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Graduate School USA

Decision Support Analytics Course

via Graduate School USA

Overview

Follow a structured, five-step approach to data-driven decision-making. Participants gain skills in analysis, data sourcing, and communicating insights to support agency goals.

Syllabus

Module 1: Management Reform Drivers

  • Explore the legislative and executive changes that drive the need for stronger analytics in federal decision-making.
  • Understand the evolution of federal performance expectations and accountability standards.
  • Examine the roles of CFOs and analysts in navigating performance management and resource allocation.
  • Identify major management laws and executive initiatives impacting federal agencies.

Module 2: Structured Approach for Conducting Analysis

  • Learn a five-step, structured framework for analysis in a federal environment.
  • Connect analytical methods to management questions in budgeting, performance, and finance.
  • Compare structured agency analysis to performance audit methodology.
  • Use a design matrix to document, plan, and track analytical activities.

Module 3: Step 1 – Defining the Questions That Drive Analysis

  • Develop descriptive, normative, and impact-driven analytical questions.
  • Apply critical thinking and stakeholder alignment in formulating questions.
  • Differentiate between overarching and subordinate questions.
  • Organize questions into eight categories, including program impact and policy design.

Module 4: Step 2 – Identifying the Data

  • Assess data quality based on reliability, verifiability, relevance, and consistency.
  • Evaluate accessibility vs. availability to set realistic project timelines.
  • Compare data from people vs. records and understand the pros/cons of each.
  • Ensure identified data effectively supports analytical questions.

Module 5: Step 3 – Collecting the Data

  • Understand methods for gathering data from systems, reports, people, and surveys.
  • Use agency performance and accountability reports and financial statements as data sources.
  • Consider sampling methods and limitations of data used in analysis.
  • Recognize internal and external data constraints in planning and reporting.

Module 6: Step 4 – Analyzing the Data

  • Apply analytical methods to descriptive, normative, and impact-based questions.
  • Use content, trend, statistical, and benchmarking analyses appropriately.
  • Understand how to use logic models and causal relationships in data interpretation.
  • Select suitable analytical techniques based on the scope and purpose of analysis.

Module 7: Step 5 – Presenting the Results

  • Communicate findings through written reports and oral briefings.
  • Structure reports to clearly answer questions, show methods, and support recommendations.
  • Incorporate visual aids and summary sections to clarify results for decision-makers.
  • Demonstrate sufficiency, relevance, and appropriateness of evidence in communication.

Module 8: Case Study

  • Apply the full five-step analysis model to a realistic agency scenario.
  • Assess internal controls within a Department of Public Health and Safety case study.
  • Practice defining questions, identifying and collecting data, and reporting recommendations.
  • Produce an executive summary including condition, criteria, cause, and effect findings.

Taught by

Alan B. Robinson, Kent Miller, and Alan McCain

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