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October 20, 2011 / Jo Ivens

DataBridge findings part 1

This 1 of 4 blogs on key issues arising from the DataBridge project to be published this week.

Aim: To summarise what we found with the organisations, their characteristics and capacity regarding data.

DataBridge set out to learn what we could about data use in six selected local groups, to assist them in their thinking and learning about data analysis, and to explore the potential of Open Data.

Brighton & Hove CAB is the local branch of the national Citizens Advice federation of CABx. They have 11-20 paid staff, and up to 50 volunteers. They are one of the larger VCS organisations in the area, and one of the largest advice providers, open to anyone who requests in on a range of issues.

The Carers Centre for Brighton & Hove is a local charity supporting people with a caring responsibility. They have 20 full and part time staff, the majority of whom provide direct support to carers, and a similar number of volunteers.

East Sussex Credit Union have 5-10 staff and 21-50 volunteers, making them a medium sized local organisation. They provide savings and loans, and light touch money advice to members who are from Brighton & Hove and East Sussex.

Amaze has 11-20 staff and 15-20 volunteers, making them a medium sized local VCS organisation. They provide support to families with disabled children, including a helpline, Disability Living Allowance support, independent parental support and transitions to adulthood.

MindOut have 1-4 staff and 11-20 volunteers, making them a small local VCS organisation. They provide support services to LGBT people with experience of mental health issues including advocacy, casework, group work, anti-stigma activities, mental health promotion activities and peer support.

Grassroots has 5-10 paid staff and 1-4 volunteers, making it a small social enterprise. They provide training and consultancy to social care and health workers, and to community members on suicide prevention, intervention and mental health both locally and further afield.

What do groups mean by data?

DataBridge started with the assumption that in this context, organisations’ data could mean very broadly any set of information about the organisations’ users and services. We explored this through our interviews with the groups, their interpretations can be summarised as:

  • Information on users: numbers of users, their geography, details of demographics & services used

  • Information for funders: monitoring information collected for Partnership funders, commissioners or trust & foundation funders

  • Qualitative information: softer information on user experience, need, anecdotal evidence gathered from conversations, focus groups, observations of staff

  • User experience: feedback, complaints from users, discussion with other organisations

Awareness of external sources of data was varied, with some organisations using a variety of government data sets, such as Job Seekers Allowance and other benefits data, the Indices of Multiple Deprivation and Census 2001 data. Some (due to capacity or skill issues) tending to rely on local or national infrastructure or issue organisations to analyse trends for them, and then relate these findings to their organisation second hand. Only half of the organisations were aware of or used local sources such as the Brighton and Hove Local Information System (BHLIS).

Awareness of open data was generally low (a later blog covers open data in more detail), with groups aware of the term, but limited understanding of what data this might refer to or the opportunities that it could present to their organisation.


The size and resource level of the group did not necessarily correlate directly with the value placed on data and the amount of time given to data management & analysis in the staffing structure. Organisational culture, business approach and practical awareness of data in a strategic context were more significant. For example,

  • Brighton & Hove CAB (large organisation) maintain a very detailed database as part of Citizens Advice information protocols, but do not employ a specific staff member for management and analysis of data. Data analysis and its relation to policy undertaken by senior staff as part of their wider role.

  • Amaze (medium) employ a dedicated database manager thanks to being contracted to provide a statutorily required database, and an organisation-wide commitment to data collection and use. Effective use of this staff member across management all of their services.

  • Grassroots (small) invest significant time and energy in getting their evaluation and data collection systems right with the involvement of most staff, plus work of a part time intern, with a focus on quality of their product and business development.

Skills and capacity

Most organisations felt that they had at least some skills on data analysis, but none were 100% confident that they had the right skills or sufficient staff time to make the most of their data, to do major analysis projects or to make the most of potential opportunities presented by open data. Pressure on resources and need to prioritise funding frontline work was inevitably highlighted as a key factor behind this.

5 of 6 organisations used their own ‘hard’ (i.e. quantitative) data to analyse trends in service use, for example, East Sussex Credit Union’s monthly monitoring of Key Performance Indicators such as number of members, shares (savings), share value, % members on a payroll scheme, how many paying in benefits, amount of loans, number of loans, average loans.

In at least one case within the cohort, significant work would be needed if they were to establish electronic data collection about services and users. This need may be much more widespread in the broader community and voluntary sector in Brighton. Data collection and data management support needs could usefully be explored further by infrastructure organisations or Dialogue 50:50 in the future.

Need v demand

There was a tendency for groups to use identification of users (demand) as a way of showing need. Most organisations expressed a desire to do more on analysis of need.

4 of 6 organisations, to varying degrees, used external data in conjunction with their own data to examine service uptake (demand) compared to the potential population of service users. For example, the Carers Centre compare their data on local users to Census 2001 data to examine the % of carers in the population.

3 of 6 organisations used data to examine need and potential need for example, Amaze are aware of the limitations to their knowledge about the population of children with disabilities in the city, where they are and what their needs are. Based on national estimates that 5-7% of children have a disability, Amaze estimate they have details on perhaps half of all eligible children in Brighton.


The six groups were chosen to represent a rough cross section of the local voluntary sector in terms of type and size of organisation, but may be more focused on data analysis than the broader population of VCS groups.

The sophistication of data management and analysis reflects organisational culture and resourcing as much as size or client group.

All the groups undertake, to varying degrees, analysis of internal and external data to look at service uptake, trends in service delivery, needs of their client groups and demand for their services.

With the increasing importance to each organisation of demonstrating the need for their services and the quality and impact of those services, having the skills, capacity and culture to make effective use of the available data and evidence is becoming critical to VCS organisations.

There is much more that could be done to identify:

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