Insights for better decisions
Perspectives, customer experiences and practical guidance on involving people, identifying what matters and turning insight into action.
Verified Case Evidence
See how others have used our approach
Real examples of organisations using Executive Group and the methodology behind Aura to involve people, identify priorities and support decisions and action.
(Some customer stories were delivered using Innoduel, the technology and methodology on which today's Aura products are built.)
Needed a practical way to structure its sustainability work and complete a Double Materiality Assessment without turning the process into a heavy, open-ended consulting exercise.
Wanted to strengthen an inclusive culture and ensure employees across the organisation could genuinely contribute their views, involving a large workforce efficiently.
Around 100 employee representatives turned annual survey findings into a concrete, prioritized action plan in approximately one hour. Predecessor to Aura WorkWell.
Knowledge Themes
Explore our thinking
Decision-making & Prioritisation
Pairwise prioritisation, collective insight, participant psychology, trade-off dynamics, and executive decision-making.
Leadership & Organisations
Workplace wellbeing, executive leadership alignment, customer voice, strategic agility, and overcoming change fatigue.
Sustainability & DMA
Double Materiality, ESRS compliance, stakeholder engagement, IRO scoring, and integrating sustainability into corporate governance.
Business Continuity & Resilience
Crisis preparedness, organizational recovery capabilities, operational vulnerability mitigation, and future resilience.
How pairwise prioritisation works
For leaders and analysts who want to understand what sits behind the numbers.
Why prioritisation instead of traditional rating?
Rating scales (1 to 5) often result in many items being rated as similarly important. When respondents can mark everything as a top priority without consequence, management receives no actionable clarity. Pairwise choices require forced trade-offs, directly revealing relative priorities.
How does pairwise prioritisation work?
Pairwise choices make people choose what matters more. Across participants and repeated comparisons, these choices reveal collective priorities that traditional rating approaches struggle to distinguish.
Why can the results be trusted?
Our engine uses randomized pairwise presentation and statistical validation to ensure every participant has an equal mathematical opportunity to influence the outcome. A sufficient comparison density guarantees mathematical robustness and isolates true organizational consensus.
Evidence and experience
Ecosystem
Practical resources when you need to go deeper
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