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Friday 20 September 2019

Marc Radley's picture
By Marc Radley

Understand and choose solutions that can achieve ROI meaning best value and improved service outcomes.

For non-technical managers and frontline workers in Children and Young People’s (CYP) services, access to new data and information science methods and capability can be a double-edged sword.


On the one hand, it offers an incredible opportunity to improve journey’s and outcomes for young people and make services more effective, by enhancing connected data to reveal patterns that help us be confident in how best to act and manage responsibilities.


On the other hand, the path to deploying and using such a sophisticated capability is littered with magical and confusing assertions and concepts. At times, Children’s Services leaders feel they lack knowledge to shape decisions and assume IT or data experts can.

Are you or decision-makers in your organisation feeling overwhelmed by the challenges? Below, we explain clearly some of the key elements contributing to effective data, information and insight management applicable to Children’s Services.


Data science uses scientific methods, processes, algorithms from professional knowledge of the domain to generate insight from data. The data captured and explored can be brought together and compared and can take many forms: it could be statistical and historical information (the journey and costs of a number of successfully resolved cases) or unstructured data (such as text from case notes or emails) or a combination of both: This can now include extreme data volumes and granularity from multiple databases easily.


At the heart of an insight system is a conceptually linked data model designed to combine and re-sequence representative data from one or more sources. It can aggregate and manipulate current and historical data for multiple different purposes. Analytics software now gives the power to ordinary uses to explore the compiled data at all information levels (like Google Earth). With so much diverse data being continuously updated with differing quality, representativeness and complexity, an effective dynamic system to bring it together in one place, means efficient and effective high levels of analysis overcoming the limitations of existing databases.

Linking data for the purpose of understanding multiple, complex needs can show how small numbers of individual, outlying child journeys lead to poor outcomes and very high costs (such as in Youth Justice.) When this data is held in fragments in different operational databases it’s impossible to see these kinds of patterns and truly consider the longer term costs of suboptimal responses.


Likely was incorrectly attributed to Einstein. When asked how he would spend his time if he was given an hour to solve a thorny problem, he said he’d spend 55 minutes defining the problem and alternatives and 5 minutes solving it.

The key to innovation and improvement is bringing observations and different perspectives together to look at things differently. Bringing representative groups together can create fresh system maps and we can now make dynamic computer models to show quality, behaviour and cost drivers in highly complex systems.  This helps define which data is needed to include in a higher level more holistic analysis.

Well designed specialised tools like ChildView Hub and ChildView QlikSense can use these maps to easily and flexibly prototype joining up data sources, for example around Risk and Vulnerability analysis. It’s a route to accelerated pattern spotting using problem solving and action learning groups. The analytics insights emerge from the collaboration and interaction with the models and the data to generate action learning cycles.


For compliance, we need to make sure that data is being used only in the right circumstances and for specific, permitted purposes with appropriate consent. Governance protocols set out these conditions, and these can be implemented through a multi-organisational framework of consent, making it easier to unlock and integrate relevant data. Highly secure Cloud environments centralise this as well as make data source integration easier to implement. These environments can now be very robustly configured to protect against data misuse and assure cyber security and confidentiality.


This is the way in which a machine with software and data can learn on its own without being explicitly directed. The application of AI, means that software robots can learn and improve from experience of finding patterns in the configured linked data models that lead to outcomes. AI techniques can be used to flag up issues to practitioners that can’t easily be seen in all the latest information. These could be fed to the immediate point of contact to be interpreted for appropriate action.

If you’d like to know more about how these tools, approaches and systems could benefit your Children & Young Peoples services organisation, talk to one of our knowledgeable specialist consultants.



Access to new data and information science methods and capabilities can be a double-edged sword for non-technical managers and front line staff in Children and Young People's (CYP) services. While on one hand it gives them the opportunity to provide effective services for CYP, on the other hand, handling such large data and basing decisions on it scares a lot of the people involves in the CYP decision making process. This article aims to some of the key elements contributing to effective data, information and insight management applicable to Children’s Services.