Step 3: Analysing the data
This section will help through the process of analysing gaps in the evidence base for the local economic assessment (LEA). It will help you think about whom you should talk to and gives some hints and tips about how to address gaps to develop a robust analysis.
- Analysing data: key starting points
- Using data to tell a story
- A simple tool for getting the balance right in analysing evidence
- How to analyse evidence
- Manipulating data
- The identification of gaps
- Links to resources
- Directly relate your evidence to key themes emerging in your 'story of place' - identify areas at which the narrative and the evidence seem to be at odds.
- Identify issues and questions at key stages of the assessment - assess evidence against them at each stage.
- Structure your LEA to make it easy to apply evidence to each section and provide a checklist of information sources and reference by subject area so that any gaps are easy to identify.
- Map information where possible and in a way that enables data to be combined in a number of ways - this will show up geographical 'quirks' and gaps that can be explored more fully.
- Test your findings with others, to explore anomalies, including consulting actively with relevant elements of your local strategic partnership (LSP) structures.
- Prepare clear conclusions on the gaps that need to be filled and recommendations on how that will be done.
- Do not restrict yourself to obvious sources of information - think laterally: talk to a range of people about how to fill gaps, transfer approaches that worked for other assessments.
Analysing data key starting points
- Check with data experts to confirm gaps and use their expertise in identifying ways to close and fill gaps.
- Follow advice in 'Magenta book' on systematic review - check whether other similar research has been commissioned.
- If the need to commission is identified, gain partner agreement to share costs.
- Set up project team to agree brief, project management and identify suppliers and or consultants with appropriate skills.
- Spend time and effort on the brief to ensure it focuses on gaps and does not repeat known information.
- Small area data is important as it can show the pattern of the distribution of key economic features within the geographies pertinent to the LEA - if possible data should be broken down to lower super output area (LSOA) level.
Using data to tell a story
Consider using contacts developed in a range of services as a source of intelligence, for example:
- Local commercial agents can provide up-to-date information on property prices and take-up for an Employment Land Review and land use monitoring.
- GP registrations can provide more up-to-date information on population and movement.
- Leisure operators and retailers may be able to provide analysis and perspectives on local catchments and or flows.
A simple tool for getting the balance right in analysing evidence
Having collected all the evidence you have access to, you need to ensure it is fit for the purpose of assessing your area's economy.
To tell a story of place, there are three core areas of analysis:
- What is the data telling you in terms of statistically reliable and defensible data?
- What are the perceptions of the area? What do businesses and communities feel about your area in more qualitative and harder to quantify ways?
- What is intelligence telling you? What are recent surveys and or research telling you about your area, including business surveys?
It is helpful to consider ways of demonstrating how you have reached a conclusion from your analysis.
A symbol such as the triangle used below could help demonstrate simply to the reader how you have arrived at your narrative or conclusion. This can show the different emphasis these elements have played in your analysis and you can describe this emphasis, in terms of percentages, to help the reader understand how you have reached that conclusion.
What an analysis might show at a local authority level - high on data but lower on perception and evidence. For example, describing demography of the area using mid-year population estimates at district level without having up-to-date evidence of actual population at LSOA level.
What an analysis might show at an LSOA level - low on data but high on perception and evidence. The use of local surveys and consultations to describe local barriers to employment in deprived areas, or qualitative data that highlights the informal economy
It also helps you and others to value the role of perception and other evidence in telling your narrative. It also helps in getting out of the ‘revolving door' syndrome of accessing data at the right spatial level, which tends to result in no action.
How to analyse evidence
The IDeA (now Local Government Improvement and Development) has produced a very handy briefing note laying out how to analyse data. The briefing note defines analysis as "a process for transforming a collection of data into a body of information that has meaning and significance". It also emphasises the point that no matter how good the data, its usefulness will be determined by how well it is analysed.
How to analyse data - IDeA (now Local Government Improvement and Development) briefing note
The briefing note also has a very useful summary of the main issues that need to be considered in relation to the analysing data, which is repeated below:
- Never leave data to speak for itself - through analysis you have to create meaning and understanding.
- Data needs to be good quality - reliable, robust, accurate.
- Use the data to test hypotheses and theories and to seek answers to specific questions - be alert to new insights that emerge from the data and question your assumptions.
- Relate the type of analysis you carry out to the purpose for which you need the data and your product. Think about who will be your audience and their needs and their capacity - for example, to understand complex statistics.
- Contextualise data about areas, population groups and so on by comparing it with data from elsewhere.
- Look at trends over time rather than a simple snapshot of a single moment.
- Use different and appropriate techniques to analyse quantitative and qualitative information.
- Analyse data from a number of different sources, as a cross-check.
- Analyse associated data in parallel, for example look at all health problems side-by-side.
- Make linkages between different bits of data - look for cross-cutting issues within and across themes.
- Avoid assuming a causal relationship between associated data.
- Think how you will want to present the information, as this will have some impact on how you carry out the analysis, for example, the format in which you analyse data - in tables, graphs or maps and so on.
Using data in innovative ways can provide you with useful insights. Below are two examples of different methodologies that have been used to manipulate data to understand your area from different perspectives.
Example: living wage and worklessness
Knowing how many people earn below the 'living wage' in your area makes it possible to assess the economic impact of introducing a living wage.
The implementation of a living wage would increase the spending power of individuals, and the economic prosperity of whole communities. It could help to reduce poverty and improve all-round financial health. It will also have an effect on worklessness. If employers accept the living wage widely it will lead to higher incomes and more workless people will have an incentive to move into work.
In London, where the living wage has been introduced by the Mayor of London and the Greater London Authority (GLA), employees have reported that it has made them far happier in their work. It has improved their standard of living, enabling them to better manage their bills, have a better standard of family life and pay for education and training.
If advice agencies are fully appraised of the extent to which in-work benefits can increase in-work incomes, even with wages at the living wage or between that level and the minimum wage, then this will be positive for 'making work pay' and reducing worklessness in your area.
A possible danger is that if the living wage concept is accepted by advice agencies but not widely by employers, then workless people may not be willing to accept wages below the living wage even if they are substantially better off than on benefits. In economic language, a living wage could increase the ‘reservation wage' - the minimum wage which workless people are willing to accept before returning to work - and thus reduce moves into work.
The methodology for calculating the living wage for your area should be based on the GLA's model taking an average of two elements: the income distribution approach and the basic living cost approach. This is then uprated by 10 per cent to provide a small excess over poverty levels. To date, the hourly living wage has been calculated for London and the South East regions, producing figures of £7.60 and £6.94 respectively.
Rural economic profiling - towns in SuffolkRural economic profiling - towns in Suffolk
The identification of gaps
Once you have collected and analysed the evidence and consulted internally and externally to ensure it reflects the unique nature of your territory, you should have a clear set of gaps in the information needed for your analysis.
Before seeking to plug these gaps, you should assess how important they are and consider the cost and challenges of addressing them. You have a number of options to help you through this gap analysis process:
- The use of proxies, measures of other related things, which enable you to make insightful inferences about the actual data you cannot get.
- Qualitative information, based on informed opinion and expertise, which provides key insights about the information you can't access.
- Local collection of information, using your own resources, where no reliable 'off-the-shelf' source exists.
- Commissioning original research through third parties, usually consultants - this is a tricky and costly process and should not be entered into lightly.
Identifying who can help with the development of strategies to address gaps is a straightforward process. The regional development agency (RDA) is a good starting point: they may be prepared to help commission research. The Office for National Statistics (ONS) regional presence staff based in the RDAs - WMRO in the West Midlands - are a particularly useful resource in this context, given their links back to ONS nationally.
Sub-regional observatories and your local information system (LIS) can also provide expertise through their mix of economists, data managers and researchers. It is worth having a detailed discussion with those who have day-to-day experience of research and data analysis. It is likely that they will have had to work through pragmatic ways of filling gaps over a range of subjects and data. They also may be able to help with a commissioning approach and help manage or support the process. Their involvement could cover:
- developing a brief or commissioning research
- analysing the results
- advising on how the additional information will fit in
- inform the overall assessment and how it will add to the shared evidence base.
Some key gaps in evidence
- Flows and linkages - information on the movement of people and goods is based on 2001 Census data and is now quite old - more up-to-date data is not straightforwardly available.
- Productivity - gross value added (GVA) data is hard to access meaningfully below county level - in building up a profile of your area, think about how you might measure productivity.
- Business data - real-time data about the profitability and employment profiles of businesses is very hard to access. Data is collected on a regular basis, for example, by chambers of commerce, but is often based on small sample sizes at the local level. Think whether and how you might collect data directly through regular surveys.
- Land and premises - changes in the take-up and availability of land are key areas for joint working between those leading the assessment and planning policy and development control staff. Internal systems can be set up, particularly where land use monitoring is done effectively, to develop trends and profiles.
Links to resources
3 May 2012