Public Sector

Analytics for the Public Sector

Government agencies are faced with running efficient business operations within their budgetary constraints, while providing the service levels the Public demands. The massive amounts of data residing in governmental agencies make it difficult to determine the optimal application of resources, assets and attention. Applying Predictive Analytics and Optimization techniques will help you see the future with more clarity and confidence, to put plans and strategies in place to manage effectively.

Fraud detection, Program integrity, and Compliance

  • Fraud detection: Identify past patterns, and apply statistical techniques to predict future fraud, waste and abuse. (Financial fraud, Transactional fraud, etc.)
  • Program integrity: Analyze, identify, and predict the critical success factors of programs, and establish plans to optimize these factors in the future.
  • Compliance: Analyze areas of past compliance and non-compliance to regulations, and determine the optimal success factors. Predict future compliance, and put mitigation plans in place where non-compliance is anticipated

Human Capital optimization

  • Improve resource allocation: Identify areas of inefficiency, and optimize future techniques to allocate resources to higher value, more strategic work
  • Employee satisfaction and retention: Analyze the factors that are positive and negative influences, and establish mitigation programs to maximize satisfaction and retention.
  • Reduce labor related costs: Analyze and predict improvement factors for employee related costs such as excessive sick days, injuries on the job, employee travel time/expenses, etc.

Health & Human Services

  • Caseworker utilization productivity: Predict patterns in caseworker workloads, and optimize their focus to maximize their efficiency
  • Fraud, waste and abuse: Identify and predict patterns of fraud, waste and abuse; and optimize program approaches to reduce these in the future<
  • Disease outbreak patterns: Identification of likely disease outbreak patterns, and prediction of future patterns
  • Sources of disease outbreaks: Identification of likely sources of disease outbreaks, and prediction of future sources

Financial operations

  • Revenue forecasting: Analyze revenue trends and improve your ability to forecast revenue. Predictions of revenue gaps in the future.
  • Revenue collections: Optimization and prioritization of revenue collections to increase efficiencies.
  • Spending optimization: Analyze the results of spending, and model optimum future spending and programs
  • Project and Program efficiencies: Identify success factors and inhibitors to optimize project and program priorities and efficiencies.

For more information on CGN's Business Analytics practice, contact Syamala Srinivasan at