How Can Data Analytics and BI Help the Public Sector?

Data is a strategic asset in all aspects of the public sector. By learning the skills to analyse the right data effectively, public sector employees have the ability to discover new insights, predict future trends, improve efficiency and make better decisions that improve public services.

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What is Data Analytics?

Data analytics is the process of analysing raw data to find meaningful, actionable insights, which can be used to inform and drive better decisions.

What Are The Main Types of Data Analytics?

There are four main types of analytics, Descriptive, Diagnostic, Predictive, and Prescriptive.

What Can Using Public Sector Data Be Helpful For?

  • Identifying specific cases from a wider group
  • Prioritising cases based on risk or need
  • Creating early warning tools
  • Making better and more efficient decisions
  • Optimising resource allocation

What Are Some of the Barriers to Using Public Sector Data For Analytics?

  • Records are often only recorded on paper
  • Records are digitised, but in hard-to-analyse formats like PDF files
  • Data is recorded inconsistently
  • Records about the same person or thing lack a common unique identifier
  • Records are unknowingly duplicated

Analytics Blogs

Here’s five data and analytics trends we expect to see more of in public sector analytics:

  1. Internet of Things (IoT)

IoT allows organisations to connect and integrate data from various devices, and automatically apply analytics to them, reducing time to action, and improving understanding of what interventions will help service users.

With significant use of personal devices such as smartwatches that collect medical data, analysts can assess patients’ risk of health decline in real time.

  1. Predictive Analytics

Organisations can embed predictive algorithms to forecast demand and provide an evidence base to understand where and when to best deploy resources to optimise outcomes and maximise return on investment.

  1. Augmented analytics

Augmented analytics can generate the insights needed for evidence-based decision-making at all levels across organisations. Powered by Machine Learning (ML) and Artificial Intelligence (AI), augmented analytics can provide real-time, easily consumable data and contextual suggestions for relevant insights.

  1. Synthetic data

Synthetic data is artificially generated by computer programmes and algorithms instead of real-world events. This has the significant benefit of eradicating any personally identifiable data, meaning organisations will use it to undertake advanced analysis and enhanced simulation modelling on datasets without having to overcome data protection and information governance constraints.

  1. Conversational AI and Natural Language Processing

Natural Language Processing (NLP) and Conversational AI enable organisations to easily analyse any unstructured text data for trends and insights that are hard to notice with the human eye.