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Using data for Local Industrial Strategies

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Over the last year, we have been advising local authorities about how to use the evidence to develop strong Local Industrial Strategies (LIS). With local authority partners, we wrote Ten Principles for developing LIS, and ran a variety of workshops on the pillars of productivity.

Good data is key to the first two Principles: to get a granular understanding of your local economy and understand how it is evolving. As a follow up piece, we have written detailed guidance and ten case studies on how local authorities can make better use of a variety of data sources to improve economic analysis. This guide acts in support of those local economic practitioners who have no or little experience of the data available.

Data is more easily accessible now than it ever was before and we provide a review of where, what and how datasets can be accessed for policy analysis. We present a few case studies of ambitious data initiatives from UK local and combined authorities, and outline the potential insights practitioners can get from mapping industries or estimating network densities.

In an earlier blogpost, Meg Kaufman wrote that data can only provide part of the picture. We review data limitations that might further pixelate that image and list common issues faced by local authorities. Administrative datasets are lagging; surveys are pricey and sometimes patchy. The process to access secondary datasets can render the data untimely.

This contrasts sharply with the wealth of data generated every day – 2.5 quintillion bytes of data pour through our fingers into the apps and websites we use to talk, to buy, and to commute. This data is cordoned off by companies and local authorities may not always have access to this highly liquid asset. But this is starting to change. A new trend has emerged over the last decade whereby private companies are striking data collaboratives with governments. LinkedIn is providing free area-level data on applicant and job pools to help policymakers target their efforts and better design their apprenticeships or estimate the extent of skills mismatch. Organisations such as The Governance Lab at the NYU Tandon School of Engineering have been pushing for these data collaboratives to become common currency. They are seeking greater evidence on the ways government can incentivize firms to share their data.

We hope our report goes some way towards helping local authorities make more data based decisions, especially as they design their local industrial policies. If you have or are looking to set up any initiatives discussed in the report, or have any questions about our data piece, we would love to hear from you.

View the guide