TRA has added a layer of thinking to the well-established habit loop – can we think beyond push notifications for cues and think beyond a discount as a reward? We analysed five different habit models and over 60 case studies in order to understand the breadth and depth of cues and rewards. Our framework takes these learnings and provides a thorough checklist for the cue, the behaviour and reward for strengthening habits. When you’re working on strengthening a one-time behaviour into a routine habit, consider the various options for each stage.

On this page we share practical tools and resources that may help humanitarian organisations in their efforts to innovate in partnership with the private sector. Publisert 29 nov 2019 Tools for innovative procurement Step by step guide to innovation friendly procurement This guide developed with TINKR and The National Programme for Supplier Development takes you through the different steps of doing an innovation-friendly procurement process in the humanitarian sector Click her to download. Tools for needs assessment Needs checklist: This checklist is a tool to evaluate if you have done relevant activities to understand as much as possible about the need/problem you are trying to solve before you move on to the market dialogue. Click here to download. Needs matrix: This matrix will help you to describe the needs your project is trying to solve and translate these into criteria you can use in your tender announcement. Click here to download. Template for invitation to market dialogue This is a template that you can use when you are inviting the private sector to a market dialogue: Click here to download. Planning template for market dialogue This template will guide you through the steps of planning and executing a market dialogue. Click here to download. Example of an innovation friendly procurement process from the humanitarian sector (The DIGID project) This is a summary of the innovation firendly procurement process conducted by The Humanitarian Innovation Platform in the DIGID project. Click here to download. Resources from the DIGID project The Humanitarian Innovaiton Platform, consisting of four Norwegian NGOs, have gathered useful resources like call for proposals document, concept note template, etc. from their innovation friendly procurement process. Go to this page to download other resources. Tools for scaling innovations Scaling model, by Tinkr This report presents the key elements of a scaling framework developed in a collaboration between Tinkr and the Norwegian Red Cross. Click here to download the scaling impact model. Tool for scaling, by Tinkr This tool will help you reflect on the scaling potential for your innovation, formulate your scaling ambition, consider which contextual factors and differences will be key to addressing in our project, and what interventions and stakeholders you can engage throughout the project to increase our likeliness of succeeding with scaling. Click here to download PPT version, and here to download PDF version. The scaling scan, by PPP Lab The scaling scan is apractical tool to determine the strengths and weaknesses of your scaling ambition. Click here to download the scaling scan. Tools for business models and IP Tools for sustainable business models Register here to receive three useful tools for sustainable business models, developed by Reodor Innovation Studios. Presentation on intellectual property What are intangible assets and IP/IPR? How can IP be protected and used? Why does IP matter? Presentation by IP expert Felipe Aguilera-Børresen. Download presentation here. Tools for communications Communications Strategy Canvas: The canvas will help you kick start your communicaitons strategy for your innovation project. Click here to download. Article on communications in innovation projects Click here to read. Social media quick tips The article provides some useful tips on how you can use social media to spark engagement about your innovation projects. Click here to read. Reports Background paper for the conference “Innovative Financing – Business models for sustainable humanitarian action“, organized by Innovation Norway and KPMG on 27th of November 2019*. Click here to download. “Leveraging the private sector in the field of protection“. Report by Oxford Research for Innovation Norway*. Click here to download. “Humanitarian organisation's use of pro bono services in innovation projects“ - Report by KPMG for Innovation Norway*. Click here to download.

Mutually-Assured Non-Complacency (MANC) Introducing MANC, a system that helps you achieve your goals. Plainly, MANC is a system that uses the people closest to you to assure that you don’t fall into status quo ruts. It’s Mutually-Assured Non-Complacency. How does it work? First, you define the new desired personal behavior (a.k.a. your goal). Then, you put in a system to achieve it (a.k.a. accountability system). This system gives your friends and family a role in your success. So you think you can MANC? The worksheet gives you the recipe. The videos give you the motivation to start today.

Growing open-sourced database of different commitment devices to help you stick with your intentions and achieve your long-term goals. Read this article for more information on Commitment Devices and how to make the most of this database.

A quick reference guide to creating behavioral maps and behavioral blueprints

Bonus talks Why You Forget Everything And What to Do About It w/ Bec Weeks – https://youtu.be/VoDlOmHbaWE The Sneaky Things That Keep Good Habits From Sticking w/ Jessica Malone – https://youtu.be/oCwMXY7u73A Nicolas Fieulaine from NFÉtudes – https://youtu.be/E-XNZUGvVT0 ––– Timestamps 0:00 Event Intro 6:53 The Science of Habit Change with David Neal 38:10 The Science of Mindfulness with Dr. Clare Purvis 53:03 Creatures of Context with David Perrott 1:21:05 Time Smart: How to Reclaim Your Time and Live a Happier Life with Ashley Whillans 2:05:36 The Invisibility of Habit with Wendy Wood 2:34:19 Digital Behavior Change in Health with Jennifer La Guardia & Aline Holzwarth 2:59:11 Better Decision Making at Work: 5 Core Heuristics (& How to Manage Them) with Scott Young, BVA Nudge Unit 3:22:32 All the small things - How behavioral science can help you unlock success in love and at work with Logan Ury & Liz Fosslien 4:09:53 How to apply behavioral insights to cyber security training with Harriet Rowthron from BestAtDigital 4:22:44 Making Meaning When Life Stinks with Yael Schonbrun 4:54:47 The Power of Identity with Dominic Packer 5:30:40 The Untapped Science of Less with Leidy Klotz 5:55:10 Day Wrap-Up with Samuel Salzer & Peter Judodihardjo

This toolkit has been designed by the Research and Evaluation Unit (RIMU) at Auckland Council to be useful to those wishing to improve public programmes or services, policy development, or team decision-making. It draws on a range of existing resources produced by the Behavioural Insights Team, the OECD and others (see ‘other resources’ on the next page). This toolkit has two components that can be used either separately or together. The first component is a step-by-step process for developing a behavioural intervention. It guides the user through understanding existing behaviours, identifying a desired behaviour, brainstorming ideas for promoting the desired behaviour, and robustly testing the best ideas. The user should follow the steps in the order they are numbered. It is focused on key questions to ask at each step. It is not a complete guide to how to answer these questions, however, and the user may need to rely on other research and evaluation resources to help with each step. The second component of the toolkit is a series of ‘brainstorming’ cards. The cards cover many important behavioural principles to keep in mind when looking to improve programmes, policies, or decision-making. Each card includes a description of the behavioural principle, some examples, and suggestions for how to apply the principle. They can be used on their own or to brainstorm ideas as in the step-by-step process above. To help with navigation, the card set has been organised into a series for better services and a series for better decisionmaking, although there is overlap in the use of the cards. The former is marked with a red dot in the top left corner and the latter with a green dot.

In this chapter we explore three approaches to ensuring that an effective intervention does lead to impact: they are scaling, dissemination, and knowledge translation. Each pathway can increase your impact - i.e., desired behaviour and societal change - but approach this goal from different directions and with emphasis on different activities and outputs. We will introduce you to the three approaches before deep diving into when and how to apply each approach.

Taking your offering to market requires a clear message that resonates with the audience. Your message is meaningful or meaningless: either your message aligns with the dominant cultural narrative and is accepted relatively easy, or your message must alter the cultural narrative before it gains widespread acceptance. Progressive ideas shift the dominant narrative, often at great cost to the messenger. Martin Luther King, like Moses, did not live to enter into the Promised Land. What makes a message convincing? What is a narrative? What makes it dominant? How does a message gain cultural acceptance? How does one shift or disrupt a cultural narrative? We will attempt to answer these questions by drawing on a number of diverse ideas and integrating them into a practical model.

On the whole, however, these behavioral interventions have been somewhat underwhelming, exposing an inherent brittleness that comes from three common “errors of projection” in current behavioral design methodology: projected stability, which insufficiently plans for the fact that interventions often function within inherently unstable systems; projected persistence, which neglects to account for changes in those system conditions over time; and projected value, which assumes that definitions of success are universally shared across contexts. Borrowing from strategic design and futures thinking, a new proposed strategic foresight model—behavioral planning—can help practitioners better address these system-level, anticipatory, and contextual weaknesses by more systematically identifying potential forces that may impact behavioral interventions before they have been implemented. Behavioral planning will help designers more effectively elicit signals indicating the emergence of forces that may deform behavioral interventions in emergent COVID-19 contexts, and promote “roughly right” directional solutions at earlier stages in solution development to better address system shifts.

The SMART acronym (e.g., Specific, Measurable, Achievable, Realistic, Timebound) is a highly prominent strategy for setting physical activity goals. While it is intuitive, and its practical value has been recognised, the scientific underpinnings of the SMART acronym are less clear. Therefore, we aimed to narratively review and critically examine the scientific underpinnings of the SMART acronym and its application in physical activity promotion. Specifically, our review suggests that the SMART acronym: is not based on scientific theory; is not consistent with empirical evidence; does not consider what type of goal is set; is not applied consistently; is lacking detailed guidance; has redundancy in its criteria; is not being used as originally intended; and has a risk of potentially harmful effects. These issues are likely leading to sub-optimal outcomes, confusion, and inconsistency. Recommendations are provided to guide the field towards better practice and, ultimately, more effective goal setting interventions to help individuals become physically active.

Method:Three participatory workshops were held with the independent Welsh residential decarbonisation advisory group(‘the Advisory Group’)to (1)maprelationships betweenactors, behavioursand influences onbehaviourwithin thehome retrofitsystem,(2)provide training in the Behaviour Change Wheel framework(3)use these to developpolicy recommendationsfor interventions. Recommendations were analysed usingthe COM-B (capability, opportunity, motivation) model of behaviourtoassesswhether they addressed these factors. Results:Twobehavioural systems mapswere produced,representing privately rented and owner-occupied housing tenures. The main causal pathways and feedback loops in each map are described.

In 2010, Colombia's defense minister contacted an ad agency to create an idea to demobilize FARC members, the oldest guerrilla army in Latin America. The agency, after spending over a year talking to nearly 100 of its members, learned two main things (1). -First, guerrilla members are ordinary men and women and not only guerrillas, a fact which is often forgotten after 60 years at war. -Secondly, they are more likely to demobilize during Christmas as it is a sensitive and emotional period. Based on these insights, they had a clever idea to put a Christmas tree in strategic walking paths in the middle of the jungle that would light up when someone passed by with a message promoting demobilization. The results? Three hundred thirty-one people who demobilized named this idea as one of the reasons to do so. Over the years, several campaigns from the same agency were quite successful, and overall, they were named in over 800 demobilizations. Causality, of course, cannot be established. Nevertheless, any measurable, non-violent efforts like this one are praised. Next time you think you have a difficult-to-reach customer, maybe think again!

CUBES (to Change behavior, Understand Barriers, Enablers, and Stages of change) is a comprehensive framework for analyzing behavior developed by Surgo Ventures. As described in the video with Peter Smittenaar below, CUBES builds on evidence-based behavioral models that are widely used across sectors and includes drivers that show evidence of changing behavior. It illustrates how adopting a new behavior is a process of stages; at each stage, people are influenced by internal and environmental factors (see Figure 1). The CUBES framework articulates three critical components of behavior change: The path toward a target behavior comprises distinct stages of change, progressing from knowledge to intention, action, repetition, and finally, habit. Perceptual and contextual drivers can act as enablers or barriers that influence each individual, shaping their progression through each stage of change. Influencers in the form of family and friends, community, and society can affect these drivers, either directly or via media channels.

A pressing goal in global development and other sectors is often to understand what drives people’s behaviors, and how to influence them. Yet designing behavior change interventions is often an unsystematic process, hobbled by insufficient understanding of contextual and perceptual behavioral drivers and a narrow focus on limited research methods to assess them. We propose a toolkit (CUBES) of two solutions to help programs arrive at more effective interventions. First, we introduce a novel framework of behavior, which is a practical tool for programs to structure potential drivers and match corresponding interventions. This evidence-based framework was developed through extensive cross-sectoral literature research and refined through application in large-scale global development programs. Second, we propose a set of descriptive, experimental, and simulation approaches that can enhance and expand the methods commonly used in global development. Since not all methods are equally suited to capture the different types of drivers of behavior, we present a decision aid for method selection. We recommend that existing commonly used methods, such as observations and surveys, use CUBES as a scaffold and incorporate validated measures of specific types of drivers in order to comprehensively test all the potential components of a target behavior. We also recommend under-used methods from sectors such as market research, experimental psychology, and decision science, which programs can use to extend their toolkit and test the importance and impact of key enablers and barriers. The CUBES toolkit enables programs across sectors to streamline the process of conceptualizing, designing, and optimizing interventions, and ultimately to change behaviors and achieve targeted outcomes.

The issue is: We try to solve every single box in the problem tree. If people don’t know about something, then we solve it by raising awareness. If people don’t care about something, then we solve it by getting them to care more. If people are doing illegal behaviors because of a lack of enforcement, then we solve it by increasing enforcement. We go through the whole set of problem tree causes in this manner, writing objectives with a one-to-one match per problem. Not only does this result in a long list of objectives, which will quickly overwhelm us, it also traps us into solving behavioral problems using logic-based approaches.

Want to build better habits? By answering these questions you will in less than 10 minutes have created your own personalized habit building plan backed by the best from behavioral science. The finished plan will be sent straight to your email.

Less is more As we look for ways to build memories and cement pre-disposition in consumers’ minds, coherence and clarity remain significant enablers across touchpoints and over time. Using Kantar’s Link database, we investigated the percentage of people who play back each of the key messages in ads that have 1, 2 or 3+ messages. One message in an ad has much more impact than multiple One message in an ad has much more impact than multiple Source: Kantar Link database, US TV ads The findings were a clear plea for simplicity. Too many messages can dilute communication as our brains can only really think about 3-4 things at once. So, in essence, the more messages an ad attempts to communicate, the lower the likelihood any single message will be communicated strongly. And although the results are somewhat varied by type of ad - TV or static - and by market, there was consensus that to successfully communicate a product benefit, we need to keep it simple and avoid too many messages. This is advertising 101 really, but with the rise of digital, it got lost in some places.

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.