Provision of Socio Demographic Data

Tender description

Indicatively the data will be used to: Get in in depth understanding of the population in England, Scotland and Wales using the following demographics to support decision-making: address/postcode affluence age crime levels distance to motorway/main road distance to public transport education levels/qualifications employment status gender house value household income housing status marital status media preference mobile phone, tablet & online usage newspaper/magazine readership number of children and age personal hobbies public transport links shopping habits social class vehicle ownership Data will be used to understand the characteristics of drivers and vehicle keepers, and how likely they are to use DVLA's online services prior to, and following transformation of DVLA services. Allow DVLA Data Analysis team to understand affluence levels and likelihood of population to pay for DVLA's products and services. Optimise public resources to save money and deliver economic resilience. Combines with individual and area data to understand health needs to benefit Drivers Medical analysis. A challenge in population health is identifying the characteristics of communities, environments and policies that promote health and wellbeing. These characteristics have the potential to assist drivers medical to forecast likely conditions based on population data. The analysis of situations from demographic-based predictions may help to identify such areas of best practice and provide much needed information. Third party data is required to allow service managers to predict whether customers of different socio demographic backgrounds are able to use DVLA products and services with the greatest amount of ease possible. As the data science team within Customer Insight Unit continues to investigate the benefits of machine learning techniques, socio demographic data will be extremely useful in exploring where complex interactions exist and the outcomes of interest, in ways that traditional regression approaches may not be able to adequately model. Continue the production of lookup tables for our mail section to advise customers of their nearest service providers (i.e. the Post Office) and medical advisers. Bolster policy and service development to ensure that any spend on new projects/initiatives, communications, face to face interaction with the customer etc. is optimised and justified. Analyse the data on driving convictions. Analyse the take up rates of Direct Debit and the impact of abolishing the tax disc on VED compliance. Carry out analysis to support customer insight and usability testing work/initiatives Carry out analysis at the request of DFT and Wider Government