Advanced Behaviour Change and Government Intervention Design Training Course

Course Introduction

Government policies and public programmes succeed not only because of sound technical design, but also because of how effectively they influence behaviours, decisions, participation, compliance, and service use. This course provides an advanced framework for understanding behavioural drivers and translating behavioural evidence into practical government interventions. Participants will examine how citizens, public employees, businesses, and institutions make decisions and how policy environments can be designed to support better outcomes.

The programme explores behavioural science as a practical discipline for improving public policy and government programmes. Participants will examine cognitive biases, social influences, habits, incentives, motivation, attention, capability, opportunity, choice architecture, identity, trust, and perceived norms. They will learn how these factors interact with institutional and socioeconomic conditions, enabling government practitioners to move beyond assumptions about behaviour and develop interventions grounded in evidence and real-world behavioural contexts.

A central focus is placed on diagnosing behavioural problems before selecting interventions. Participants will learn to distinguish behavioural barriers from structural, administrative, economic, technological, regulatory, informational, and institutional constraints. Through behavioural diagnosis, audience segmentation, journey analysis, user research, and evidence synthesis, they will identify why desired behaviours are not occurring and determine which intervention mechanisms are most appropriate for specific populations and policy environments.

The course develops advanced capabilities in intervention design, experimentation, and evaluation. Participants will explore nudges, boosts, incentives, reminders, defaults, simplification, social norms, communications, commitment mechanisms, environmental changes, service redesign, and regulatory approaches. Particular emphasis is placed on designing interventions that are proportionate, ethical, inclusive, transparent, operationally feasible, and capable of producing measurable behavioural and policy outcomes rather than merely increasing awareness.

Participants will also examine the use of behavioural data, digital technologies, artificial intelligence, personalization, experimentation platforms, and real-time analytics in modern government intervention design. These tools can improve targeting and learning but introduce important questions about privacy, manipulation, algorithmic bias, autonomy, transparency, digital exclusion, and public trust. The programme therefore integrates responsible innovation and ethical safeguards throughout the behavioural intervention lifecycle.

The course concludes with an integrated framework for institutionalizing behaviourally informed policymaking. Participants will learn how to develop behavioural problem statements, intervention theories, design prototypes, experimental plans, implementation strategies, evaluation frameworks, and scaling decisions. The ultimate aim is to strengthen government capacity to design interventions that work in practice, improve citizen and institutional outcomes, use public resources effectively, and continuously learn from evidence.

Duration

10 days

Who Should Attend

• Ministers, permanent secretaries, deputy permanent secretaries, and senior executives responsible for policy, programmes, regulation, and public outcomes.

• Commissioners, directors-general, chief executives, and senior government managers leading behavioural, policy, service, or institutional interventions.

• Policy advisers and policy analysts seeking to incorporate behavioural evidence into policy formulation, implementation, and evaluation.

• Programme and project managers responsible for designing and delivering public interventions intended to change behaviour or improve participation.

• Government economists and social researchers examining incentives, decision-making, behavioural responses, and public-policy outcomes.

• Behavioural insights practitioners and specialists working on public policy, service delivery, regulation, communications, or organizational performance.

• Service designers, user researchers, and citizen-experience professionals developing interventions around real-world citizen needs and behaviours.

• Regulatory professionals designing compliance interventions, enforcement strategies, standards, incentives, and behaviourally informed regulatory approaches.

• Public-health, education, social-protection, environmental, transport, and economic-policy professionals developing behaviour-focused government programmes.

• Monitoring, evaluation, research, and learning specialists responsible for measuring intervention effectiveness, behavioural outcomes, and programme impact.

• Data analysts and digital-government professionals using behavioural data, experimentation platforms, artificial intelligence, and analytics to improve government interventions.

• Communications professionals developing public campaigns, behavioural messaging, social-norm strategies, and targeted government communications.

• Innovation and transformation leaders applying experimentation, prototyping, behavioural research, and evidence-based approaches to public-sector reform.

• Senior officials responsible for ethics, governance, privacy, accountability, or responsible use of data and behavioural technologies.

• Development partners, consultants, researchers, advisers, and technical specialists supporting behaviourally informed government reform and programme implementation.

Course Objectives

• Develop advanced understanding of behavioural science and its application to government policy, regulation, service delivery, programme design, and institutional transformation.

• Diagnose behavioural problems systematically by distinguishing behavioural barriers from structural, economic, administrative, technological, regulatory, and institutional constraints.

• Apply behavioural frameworks to understand motivation, capability, opportunity, habits, cognitive biases, social influences, incentives, norms, trust, and decision environments.

• Conduct behavioural segmentation to identify meaningful differences in motivations, barriers, capabilities, contexts, preferences, and responses among target populations.

• Design behaviourally informed interventions that address identified mechanisms while remaining proportionate, practical, inclusive, ethical, transparent, and operationally feasible.

• Select appropriate intervention mechanisms including simplification, defaults, reminders, incentives, social norms, communications, commitments, environmental changes, and service redesign.

• Develop behavioural theories of change that clearly connect intervention activities and mechanisms with behavioural responses, intermediate outcomes, and desired policy results.

• Apply experimentation, prototyping, randomized trials, quasi-experimental methods, and other evidence-generation approaches to test whether interventions produce meaningful behavioural effects.

• Use behavioural data, digital analytics, artificial intelligence, and personalization responsibly while addressing privacy, fairness, autonomy, transparency, bias, and public-trust considerations.

• Design behavioural communications that account for attention, comprehension, motivation, social context, trust, framing, message fatigue, and differences among target audiences.

• Establish evaluation and learning systems that measure behavioural outcomes, implementation quality, unintended consequences, cost-effectiveness, equity, and long-term sustainability.

• Build institutional capability to embed behavioural science into government decision-making, policy cycles, programme management, regulation, service design, experimentation, and continuous improvement.

Comprehensive Course Outline

Module 1: Foundations of Behavioural Government

• Understanding behavioural science, behavioural public policy, behavioural insights, intervention design, and their growing role in modern government.

• Examining how citizens, businesses, public employees, and institutions make decisions within real-world social, economic, administrative, and policy environments.

• Distinguishing behavioural explanations from purely informational, financial, structural, institutional, technological, and regulatory explanations of policy problems.

• Establishing principles for applying behavioural evidence responsibly, rigorously, proportionately, inclusively, and transparently in government interventions.

Module 2: Behavioural Diagnosis and Problem Definition

• Defining behavioural problems precisely by identifying the desired behaviour, current behaviour, target population, context, frequency, and measurable policy outcome.

• Diagnosing barriers involving capability, opportunity, motivation, attention, habits, social norms, trust, incentives, information, and decision environments.

• Distinguishing symptoms from underlying behavioural mechanisms through research, observation, administrative evidence, qualitative analysis, and behavioural data.

• Developing evidence-based behavioural problem statements that prevent premature selection of interventions without sufficient understanding of causal drivers.

Module 3: Cognitive Biases and Decision-Making

• Examining cognitive biases, heuristics, framing effects, present bias, loss aversion, status quo effects, overconfidence, and limited attention in public decisions.

• Understanding how cognitive constraints influence citizen choices involving public services, compliance, savings, health, education, taxation, and other policy areas.

• Assessing when behavioural biases are context-dependent and how institutional environments can amplify or mitigate their effects.

• Translating behavioural decision-making insights into practical intervention opportunities without oversimplifying complex human behaviour.

Module 4: Motivation, Capability and Opportunity

• Applying behavioural models to assess whether people possess the motivation, capability, opportunity, resources, and environmental conditions required for desired behaviours.

• Identifying practical barriers such as complexity, lack of time, limited knowledge, financial constraints, accessibility problems, competing priorities, and institutional friction.

• Examining intrinsic and extrinsic motivation and how incentives can strengthen or undermine sustainable behavioural change over time.

• Designing interventions that address multiple behavioural determinants rather than relying on single-factor solutions to complex policy challenges.

Module 5: Social Norms, Identity and Collective Behaviour

• Understanding descriptive and injunctive social norms and their influence on individual choices, compliance, participation, consumption, and collective action.

• Examining identity, group membership, social expectations, status, trust, reciprocity, and perceived community behaviour as drivers of government-relevant actions.

• Designing social-norm interventions that avoid unintended effects such as normalizing undesirable behaviour or stigmatizing particular population groups.

• Applying behavioural insights to collective-action problems involving environmental protection, public health, civic participation, safety, and regulatory compliance.

Module 6: Behavioural Research and User Understanding

• Applying interviews, observation, behavioural mapping, journey research, surveys, field studies, experiments, and administrative data to understand real-world behaviour.

• Identifying gaps between stated intentions and observed behaviours and determining how context influences decisions and actions.

• Combining qualitative and quantitative evidence to develop robust behavioural hypotheses and intervention opportunities.

• Designing inclusive behavioural research that captures differences in socioeconomic conditions, accessibility, culture, digital access, language, and service context.

Module 7: Intervention Mechanisms and Choice Architecture

• Designing choice architecture through defaults, simplification, sequencing, salience, reminders, prompts, feedback, commitments, and strategically structured decision environments.

• Assessing when nudges are appropriate and when stronger policy instruments such as regulation, financial measures, service redesign, or structural changes are required.

• Comparing intervention mechanisms according to behavioural mechanism, expected impact, implementation feasibility, cost, ethics, scalability, and potential unintended consequences.

• Developing intervention portfolios that combine complementary behavioural mechanisms rather than relying excessively on a single behavioural technique.

Module 8: Behavioural Communications and Public Engagement

• Designing behaviourally informed communications that improve attention, comprehension, motivation, relevance, credibility, recall, and action among target audiences.

• Applying framing, messenger effects, simplification, personalization, social norms, loss and gain framing, and timely prompts appropriately.

• Testing messages through behavioural experiments and user research to identify differences between intended communication effects and actual behavioural responses.

• Developing communication strategies that preserve transparency, public trust, informed choice, accessibility, and respect for citizens' autonomy.

Module 9: Behavioural Regulation and Compliance

• Applying behavioural insights to regulatory design, inspection, licensing, reporting, taxation, standards, enforcement, and compliance management.

• Understanding why regulated organizations and individuals comply or fail to comply with requirements and how behavioural barriers influence enforcement outcomes.

• Designing proportionate compliance interventions using simplification, reminders, feedback, norms, incentives, inspections, enforcement, and targeted communication.

• Evaluating regulatory interventions for effectiveness, fairness, administrative burden, behavioural response, unintended effects, and impacts across different regulated groups.

Module 10: Behavioural Experimentation and Prototyping

• Designing behavioural prototypes that allow government teams to test intervention concepts rapidly before committing substantial resources to full implementation.

• Developing randomized controlled trials, A/B tests, field experiments, quasi-experimental designs, and other rigorous approaches for estimating behavioural effects.

• Establishing experimentation protocols covering hypotheses, treatment groups, outcome measures, sample requirements, implementation fidelity, ethics, and decision thresholds.

• Using experimental evidence to determine whether interventions should be stopped, redesigned, adapted, expanded, combined, or tested under different conditions.

Module 11: Digital Behaviour and Emerging Technologies

• Examining how digital interfaces, mobile services, algorithms, artificial intelligence, personalization, and automated systems influence citizen decisions and behaviours.

• Designing digital choice environments that reduce friction while avoiding deceptive patterns, excessive persuasion, manipulation, exclusion, or inappropriate use of behavioural data.

• Applying behavioural analytics to identify drop-off points, service abandonment, repeated errors, engagement patterns, and opportunities for digital intervention.

• Establishing responsible technology governance addressing privacy, algorithmic bias, transparency, explainability, security, human oversight, and citizen autonomy.

Module 12: Behaviour Change in Public Services

• Applying behavioural insights to improve service uptake, appointment attendance, application completion, payment behaviour, compliance, communication, and successful service use.

• Redesigning public-service journeys to address behavioural barriers created by complexity, uncertainty, cognitive load, waiting, poor information, and fragmented processes.

• Developing interventions that support citizens throughout critical service journeys using timely prompts, simplification, feedback, reminders, assistance, and proactive support.

• Measuring whether behaviourally informed service changes produce sustained improvements in completion, satisfaction, outcomes, equity, and service efficiency.

Module 13: Ethics, Equity and Responsible Intervention Design

• Examining ethical questions surrounding nudges, incentives, personalization, behavioural targeting, persuasive communications, defaults, and government influence over citizen decisions.

• Applying principles of autonomy, transparency, proportionality, fairness, accountability, informed choice, privacy, and public-interest justification to interventions.

• Assessing whether behavioural interventions create unequal impacts or impose disproportionate burdens on vulnerable, disadvantaged, or digitally excluded populations.

• Establishing ethical review and governance processes that identify manipulation risks, unintended consequences, discrimination, privacy concerns, and loss of public trust.

Module 14: Behavioural Evaluation and Impact Measurement

• Developing behavioural outcome measures that distinguish awareness, intention, action, persistence, compliance, service use, and ultimate policy outcomes.

• Establishing evaluation frameworks that combine behavioural indicators with implementation measures, cost-effectiveness, equity, citizen experience, and broader public outcomes.

• Interpreting experimental and observational evidence carefully while considering statistical uncertainty, external validity, implementation variation, and contextual differences.

• Creating learning systems that ensure evaluation findings influence intervention redesign, resource allocation, policy decisions, scaling, and institutional practice.

Module 15: Scaling, Adaptation and Institutionalization

• Assessing whether successful behavioural interventions can be transferred across regions, services, population groups, institutions, or policy contexts without losing effectiveness.

• Identifying implementation conditions, organizational capabilities, technology requirements, partnerships, workforce skills, and governance arrangements required for sustainable scaling.

• Adapting interventions to local contexts while preserving the behavioural mechanism and maintaining appropriate evaluation and monitoring standards.

• Building behavioural science capabilities through multidisciplinary teams, professional standards, leadership support, knowledge systems, and repeatable intervention processes.

Module 16: Behaviour Change Intervention Capstone

• Developing a complete behavioural diagnosis and intervention strategy for a selected government policy, programme, regulatory, or service-delivery challenge.

• Creating a behavioural theory of change that connects identified barriers, behavioural mechanisms, intervention components, implementation assumptions, and measurable outcomes.

• Designing an intervention prototype, experimentation plan, evaluation framework, ethical safeguards, implementation approach, and evidence-based scaling strategy.

• Presenting an institutional roadmap for integrating behavioural science into government policy cycles, service design, regulation, programme management, experimentation, and continuous learning.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.