This is a work in progress by the Service Innovation Lab. Pull requests are welcome on GitHub.

Data Analytics for Policy

Welcome to this resource for Policy Practitioners

This website is a result of a Service Innovation Lab project with involvement from policy practitioners from across government exploring how to improve submission analysis processes, especially when dealing with large amounts of submissions.

Data analysis phase

Pages

There are three pages on this website:

Available Tools

This page has a list of tools used to process submissions on policy proposals and describes what they do.

Analysis Tool Matrix

Submissions Analysis and Machine Learning This page explains and supports the understanding of machine learning use for submissions analysis. The page also includes a demonstration of a machine-learning-based software and a recommended approach to using it to give an early indication of key themes, which is particularly useful when processing large quantities of feedback.

Machine Learning & Demo

Feeding back to those who submitted

This page sets out how you can report the findings from engagement or consultation back to those who made a submission. The page shows how you might include your participants throughout your analysis process and finally close the feedback loop with them at the end of your analysis.

Designing the Feedback Loop