Case Study - Interactive Demographic Forecasts for Investment and Resourcing Decisions
Al Cranswick
July 7, 2025
How an Interactive Demographic Model Transformed Investment and Resourcing Decisions for 200+ Organisations and their Industry Peak Body
Discover how a geo-spatial demographic model delivered $3.2M annual savings for the members of an industry Peak Body, and allowed the Peak Body to re-focus on proactive insights and advocacy.
Executive Summary
The Challenge: Two hundred firms across an industry were each spending $80k periodically on demographic analysis of their region. Furthermore, analysts at the industry's Peak Body were spending most of their time on reactive tasks, responding to analysis requests from their two hundred members.
The Results:
Cost Savings: $3.2 million annual savings costs of pre-feasibility analysis for investment decisions by members.
Frequency Improvement: From every 5 years to every 6 months (10x more frequent insights).
ROI: 15:1 return on consulting investment
Side benefit: Analysts at the industry Peak Body were able to refocus their time on proactive analysis, providing value-adding unexpected insights via newsletters and political advocacy.
The Challenge
Client Profile: An industry Peak Body representing 200+ member organisations across regional markets, each requiring financial and demographic insights for investment planning.
The Problem: Each member organisation independently commissioned economic consultants every 5 years to perform local demographic modelling, costing approximately $80,000 per study. Furthermore, analysts at the industry Peak Body were spending most of their time on reactive tasks, responding to analysis requests from their members. This fragmented approach created inefficiencies across the industry.
Key Issues:
Duplicated Costs: $3.2M annually spent on similar research across 200 members
Inconsistent Methodologies: Varying quality and approaches across different economic consultants.
Outdated Insights: 5-year gaps between updates meant decisions based on outdated demographic data.
Reactive Support: Peak Body staff overwhelmed responding to member requests for assistance with financial projections.
Our Approach
Our experts applied a centralised analytics framework, leveraging proven geospatial modeling techniques. The engagement followed a structured 12-month process:
Phase 1: Requirements Analysis (2 months)
Analysed existing research methodologies across member organisations.
Identified common data requirements and output formats.
Phase 2: Platform Development (4 months)
Built an integrated geospatial model by integrating incomplete data from multiple sources including member organisations, government bodies, ABS and ESRI’s ArcGIS platform.
Developed Power BI dashboards for self-service analytics.
Integrated ABS regional projections and demographic datasets.
Phase 3: Deployment & Training (2 months)
Supported the Peak Body with a phased testing and rollout approach, including Alpha, Beta and Full member roll-out.
Supported the organization to achieve single sign-on for members, with dynamic privacy to allow each member organisation to see their own data, benchmarked against aggregated anonymised data from similar members (similar to the GDPR -compliant privacy-preserving dynamic aggregations used by google analytics).
Results Achieved
Financial Impact
Annual Cost Savings: $3.2 million across member organisations.
Platform Investment: $200k total development and deployment cost.
ROI: 15:1 return on consulting investment.
Other Benefits
Update Frequency: Improved from every 5 years to every 6 months (10x improvement).
Data Consistency: 100% standardised methodology across all member organisations.
Self-Service Adoption: 85% reduction in member queries emailed to the Peak Body.
User feedback: 100% positive after Beta-Test phase. (Though the Peak Body is now looking at a paid subscription model to address requests for additional data and functionality from members who are enthusiastic about the platform).
Key Takeaways
When to Consider This Approach:
Industry associations with members purchasing similar economic research independently
Organisations requiring regular demographic or economic analysis.
Organisations looking to refocus their analysists from reactive responses to proactive insights.
Critical Success Factors:
Quality Assurance (QA): Our extensive internal QA meant that use-acceptance testing by the client and their members was able to focus on user experience, because the delivered model was 100% consistent with input data and assumptions were transparent. From the very first draft our experts provided for client testing, there were no corrections required to modelling algorithms.
Focus on User Experience (UX): Our experts involved UX experts and facilitated a staged rollout to ensure that the published dashboards were as intuitive as a travel booking website (no manuals or individual training required).
Best-Practice Methodology: Anyone can build a Power BI dashboard, but only certified, experienced data modelling professionals can integrate 5+ incomplete, contradictory datasets into a cohesive model that is held out by a peak body as the authoritative single source of truth for their industry. Our experts have successfully applied Kimball data modelling frameworks across many similar analysis projects, consistently delivering +1,000% ROI while improving data quality.
Certified, experienced analysts: Our experts used experts in ESRI ArcGIS, Microsoft Power BI, and Demographic Modelling.
Next Steps
Facing similar challenges with duplicated research costs or reactive analysis? This proven methodology can be adapted to your specific situation.
Schedule a consultation to discuss:
Preliminary assessment of potential cost savings in your context;
Customised geospatial analytics approach for your industry;
Expected timeline and investment requirements.
About the Consultant: As an ex-CFO, Alastair Cranswick understands how frustrating it is when a consultant thinks it is the client’s job to check for accuracy. As an experienced, certified data scientist, he has the skills to build privacy preserving, interactive prediction models. As a curious critter, he is always looking for opportunities to supplement his blind spots with additional expertise such as:
experts in user experience
experts in regional demographic projections; and
experts among client staff members, looking to automate their analysis.
Schedule a consultation with Alastair
