That’s why we’ve developed an evidence-based approach to identifying and prioritising the most suitable behaviour(s) to address a problem: The Impact-Likelihood Matrix (ILM), developed by our very own Sarah Kneebone. By undertaking a rigorous investigation of the literature and audience research, our technique ensures that the behaviour(s) you choose to target for your intervention or policy will have the highest likelihood of driving the change you are seeking.

Prioritizing work into a roadmap can be daunting for UX practitioners. Prioritization methods base these important decisions on objective, relevant criteria instead of subjective opinions. This article outlines 5 methods for prioritizing work into a UX roadmap: Impact–effort matrix Feasibility, desirability, and viability scorecard RICE method MoSCoW analysis Kano model These prioritization methods can be used to prioritize a variety of “items,” ranging from research questions, user segments, and features to ideas, and tasks.

If you write briefs as part of your job, read & bookmark this. So much that’s NB & useful, from truly interrogating the objective, to making sure the different sections line up, to writing your proposition as a headline, to the brief being a dynamic doc open to improvement.

We present a theoretical model to clarify the underlying mechanisms that drive individual decision making and responses to behavioral interventions, such as nudges. The model provides a theoretical framework that comprehensively structures the individual decision-making process applicable to a wide range of choice situations. We also identify the mechanisms behind the effectiveness of behavioral interventions—in particular, nudges—based on this structured decision-making process. Hence, the model can be used to predict under which circumstances, and in which choice situations, a nudge is likely to be effective.

To date, much of the discussion of behaviorally informed approaches has emphasized “nudges,” that is, interventions designed to steer people in a particular direction while preserving their freedom of choice. Yet behavioral science also provides support for a distinct kind of nonfiscal and noncoercive intervention, namely, “boosts.” The objective of boosts is to foster people’s competence to make their own choices—that is, to exercise their own agency. Building on this distinction, we further elaborate on how boosts are conceptually distinct from nudges: The two kinds of interventions differ with respect to (a) their immediate intervention targets, (b) their roots in different research programs, (c) the causal pathways through which they affect behavior, (d) their assumptions about human cognitive architecture, (e) the reversibility of their effects, (f) their programmatic ambitions, and (g) their normative implications.

In their maturity, the fields of experience strategy and behavior change design are moving past the casual flirtations of two complementary knowledge domains into a full fledged partnership: when we marry the design of behavioral interventions and the design of experiences, there’s a special power in combining the myriad frameworks from both domains. This becomes especially effective when the goal is not just to identify pain points in an existing experience journey or illustrate an ideal future one — but to make actionable recommendations that will help clients make the leap from actual to ideal.

Achieving sustained behavior change takes a long time. I mean, hell, we’re still running ads about buckling seat-belts and most states made it a law 35 years ago! Beyond achieving behavior change, seeing the positive impact of said change on species, habitats and ecosystems can take even longer. So how can we balance these longer term goals with the need to show more immediate outcomes?

I propose a four-stage model below that balances an understanding that each part is essential with the need to break it down into units of work that can be spread across internal teams and external vendors when necessary. But be warned: each handoff increases the potential for loss, particularly when there is an incomplete understanding of the adjoining stages. A tightly integrated process managed by people who understand the end-to-end process will always have the greatest likelihood of creating meaningful behavior change; that we can name the parts should not detract from the need for a whole. Behavioral Strategy: the defining of a desired behavioral outcome, with population, motivation, limitations, behavior, and measurement all clearly demarcated. Plain version: figuring out what “works” and “worth doing” mean in behavioral terms by collaborating with stakeholders. Behavioral Insights: the discovery of observations about the pressures that create current behaviors, both quantitative and qualitative. Plain version: figure out why people would want to do the behavior and why they aren’t already by talking to them individually and observing their behavior at scale. Behavioral Design: the design of proposed interventions, based on behavioral insights, that may create the pre-defined behavioral outcome. Plain version: design products, processes, etc. to make the behavior more likely. Behavioral Impact Evaluation: the piloting (often but not always using randomized controlled trials) of behavioral interventions to evaluate to what extent they modify the existing rates of the pre-defined behavioral outcomes. Plain version: figure out whether the products, processes, etc. actually make the behavior more likely. Behavioral Science: combining all four of those processes. Plain version: behavior as an outcome, science as a process.

To solve problems and suggest solutions on behalf of others is to have power. As a result, we behavioral scientists have a heightened responsibility: Being in this privileged position requires recognizing when and where assumptions about “what good looks like” might creep in. When we design interventions—even just determining what options are available, or what the default choice should be—we shape other peoples’ experiences in ways we may not always fully appreciate. And our decisions to address certain problems while leaving others aside implicitly declares what challenges, and audiences, we think are worthy of receiving attention.

One of the most effective approaches I have learned is called SCIPAB, a technique developed by Steve Mandel and now spread by the company he founded, Mandel Communications. I was lucky enough to be trained in SCIPAB by Mandel Communications as part of a more general “presentation skills“ training. I don’t want to steal their thunder (or their business!), but I do want to share some of the insights that I carry with me and use regularly. SCIPAB is an acronym, which stands for the phases of a story: Situation Complication Implication Proposal1 Action Benefit

In order for the software that supports collaboration and automation in production workflows to interoperate, common data models and schemas for data exchange are needed. MovieLabs and its member studios developed it’s Ontology for Media Creation (OMC) to improve communication about workflows between people, organizations, and software. The OMC can serve as the underpinnings for that by providing consistent naming and definitions of terms, as well as ways to express how various concepts and components relate to one another in production workflows.

We argue that the reason so little progress has been made against obesity and type 2 diabetes is because the field has been laboring, quite literally, in the sense intended by philosopher of science Thomas Kuhn, under the wrong paradigm. This energy-in-energy-out conception of weight regulation, we argue, is fatally, tragically flawed: Obesity is not an energy balance disorder, but a hormonal or constitutional disorder, a dysregulation of fat storage and metabolism, a disorder of fuel-partitioning. Because these hormonal responses are dominated by the insulin signaling system, which in turn responds primarily (although not entirely) to the carbohydrate content of the diet, this thinking is now known as the carbohydrate-insulin model. Its implications are simple and profound: People don’t get fat because they eat too much, consuming more calories than they expend, but because the carbohydrates in their diets — both the quantity of carbohydrates and their quality — establish a hormonal milieu that fosters the accumulation of excess fat.

Developed by the Right Question Institute, the Question Formulation Technique, or QFT, is a structured method for generating and improving questions. It distills sophisticated forms of divergent, convergent, and metacognitive thinking into a deceptively simple, accessible, and reproducible technique. The QFT builds the skill of asking questions, an essential — yet often overlooked — lifelong learning skill that allows people to think critically, feel greater power and self-efficacy, and become more confident and ready to participate in civic life.

Companies should experiment with interactive social media content types, include relevant calls to action in posts, and avoid posting too frequently.

The framework comprises 6 key stages. Each building on the insights of the previous and each with its own objectives, tools and resources: 1. What - are the target behaviours? 2. Who - should we focus our resource on? 3. Why - do/don’t those people manifest the target behaviours? 4. How - can we empower people to change? 5. So What? To what extent were our interventions effective? 6. What Now? How do we apply our learnings at scale?

Key Terms in this Chapter Behavioural Policy Cube: The policy cube encapsulates three core features of the ‘libertarian paternalism’ framework; namely if an intervention or policy tool is informed by the standard axiomatic assumptions of rational man theory or by insights from behavioural theories, if it is internality or externality targeting, and if it is regulatory or libertarian in nature (Oliver, 2017b). Nudge: A nudge is any aspect of the choice architecture that alters people's behavior in a predictable way without forbidding any options or significantly changing their economic incentives (Thaler & Sunstein, 2009). Boost: A boost improves the competency of a decision-maker by enriching his or her repertoire of skills and decision tools and/or by restructuring the environment such that existing skills and tools can be more effectively applied (Grüne-Yanoff & Hertwig, 2016). Think: A think is a schooling strategy that involves large-scale deliberations to enable citizens to own the process of behavioural reforms. These often include citizen forums and large-scale behavioural therapies. Nudge Plus: Nudge plus refers to an intervention that has a reflective strategy embedded into the design of the nudge. It can be delivered either as a one-part device in which the classic nudge and the reflective plus are intrinsically combined, or as a two-part device whereby the classic nudge is extrinsically combined with a deliberative instrument that prompts individual reflection on the nudge. (Banerjee & John, 2020).

Design fiction is one of the tools the students learn to prototype the future of business. Designers often use this strategy to help stakeholders envision divergent scenarios for their organization in the context of uncertainty. We asked the students to consider the forces at play in today’s fast-changing society, such as artificial intelligence and decentralized governance models, and write a story about the future. Zooming out of this aspirational story, they mapped out what would have to be true from a technological and business standpoint to bring positive aspects of that future to fruition, while calling attention to factors or decisions that could negatively impact our world years from now. At its core, design fiction is a strategic exercise that connects the dots between vision and execution, transitioning teams from imagining the future to taking action.

The five psychobehavioral segments of Americans Surgo identified from its survey are: 1. The “Enthusiasts” (40% of the U.S. population). Every person in this group said they would get the vaccine as soon as it is made available to them. There are no barriers to vaccination 1 for people in this group—in fact, the key challenge will be ensuring vaccine supply meets their demand before they lose enthusiasm, as we’re seeing now as people struggle to sign up. 2. The “Watchful” (20% of the U.S. population). For this segment, social norms are important: Before they get the shot themselves, people in this segment first need to see that others in their peer group or community are getting vaccinated and having safe, positive experiences. 3. The “Cost-Anxious” (14% of the U.S. population). For this segment, time and costs are the primary barriers to getting the vaccine. Every member of this group reports having delayed seeking care for their health in the past due to the expense. The irony: Only 28% of people in this group lack health insurance, indicating that their concerns about costs override having insurance to cover them. 4. The “System Distrusters” (9% of the U.S. population). This group primarily believes that people of their own race are not treated fairly by the health system. Members of this group are likely to belong to, but are not exclusively, communities of color. There are multiple, complicated barriers for this segment, but most of them are related to trust in and access to a health system that has an inequitable history. 5. The “Conspiracy Believers” (17% of the population). This segment has perceived barriers around COVID-19 vaccination that Surgo believes are simply too hard to shift in the short term. It includes people who don't believe in vaccines in general, but the primary barrier for people in this group is their very specific and deeply-held beliefs around COVID-19. Every person in this group believes in at least one conspiracy theory: ○ 84% believe that COVID-19 is exploited by government to control people ○ 65% believe COVID-19 was caused by a ring of people who secretly manipulate world events ○ 36% believe microchips are implanted with the COVID-19 vaccine The three most persuadable psychobehavioral segments Surgo recommends prioritizing are the “Watchful”, “Cost-Anxious” and “System Distrusters” for maximum benefit. Each segment has specific barriers to overcome:...

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