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.
Overview
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