The Effective Partnership Data Management project is a Communities and Local Government (CLG) project, commissioned in August 08 and due to publish final reports in February 09.
The project is tasked with building models for data sharing between partners that will help LSPs deliver services and change more effectively for their citizens and better support the ambitions of central government.
In order to make sure that the models are grounded in reality and reflect local needs, deliverables will address the strategic and tactical needs of 6 to 8 volunteer LSPs.
A primary deliverable will be the definition of a number of pilot projects, for each volunteer LSP, that would deliver the business benefits outlined below.
Depending on the nature of these projects (scale of benefits, wider applicability of proposed solutions, alignment with other strategic initiatives etc), and subject to business case approval, CLG will consider funding the implementation of a number of pilots by volunteer LSPs.
As discussed above, the data sharing pilot projects defined by this work will be shaped and owned by volunteer LSPs. In order to ensure that they are applicable to the wider LSP community we have selected a range of two-tier, metropolitan, rural and London councils.
In addition, we will also be involving a wider community of LSPs, central and regional government to validate the deliverables produced.
In order to define pilot projects that will deliver quantifiable benefits, they will be scoped in the context of a discrete number of National Indicators, provisionally as follows;
Although in terms of immediate benefits the pilot projects will focus on these indicators, in Infrastructure terms they will establish a reusable platform that could be used deliver similar benefits for the majority of the 198 National Indicators.
Following initial desk based research and a workshop with 6 LSPs; the following potential benefits were identified;
For example, if we could use shared data to accurately predict the likelihood that elderly citizens were likely to need care home provision in the next 6/12/18 months we would be able to plan capacity and resource requirements more effectively.
For example, if we could automatically generate performance metrics from detailed citizen data (held securely and not accessible for viewing) we could reduce the effort to calculate performance metrics, enable more timely generation and generate performance data at more granular geographies.
For example, if we could understand the causal relationship (using statistical methods) between improvements in operational performance and improvements in National Indicator performance, we could understand where resources should be focused for maximum impact.
For example, if we could share data to notify partners of key events in customers lives to trigger partner support activity we could significantly improve service delivery (and prevent back office failure demand).
For example, if we could share data to predict which citizens qualified or would benefit most from services, we could target service delivery at the most needy
For example, if we could share performance data across partners, within a framework that showed their contribution to outcomes and allocation of resources, LSPs could more effectively define and deliver co-ordinated strategies across partners.
All of the above will help service providers to better understand citizen needs, and therefore provide them with better, more relevant information on services and performance. Also, if we can develop a model that illustrates how different local agencies are working together to deliver outcomes we can start to present a more unified image to citizens as well as engaging them in more effective dialogue around options for service delivery.
As mentioned above, this work will define how these benefits could be delivered for the selected National Indicators.