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Public Policy Analysis, Review, Advice and Evaluation

Over the past 30 years, we have been trusted advisers and policy analysts to Government, industry and business organisations.

Our work is thorough, informed by our professional knowledge and experience, and timely.  

We are driven by a curiosity to understand problems, issues and opportunities before advocating solutions.  

Our approach combines data-driven and theory-driven research methodologies. We do not have pre-packaged or"cookie-cutter" solutions.


Current Projects

Comparing Theory-Based Research and Data-Driven Research

Research is fundamental in various fields, such as social, natural, and business. Researchers employ different approaches to understand and analyse phenomena based on their objectives, methodologies, and theoretical frameworks. This essay explores and compares theory-based and data-driven research, highlighting their differences and advantages in generating knowledge.

Theory-based research involves formulating a hypothesis or developing a theoretical framework before collecting data. Researchers identify existing theories or develop new ones to guide their investigations and make predictions about the results. These theories provide a solid foundation for research design, methodology, and the interpretation of findings. Typically, theory-based research seeks to answer questions such as why and how something happens.

Data-driven research, sometimes known as empirical research, focuses primarily on collecting and analysing data without a predefined theoretical framework. Researchers gather data and derive insights and patterns to construct theories or hypotheses. This approach is commonly used in exploratory studies or when there is limited theoretical knowledge on a particular subject.

This project explores the current trend towards data-driven research, driven in large part by the massive amount of administrative data and the availability of computing power and sophisticated mathematical techniques. Causal connections are often overlooked, and methods lack a scientific approach to theory and hypothesis building, testing, and validation. 

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