Team Types

Team types #

Summary #

Broadly, we might think of three types of analytic team within the ICS:

  • Performance
  • Data analysis/ reporting
  • Data science
  • Public health/ population health

The roles of these teams is discussed in more detail following. Quoted content comes from the data job family which is licensed under the OGL3.

Performance #

Performance teams:

…develop performance measurement frameworks - key performance indicators (KPIs), goals, user needs and benefits - and analyse the performance of a service or product against these, adapting your approach and framework appropriately and in line with any changes

Tools and approaches

  • SPC
  • RAG ratings
  • Board level summaries of KPIs

Data analysis and reporting #

Data analysts:

“apply tools and techniques for data analysis and data visualisation (including the use of business information tools), collect and migrate data to and from a range of systems manage, clean, abstract and aggregate data alongside a range of analytical studies on that data manipulate and link different data sets summarise and present data and conclusions in the most appropriate format for users”

Tools and approaches

  • PowerBI/ Qlik/ Tableau
  • Benchmarking
  • SPC
  • Statistical analysis
  • SQL

Data science #

Data scientists

…use data to identify and solve complex business problems. They have an interdisciplinary focus, using techniques and knowledge from a range of scientific and computer science disciplines (for example, statistics, analytics, machine learning)

Tools and approaches

  • R/ Python/ Julia/ SQL
  • Time series analysis/ forecasting
  • Statistics (especially e.g. regression models, GAMs, GEEs, etc.)
  • Machine learning
  • Natural language processing
  • Open tooling/ version control

Public health/ population health #

Population Health Management:

…improves population health by data driven planning and delivery of proactive care to achieve maximum impact. It includes segmentation, stratification and impactabilty modelling to identify local ‘at risk’ cohorts - and, in turn, designing and targeting interventions to prevent ill-health and to improve care and support for people with ongoing health conditions and reducing unwarranted variations in outcomes

Tools and approaches

  • Segmentation
  • Health economics
  • Public health and epidemiological analysis
  • Impactability modelling
  • Population health profiling
  • Opportunity analysis