Wellbeing Science and Intervention Design
Most corporate wellbeing programmes fail because they are designed for the average employee who does not exist. They deploy population-level interventions — mindfulness apps, resilience workshops, gratitude journals — based on research showing small-to-medium effects across aggregate samples. But the aggregate conceals the individual. What works for one person does not work for another.
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About This ServiceWellbeing Science and Intervention Design
This service applies precision wellbeing science to intervention design. I begin with a construct audit: clarifying what your organisation actually means by ‘wellbeing,’ identifying the gap between that definition and what your measurement instruments capture, and establishing a validated measurement framework grounded in contemporary theory — PERMA, self-determination theory, and person-environment fit models. From there, I design population segmentation strategies using psycho-behavioural cluster analysis.
The output is an intervention architecture with evidence-mapped logic models, precision targeting frameworks, and an outcome measurement plan that can distinguish signal from noise. Every recommendation is grounded in peer-reviewed evidence and labelled by evidence quality.
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What You Receive
An intervention architecture with evidence-mapped logic models and precision targeting.
Our Approach
A structured, step-by-step methodology tailored to every engagement.
Construct Audit
Clarify what your organisation means by wellbeing and audit current measurement against validated frameworks.
Population Segmentation
Intervention Design
Outcome Framework
Pilot and Handover
| Step | Title | Description |
|---|---|---|
| 01 | Construct Audit | Clarify what your organisation means by wellbeing and audit current measurement against validated frameworks. |
| 02 | Population Segmentation | Identify distinct workforce subgroups using psycho-behavioural cluster analysis to reveal heterogeneous needs. |
| 03 | Intervention Design | Design interventions matched to segments with logic models, active ingredients, and evidence ratings. |
| 04 | Outcome Framework | Build measurement plan with primary and secondary outcomes, control design, and minimum detectable effect sizes. |
| 05 | Pilot and Handover | Design pilot programme with stakeholder communications, facilitator training, and quality assurance protocols. |
Who This Is For
This service is designed for organisations and teams navigating the intersection of AI, people, and accountability.
Chief People Officers
Leaders suspecting their wellbeing programme is not delivering measurable outcomes.
Organisations Investing in Wellbeing
Organisations spending significantly on wellbeing who want evidence-based redesign.
HR Technology Teams
Teams building or procuring AI-driven wellbeing platforms who need scientific validation.
Healthcare and Insurance Organisations
Organisations designing preventive wellbeing programmes with measurable outcomes.
Academic Institutions
Researchers and institutions seeking consultation on wellbeing trial design and methodology.
Frameworks & Standards
Every engagement is anchored to recognised standards and frameworks for accountability and rigour.
Engagement model: Typical engagement runs 4 to 8 weeks. Work can be structured as a focused construct audit, a full intervention design cycle, or ongoing advisory support.
Ready to Get Started?
Let\u2019s discuss how this service can support your needs.