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Using Data Driven Insights to Understand Deprivation in England: Live Webinar Series

An improved approach to analysing the Indices of Deprivation using Tableau


By standardising previous Indices of Deprivation data releases to the latest geographic hierarchy (2019) we can compare relative deprivation accurately, for the first time.

What are the Indices of Deprivation?

The Indices of Deprivation (IMD) is a set of metrics comparing relative deprivation across England for 317 Local Authorities and 32,844 neighbourhoods (known as LSOAs).

These metrics are combined into 7 domain categories (Income, Employment, Health, Education, Living Environment, Crime, Barriers to Housing & Services), which collectively form the Index of Multiple Deprivation.

How have we improved the approach to analysing the IMD?

Through a collaborative project between Kirklees Council, Surrey County Council, Concentra Analytics, Tableau, and the wider Public Sector Community, a suite of dashboards has been developed to address this challenge.

We overcome some typical complications when trying to understand how relative deprivation has changed over time. Due to changes in geographic boundaries between IMD data releases, it has been impossible to accurately comment on how relative deprivation has changed over time for the affected areas.

We use a novel approach to overcome this, creating what we feel, is the most sophisticated approach for using this data to provide insights. These dashboards could be used by a wide range of users, from strategic policy makers through to members of the public looking to buy a house.


Join us for this 3-part webinar series in collaboration with Tableau, Kirklees Council and Surrey County Council, to understand our approach.

During these webinars we will cover:

  • Webinar 1: What is the IMD and how do I use the dashboards?
  • Webinar 2: Pushing Tableau Prep to its Limit
  • Webinar 3: Developing the IMD Dashboards

Delivered in Proud Partnership with

Please register your place below to attend all 3 webinars

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