Cognistat partners with public sector agencies and socially-driven organisations to design better surveys, collect quality data, and turn evidence into action.
COGNISTAT
COGNITIVE STATISTICS AND AI
Who We Are
CogniStat is a Melbourne-based data and evaluation consultancy. We specialise in the full data lifecycle, from survey and sampling design through to advanced analytics and program evaluation, helping our clients make decisions grounded in rigorous, reliable evidence.
We work primarily with public sector agencies, government departments, and organisations pursuing measurable social impact. Our clients come to us when the quality of data and methodology matters as much as the findings themselves.
Why CogniStat
We cover the entire data lifecycle, not just the analytics layer.
We design and control fieldwork quality ourselves — no outsourcing.
Rigorous quantitative techniques applied to real-world problems.
Deep familiarity with public and not-for-profit evaluation contexts.
Resources
Get a concise overview of CogniStat's services, team credentials, sector experience, and compliance registrations — ready to share with procurement teams and decision makers.
Download PDFWhat's inside
Company overview and service pillars
Sectors served and key differentiators
Founding team credentials and track record
ABN and UNGM vendor registration details
What We Do
Each engagement draws on one or more of our core capabilities, tailored to your context and objectives.
Rigorous instrument design and statistically sound sampling frameworks that ensure your data represents the population you care about.
End-to-end fieldwork management with in-house quality controls, ensuring data integrity from collection through to delivery.
Advanced statistical techniques, from regression and multivariate analysis to predictive modelling, that surface meaningful insights.
Theory of change, impact measurement, and evaluation frameworks designed to demonstrate outcomes to funders and stakeholders.
Our People
A multidisciplinary leadership team combining statistical rigour, research leadership, and program delivery expertise across three continents.
Statistical Methods Advisor
Co-Founder · Stockholm, Sweden
Edgar is a co-founder of CogniStat. He holds a PhD in Statistics from Stockholm University, and he is currently based in Stockholm, Sweden.
With over 15 years of experience as a professional statistician, his expertise is grounded in the design and analysis of survey data from both an academic and a practitioner's perspective: he is a Senior Lecturer at Stockholm University, teaching and researching sampling and estimation methods at the graduate level. He has also participated as a consultant in several projects for organisations including the World Bank and the International Women's Development Agency.
At CogniStat, Edgar provides methodological oversight on survey design and statistical modelling, bringing academic rigour to the consultancy's work.
PhD in Statistics · Stockholm University
Project Delivery Lead
Co-Founder · Melbourne, Australia
Felipe is a co-founder of CogniStat and brings over 15 years of experience delivering complex, large-scale programs across government, FMCG, manufacturing, and technology sectors. He currently leads global IT transformation programs, managing cross-functional teams across APAC, Europe, and the Americas.
Felipe's background spans procurement digitisation, enterprise system integration, and agile delivery. His experience includes leading a major enterprise procurement transformation program, as well as several business analyst roles spanning consumer goods, consulting, and enterprise technology sectors.
At CogniStat, Felipe leads project delivery and stakeholder engagement, ensuring programs run smoothly from scope through to execution.
Master of Business Information Systems · Monash University
Principal Investigator and Lead Analyst
Melbourne, Australia
Yolanda brings over 15 years of experience directing complex mixed-methods research and translating evidence into policy-relevant recommendations for government and international audiences. She currently leads the Data Methods and Design function at Equality Insights, a program of the International Women's Development Agency.
Her background spans senior research roles at Monash University's Gender, Peace and Security Centre and policy advisory positions within the Colombian government, supporting multidimensional poverty measurement and social policy analysis. Her work has been cited by the United Nations Secretary-General and published in peer-reviewed journals including the International Political Science Review.
At CogniStat, Yolanda leads survey design, quantitative modelling, and analytical quality assurance across the consultancy's research and evaluation work.
Master of Economics · Bachelor of Economics (Honours)
Our Work
A sample of the work we do across sectors. Project details are available on request.
Sampling · Methodology
Designed statistically robust sampling strategies for research programs spanning multiple countries, supporting rigorous, cost-efficient data collection for development and academic partners.
Government · Statistics
Designed and implemented statistical estimation methods for national indices used in government policy and planning, including census-based measurement and quality control frameworks.
Research · Data
Directed construction of a large, multi-country dataset from thousands of source records, establishing quality assurance protocols to produce a novel evidence base for policy and academic use.
Insights and Resources
Original research from our team, alongside articles and papers we find valuable on data methodology, survey practice, and evaluation.
Peer-Reviewed · Survey Methodology
Published in Survey Methodology (Statistics Canada, June 2021), this paper co-authored by CogniStat co-founder Dr Edgar Bueno demonstrates that the commonly-used probability-proportional-to-size sampling strategy is not robust under even moderate model misspecification, and can be outperformed by alternative approaches. A methodologically rigorous case for why sampling design deserves far more scrutiny than it typically receives.
Read the paper →Peer-Reviewed · Public Sector
A compelling public-sector case study from PNAS Nexus examining how the US Census Bureau withheld 2020 ACS estimates to protect sample quality, and how COVID-19 disrupted representativeness across population subgroups. A timely reminder of the high stakes involved in survey integrity for government research programs.
Read the paper →Peer-Reviewed · Program Evaluation
A peer-reviewed reconceptualisation of project evaluation logic, exploring how well-designed frameworks demonstrate transparency and accountability, enable knowledge transfer, and generate reusable lessons across programs. Directly relevant to M&E design in government and development contexts.
Read the paper →Get in Touch
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