Poverty Index ALPHA

Project details:

Organisation London Borough of Hackney
Department
Collaboration Level Share Ideas
Budget Unknown
Key Contact Soraya Clarke
Phase start 28 October 2019
Phase Estimated end 31 January 2020

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Description

The Hackney Poverty Index

 

Hackney aims to be evidence-led in everything we do, but the lack of insight about poverty and deprivation in the borough is limiting our ability to develop effective strategies, plan services that meet our residents’ needs, and make informed decisions.

 

Earlier in the year, the Data and Insight team, along with colleagues from Public Health and SPED, carried out a 6-week discovery where they developed an MVP of the ‘Hackney Poverty Index’. This was a basket of poverty-focussed indicators using public and locally held data, brought together and visualised in a Qlik dashboard. 

 

In the discovery phase, we learned that there is a real appetite for better data on poverty to support our residents. However, we know that the terms ‘poverty’ and ‘deprivation’ often means different things to different people. They are widely understood to mean a lack of income and material possessions, but broader definitions also include lack of access to living conditions or participation in activities which are customary in society.

 

This project aims to build a shared understanding of poverty in Hackney by making the most of our local data.


Our vision is to use up-to-date local and public data to build a better-shared understanding of poverty in Hackney across our organisation and amongst partners to enable better decision-making and service design.


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Status Updates

13 January 2020

  • Soraya Clarke

    Hackney Poverty Index Project

    Week commencing 6th January 2020

    Sprint 5

     

    The Hackney Poverty Index aims to build a shared understanding of poverty in Hackney by making the most of our local data.

     

    During our last show and tell we shared the 4 themes and indicators that we had identified for the Hackney Poverty Index, these included; Income, Housing, Education & Skills and Health. 

     

    Since then we have been liaising with data experts and conducting desktop research to gather our indicators.

     

    Last week, we reviewed how much data we have been able to obtain so far. Although we are still awaiting information from some service areas we have collected enough data around the income theme to produce an interim output for Income. As a result, this is our sprint goal for the next two weeks as well as following up on obtaining data for the other themes.

     

    We are continuing to keep our ‘minimum viable documentation’ up to date. The most recent update includes the threshold we will use to classify small areas within Hackney. We decided to use the borough average as this way we won’t have to rely on the availability of external datasets to get on with prototyping.

     

    Challenges 

    • Our project is heavily reliant on access to data as a result this may mean that the project may take longer than originally anticipated to conclude, or we may choose to pause the project if we can’t move forward without the missing data. 

     

    This Sprint 

    We look forward to producing our first interim output for our project and using this as a learning opportunity for developing the remaining themes.

23 December 2019

  • Soraya Clarke

    Hackney Poverty Index Project

    Week commencing 25th November 2019

    Sprint 3

     

    The Hackney Poverty Index aims to build a shared understanding of poverty in Hackney by making the most of our local data.

    This week: 

    This week our project highlights included;

    1. Agreeing our evaluation methodology for the Index. Part of the evaluation method includes each theme including publically available/open data and local/web scraping variables (by default min of 2 variables). This is important because we want to be transparent about how we’ll fairly evaluate the model without tweaking it too much in line with our existing biases. Essentially we want to make sure we’re not building something that just says what we thought it should say from the outset.

    2. Deciding on some consistent terminology - both for the Index itself and its component parts (e.g. indicator versus variable) and thinking through precisely how we distinguish between ‘poverty’ and ‘deprivation’. We’ve found this distinction from the team behind the Index of Multiple Deprivation helpful: ‘‘Deprivation’...refers to people’s unmet needs, whereas ‘poverty’ refers to the lack of resources required to meet those needs.’ 

    We’ve begun to write all of this up into a first take on our ‘minimum viable documentation’ which you can take a look at if you’re interested in understanding more (we’re assuming writing this as we go will help consolidate our thinking and save us a hideous job at the end of the project!)

    https://docs.google.com/document/d/17orotUvW8HBzoTcPOo0LbTmFWPn6Q-UQCmGHy46Abdo/edit?usp=sharing

    1. Consolidating the Optimal sort research and identifying the themes for the Index. The four themes are: 

    *Income

    *Housing

    *Education, qualifications and employment

    *Wider indicators of poverty (name TBC but inc crime, health and environment)

    1. We started to pick out variables for each theme. This was harder than we thought but has helped us revisit point 1 and think further about the coverage of the variables we include and the balance of internal and external data.

     

    The Challenge: 

    It was highlighted this week that 'time' is the key challenge within our project, as many of our project team our working on multiple projects at the moment. To combat this we plan to block out chunks of time during the sprint to enable the team to commit to maintain momentum.

    We’ve been without our Product Owner this week (but have added Liz to the project team) but now Lisa’s back from leave, we need to try and steal some of her time from her other work so we can test our thinking over the last week and make sure our progress around methodology, themes and variables, is going in the right direction.

    Next: 

    We plan to finish identifying the remaining indicators for each theme, and start talking to the stakeholder owners of those indicators data sources.