Manchester City Council (MCC) is looking to establish a framework to help delivery its research and intelligence work, in support of its wider objectives. The framework will provide a mechanism through which expert support and advice can be effectively obtained to meet the myriad of needs of Manchester.

Framework Structure
The Performance Research and Intelligence (PRI) function in MCC is establishing a procurement framework which will help support the work of the directorate, The Council and our partners. The Research, Evaluation and Data Science (REDS) Framework covers a broad range of activities which have been structured into six areas, known as LOTs.

LOT 1 - Data management, open text coding, text analytics and transcribing
• Coding of text, including responses to open text consultation questions and internal case notes
• Sentiment analysis
• Machine learning analysis
• Transcribing audio files
• Recoding and transforming datafiles

LOT 2 - Primary Research
• Opinion research - Measuring perceptions and opinions of residents, businesses, service users via interviews, survey, focus groups
• Observation/ ethnographic research
• Insights including behavioral insights

LOT 3 - Evaluations and Impact Assessments of Projects and Programmes
• Theory of Change and Logic Model development
• Evaluation and Impact Assessments of projects and programmes including both outcome and process evaluation
• Cost Benefit Analysis
• Randomised Controlled Trials
• Rapid Evidence Reviews of services, systems and current internal practice
• Equality Impact Assessments (EIA) and Health Impact Assessments (HIA)

LOT 4 - Property & Economic Intelligence
• Residential property market analysis
• Commercial property market analysis
• Economic research including businesses, employment and skills

LOT 5 - Analytics and Modelling
• Analysis of complex data and presentation to a wide range of audiences
• Statistical Analysis, including descriptive statistics of time series, trends and demographic information
• Statistical Modelling, including classification and regression modelling to support population segmentation, risk stratification and predictive modelling
• Analysis of markets, including Social Care Markets
• Population and Service needs assessments to inform policy and commissioning
• Implementing data standards, quality and supporting approaches / systems
• Analysis and Modelling of demand for services to support service planning and commissioning decisions
• Presentation of analytics and modelling output to non-specialist audiences within bespoke and existing reports
• Development of analytical and modelling processes into standard workflows.

LOT 6 - Expert Networks: Cross-cutting Research and Evidence Generation
• Rapid review and synthesis of multiple and complementary evidence sources
• Complex systems modelling
• Advanced and cross-discipline economic analysis