Creating a Conducive Zone for Innovation in Children’s Social Care

Innovation activity in child and family services has accelerated over the past 2 decades, particularly in England, where substantial government investment in pilots, diffusion activities and evaluations has created an emerging body of literature on effective approaches and characteristics of efficient practice systems. However, the literature on the interplay of enabling or impeding factors and processes at a local and national level tends towards the descriptive, while theorisation of the underlying dynamics remains limited. This paper presents the findings of a framework analysis produced through integrating thematic insights from a narrative review of academic and grey literature with those drawn from interviews with 21 expert informants engaged in social care innovation within the UK within policy, leadership or researcher roles. Analysis enabled five clusters of ‘conditional parameters’ to emerge, covering: mobilisers; system capabilities; design and implementation features; organisational culture, climate and processes; and the macro context. Three or four conditional parameters are identified per category, each outlining factors and processes that could either facilitate an innovation or create barriers that needed to be overcome. To achieve an environment most conducive to innovation, attention needs to be paid to the interplay of these conditions, recognising that their operation and influence might be occurring out of awareness and scrutiny. Innovation is found to be best facilitated by a stable, well-supported workforce that feels energised and confident to create and implement change. This requires developing a supportive, collaborative, relational culture and climate of mutual trust, where reflexive supervisory and evaluatory mechanisms follow the human-centred grain of professional practice and where staff feel safe to experiment and make mistakes. This can enable a conducive zone for innovation to open up, even where policy drivers and the availability of resources are less than optimum.