Kirklees Borough Council

By the time a customer presents to the council in crisis it’s often too late to offer them anything but intensive intervention services – these are typically expensive.

The council holds extensive amounts of data on customers but it remains disconnected from both wider departmental and Council services. We anticipate testing the effectiveness of various data science and machine learning techniques in the production of a risk-based scoring matrix built from known historical cases. Effectively spotting trends and ‘trigger events’ with a view to predicting future negative outcomes. We want to examine the feasibility of this and demonstrate a business case to unlock valuable insight from datasets across the council.

For example, an elderly person needing urgent residential care may well have benefited from earlier advice and guidance, lower level services, equipment and adaptations helping them to remain living independently for longer. It’s possible that this individual may have significant life events that could have lead to their needs rapidly increasing. eg family bereavement. By connecting these various threads (and their associated systems/data), this scenario could have been prevented.

The impact of investment in this area could be wider spread with numerous use cases eg. Housing, Children Services, Planning etc.