negative behaviors and taking new positive ones. In an ideal academic world, one could test these in a laboratory, controlling for all factors and determining true causality. All experiments come with trade-offs due to resource and time constraints in the real world.?

There are many ways to approach testing interventions. If your product is full of digital and you have a good data infrastructure, the fastest and easiest way to test an intervention is to deploy it and see changes to the behavioral data of your users. The next best solution is a pseudo-laboratory study if you are without a digital product or still need to establish a data pipeline. You will recruit participants to join your research and split them into two groups. The first group will continue getting the everyday experience, and the second group will get the new venture. You will then compare the outcome to something of the groups similar to an RCT. If this is still too complex, you can do a small sample usability study to understand how users react to mockups of the new intervention (as represented by a new feature.

In all of these methodologies, you want to ensure that you are only deploying the new intervention to a subgroup of users. Taking a pilot approach helps to avoid spreading unintended effects, which you would want to ensure you also measure as part of the study. Finally, if you're methodology allows it, you will wish to also to measure if there are any subgroup effects. This patterns is when one group responds more positively to the intervention than others. While optional, this is the basis of personalization and will be helpful to institute earlier to avoid feature overload down the road.

Iterate until it is successful and scale

With your experimentation setup established, you will want to continue to deploy the interventions, learn from them, iterate the design, and retest. You will only be sure that you have completed it if you have completed it. Instead, you will want to establish some goal, and once that is passed, consider it finished. After testing multiple interventions and identifying the most successful ones, it is time to scale them up! But testing does not end there, and you will want to continue tracking the intervention's progress as it is deployed to the greater population.

• Personal - After finding what works, I can implement it not just in my morning routine but throughout my day with any other tasks that I am struggling to do.
• Business Internal - After testing with one department and finding what works, continue to roll it out as part of a larger change management program measuring the effects of each department.
• Business External - Testing with a subgroup of users, and finding what works, the new experience can be included in a full release and the learning lessons can be transferred to other common problems that users are facing.

Conclusion

Whether you find The aggregate framework helpful in decreasing Choice overload or you want to align to one of the specific Frameworks below, you will better understand why Frameworks are helpful in an applied Behavioral Science context. Utilizing one of these guides will ensure you take an intervention development process that has been shown to work for other leaders in the field.

If you found this discussion helpful for determining how to release your first applied Behavioral Science Project, I have a course that is intended to assist in doing that. Check out the link to sign up for more when it launches!

Frameworks Analyzed:

• OECD BASIC
• Matt Wallaert's Intervention Design Process
• Steven Wendell's DEFINE
• Behavioral Insights Team
• Ideas42 Methodology