Intelligence led Business Processes:

Birmingham CSP -Analysing intelligence to determine priorities

Birmingham CSP is structured to support information sharing and the intelligent analysis of data. Through their Information and Intelligence Team, the CSP has developed a Composite Index of community safety, based on the Victim/Offender/Location problem-analysis triangle, which enables them to effectively determine local strategic priorities, as well as guide their delivery responses.

What they did

Birmingham CSP developed a local structure to support intelligence-led business processes. The Information and Intelligence Team, which bridges the strategic leadership and ongoing local delivery (as shown below), is responsible for:

  • Updating and maintaining COSMOS (multi-agency web-based product on www.cosmos-bcsp. com).
  • Performance management and analysis, including regular performance management information, briefings to the CDRP boards, police commanders and constituency directors, overview and scrutiny panel and a tactical assessments for the city tasking and co-ordination process.
  • The annual strategic assessment.
  • Bespoke intelligence products commissioned through a formal request process to ensuring the work is directly related to the aims and objectives of the partnership with a tangible outcome.

The structure of the partnership, and specific responsibilities of this team are illustrated below:

The Structure of the Birmingham CSP, and their specific responsiblities

A key part of the team’s responsibility is the production of the strategic assessment for the city and then for each of the ten constituencies. To inform the assessment, the team developed the Composite Index. As demonstrated below, each of the core themes for community safety is analysed geographically, to create a layered picture. This enables the partnership to identify strategic priorities and shape delivery accordingly.

In brief, the Composite Index is developed by:

  1. Identifying specific issues within each of the core themes, based on a wide range of quantitative and qualitative data.
  2. Analysing each of these issues using the victim/offender/location problem-analysis triangle.
  3. For example, hate crime was identified as a key issue under the violence and vulnerability theme. The team asked:
    • Where victims of hate crime reside (victim)?
    • Where offenders who commit hate crime reside (offender)?
    • Where does hate crime take place (location)?
  4. To improve the understanding, this analysis was not restricted to existing administrative boundaries.
  5. Agreeing the strategic priorities and guiding delivery accordingly.

What it involved

The Birmingham CSP process for developing the strategic assessment is roughly a 4-month project, within which the index forms a significant part. As it relies heavily on data from multi-agency sources, much of this time was spent in sourcing the data and formatting/cleansing/etc. The time it takes varies according to the number of variables that are included. The assessments are made available on http://ww.birmingham-csp.org.uk (link opens in a new window).

What impact it had

Through the Composite Index, Birmingham CSP was able to identify a “gap” in community safety in the area. In order to improve the overall performance on this indicator, the partnership aimed to reduce this gap. While this gap still exists, significant improvements have been delivered and it is reduced in comparison to years prior to the Composite Index.

In addition to performance improvements, this practice has also had wider benefits, including:

  • A shift in focus from a silo mentality – both in terms of a geographic focus up to and now beyond administrative boundaries as well as understanding the intra-relationship of different community safety themes and priorities.
  • Joining up LAA blocks – by demonstrating that the communities most affected by community safety are largely similar to other areas of the strategic partnership and LAA.
  • Improvements in data sharing – by highlighting existing gaps in the process and encouraging the development of new data sets with agencies keen that their data can be included.

Lessons learned

Key lessons learned from this process include:

  • The need for analytical capacity and technical skills – e.g. the analyst needs to decide which denominator to use to normalise data or if volume/clustering is more appropriate.
  • Importance of prioritisation – the Composite Index will never contain every set of data desired and some core priority themes will be weaker than others.