This is important stuff, but pity the intelligence teams who have to understand performance data for each and all of these areas, monitor progress for local priority neighbourhoods, and do Total Place-style analysis that combines spending and service data from service organisations covering different areas.

To help central and local analysis teams understand performance for complex geographies, OCSI are working with Communities and Local Government, Work and Pensions, and the Office for National Statistics. As part of this project we’ll be developing tools to help researchers model data to small areas, understand how to develop robust data for functional economic areas (a key component of local economic assessments), and developing National Indicator data for the Thames Gateway and other areas. We’ll be posting more about our work on the project as it develops, but if you’re interested then contact us.

Related work:

• OCSI (2010), How can the State of the Cities Database be more useful? Recommendations for CLG based on user consultation
• OCSI (2010), Technical feasibility for improving the State of the Cities Database, report for CLG 

By far the bulk of annual spend (ranging up to £130K) were staff costs, and system managers identified that the main area for potential saving was in reducing the time spent obtaining and loading data. OCSI have been working with several local information system teams to save time spent in inputting data and setting-up performance reports and needs assessments (for local economic assessment, joint strategic needs assessment and other work). The Data and Report Packs load straight into standard local information systems including InstantAtlas, providing a rich range of indicators and high quality report outputs. To find out more, see our pages on the Data and Report Packs, or contact us.

Key findings from the “Understanding the value and benefits of establishing a local information system” research include:

• Local information systems generate an overall benefit:
  • A conservative estimate of £140-210 value for an average user /year (time saved in obtaining information from other sources), giving a breakeven point of roughly 300-400 users per year for a system with average running costs. Most systems have many more users than this.
  • Many examples of information underpinning successful funding bids by local organisations
  • Using information well in decision making leads to better local public services, with those authorities demonstrating good information use more likely to be strongly performing (Audit Commission ‘In the know’ report), with 94% of LAs saying use of information has become an increasing strategic priority (Audit Commission ‘Is there something I should know?’ report)
• Where systems can make savings:
  • Main suggestions focused on decreasing time to input data
  • Off-the-shelf systems significantly cheaper than bespoke.
• Key recommendations for local information systems teams
  • Identify the value of your system: Collect detailed information about users and time spent on the site (and use the Local information systems value-assessment tool)
  • System managers should be encouraged and supported to adopt and share good practice from the Open Data programme, including the ONS Neighbourhood Statistics Data Exchange
  • Local information systems, performance management and finance systems should adopt common interoperability standards to make integration easier within, and across, partner organisations.

Relevant links:

• Foley et al (2010), Understanding the value and benefits of establishing and running a local information system.
• Foley et al (2007), Local Information Systems: A review of their role, characteristics and benefits.
• OCSI (2009), Supporting local information and research: Understanding demand and improving capacity

The September 2009 data showed that the total number of people claiming Jobseekers Allowance (JSA) across England fell by 4,700 compared with August 2009. Although only a small fall - those 4,700 people represent less than half a percent of the 1.3 million people now receiving unemployment benefit - this is more good news to add to the relatively small increases over the last six months. The three-month June-Sept increase of 2.4% and six-month March-Sept increase of 4.4% are certainly a good deal better than the 62% increase over the six-months from Sept 2008-March 2009.

There are other causes for optimism. The ILO unemployment estimates published yesterday showed a fall in the June-July monthly estimates, and a less-than-expected-rise in the June-August quarterly data. And Google has declared the worst of the recession is over, with net revenue up 7% and profits up 27% over the third quarter. However, there is a long way to go. Youth and long-term unemployment continue to rise, and across England, there are still two-thirds more people getting unemployment benefit than 12 months ago.

At regional and local level, the picture is also looking more positive. Data on the Local Economic Monitor identifies that 223 of the 326 Local Authorities in England recorded a decrease in the number of JSA claimants over the most recent period, with falls across most of the regions.

At regional level, only London and the West Midlands recorded a rise in claimant numbers over the period, see figure. Unemployment rates are particularly high in the West Midlands: four of the six local authorities with the highest rates of unemployment in England are now in the Greater Birmingham/Black country area. Based on the September 2009 figures, Wolverhampton has the highest proportion of people receiving JSA, with 8.2% of the working age population in receipt of JSA. Birmingham (8.2%), Sandwell (7.9%) and Walsall (7.4%) are also among the top six areas in England with the highest proportion of adults claiming JSA. The unemployment rate has risen significantly in these areas, with an additional 1,700 JSA claimants recorded in these four areas in the last month alone.

For further information and the latest data, see the Local Economic Monitor (you can sign-in or register here).

Stefan Noble and Tom Smith (OCSI).

I’ve been involved in the study as part of the external advisory group, and was impressed by the effort put in by the Commission team to develop practical tools for authorities to improve their information use for making decisions.  In this area, there are lots of tools aimed at improving researcher skills, but what’s often ignored or glossed-over is that evidence-based decision-making needs better skills from both researchers and decision-makers (an issue we highlighted in our work for Communities and Local Government on how to support local research). So it is great to see the emphasis by the Audit Commission on practical tools for elected members and senior officers, including sets of questions “designed to help members and senior officers consider whether they have all of the information they need to take a decision”.

Links to the report and practical tools:

• Summary report and Full report
• Self assessment framework
• Resources for elected members 
• Analyst diary
• Resource mapping tool
• Decision making guides
• Links to training and support

Tom Smith, OCSI.

• analysing and presenting small area data (eg, below District level)
• understanding and communicating trends and dynamics over time
• benchmarking comparisons (between areas, groups and services)

We are looking for good examples of visualisation that have:

• made an impact/ helped communicate findings to decision-makers;
• helped researchers understand the story behind the data.

The project/website will be an excellent opportunity to show case your own examples of good visualisation, and help contribute to common standards of good practice in the research community. If you have any examples, we would love to hear from you! Please email us on visualisation@ocsi.co.uk, or 01273 201 345.

Background

The project has been commissioned by the Department of Communities and Local Government, who are looking to understand the potential for visualisations to analyse and communicate data, and provide guidance for national and local analysts on making best use of visualisation.

Work on the project will explore questions including:

• What visualisations are being used by the public sector? What can we learn from elsewhere?
• Is there a useful typology (classification) of visualisation techniques for public sector users?
• How effective are particular types of visualisation in supporting public sector research and decision-making?
• What are the most appropriate visualisation techniques for particular purposes?

The primary output from the project will be a web application, to help users identify strengths and weaknesses of visualisations for particular purposes, also linking to examples and supporting material.

Further information

James Geehan, (Project manager), Communities and Local Government, tel: 0207 944 4857, James.Geehan@communities.gsi.gov.uk

Tom Smith, (Project lead), OCSI, tel: 01273 201345, tom.smith@ocsi.co.uk

Alternative formats

This briefing note is also available for download in PDF format and as a Word document.

So, in the spirit of joining these two themes up, I want to show that there are some good sources of data out there on equalities groups - and we should be using them.

Data4nr – signposting data: If you want to get hold of equalities datasets available on the web (for Local Authority areas and below), Data for Neighbourhoods and Regeneration (Data4nr) is worth a look. This signposts to all the major public datasets, across all the government websites – one click from the Data4nr site gets you straight to a specific dataset. It also allows you to filter datasets by key equalities groups (eg age, gender, ethnicity etc), theme (health, education, economy etc), and what geographical level the data is held at. The service is run by OCSI on behalf of the Department of Communities and Local Government, updated fortnightly, and is free to all.

IDeA Equality mapping: The IDeA Equality Mapping programme has been developing work around what information is available, which National Indicators could be disaggregated by equalities group, and how people are using this locally. They have also been running seminars over the last couple of months, with presentations on their Community of Practice (login needed).

South-East Equality and Diversity Data Tool: If you’re in the South-East, the South East England Development Agency (SEEDA) and the South East Intelligent Network (SEE-IN) have produced a comprehensive mapping of socio-economic data for the six core equality groups against their geography of interest. The Equality and Diversity Data Tool enables colleagues in partner agencies (public, private and 3rd sector) to access baseline data on these groups.

Equality Measurement Framework: If you’re interested in knowing about all the potential data sources, the Equality and Human Rights Commission (EHRC) has been looking at measures of equality. They’ve commissioned a hefty review of all the major national surveys and administrative data sources – 459 pages long, but some good stuff - but note that much of this data will only be robust at national or regional level. The EHRC is also shortly to publish its indicators for the Equality Measurement Framework [I’ll add links once this is published]. This will provide a set of measures that track progress for different equalities groups under ten domains - Life, Health, Physical security etc - and cover issues around inequality of outcome (ie groups faring badly compared with others), inequality of process (ie discrimination), and inequality of autonomy (ie how much choice and control do people have).

There are big gaps in the information needed for good policy-making around: the size and makeup of equalities groups; inequality between different groups; comparisons and benchmarking across areas; and where different equalities groups fare badly on specific outcomes.

However, there is lots of good data out there, and we need to be making the most of it. Then we can start identifying (and plugging) the real gaps in knowledge.

Tom Smith, OCSI

Quite apart from the debate over whether the survey questions are the right ones for assessing local progress, some LAs are talking about response rates as low as 20%. That could result in LAs struggling to meet guidance that the “achieved sample size should be no smaller than 1,100″. As a result, findings from the survey will come with pretty big margins of error (and even more so if you’re wanting to use the data to look at particular areas or groups). And this has consequences when it comes to identifying whether targets have been achieved or not.

We’ve explored this issue in work for the Department of Communities and Local Government, identifying which datasets are appropriate for target setting and performance assessment at neighbourhood level. To cut a long report short, the key message is that due to relatively small numbers of cases, few datasets are robust enough for target-setting at neighbourhood level (the main exceptions being benefits data from DWP), but that lots of datasets provide very useful intelligence. The full report ‘Assessing Neighbourhood-Level Data for Target Setting’ is available here.

The issue of sample size is very relevant to whether the Place Survey can be used to evaluate progress at LA level. For example, with 1,000 respondents, standard margins of error on any one indicator value are in the region of plus/minus 3%. With only 500 respondents, that’s more like plus/minus 4%. This is useful intelligence, but to demonstrate progress on these indicators you’d need to be seeing changes bigger than 6% with 1,000 filled-in surveys (and 8% with 500). That’s a pretty big shift to sign-up to as a National Indicator target, but any changes smaller than this could simply be due to chance fluctuation.

So, what are the key messages?

First, if we’re serious about using the Place Survey results for improving services and assessing progress against targets, local partners with low response rates will want to understand the pattern of non-response. Without this information, it’s difficult to know how representative the survey is of local resident views. For example, are particular groups less likely to fill-in and return the postal survey (those with low literacy skills, or poor English language, or in the most deprived areas spring to mind).

Second, local partners and Government Offices (and other agencies) need to be sure they’re taking margins of error into account when looking at indicators and targets based on the Place Survey and other sample surveys. It’s worth emphasising the Royal Statistical Society message that the “reporting of Performance Management data should always include measures of uncertainty”. Simply asserting that targets have been reached or not, based on indicator values, is not good enough.

Third, the process of identifying and setting targets for local priorities always needs significant input from research teams. Just because something is a policy priority does not mean that there is decent data with which we can evaluate progress. Einstein put it rather better - “Not everything that counts can be counted, and not everything that can be counted counts.”

Tom Smith, OCSI

The aim is to highlight issues of general interest.  But we’ll be staying relatively close to our focus on improving the evidence-base for public sector decision-making. So it will be more Sub-National Review than Strictly Come Dancing, more Local Area Agreements than Lewis Hamilton etc etc …

But it’s all a bit of an experiment, so we’ll see how it goes.

The OCSI team.