Day 1: From Business Questions to Analytical Focus

Framing Analytical Questions

• Required decision and analytical purpose
• Convert problems into measurable questions
• Identify key influencing variables
• Form testable analytical hypotheses

Defining Information Needs

• List inputs required for decisions
• Separate essentials from supporting details
• Required level of detail
• Schedule collection of core inputs

Defining Analytical Scope

• Analytical scope and boundaries
• Set the analysis time period
• Exclude data beyond scope
• Specify required analytical outputs

Day 2: Building Trust in the Data Foundation

Inventorying Data Sources

• Available internal data records
• Assess available external datasets
• Document owners of data sources
• Required source refresh frequency

Assessing Source Reliability

• Core source accuracy and reliability
• Review freshness of available data
• Required field completeness criteria
• Known source limitations register

Profiling Data Structures

• Core fields and variables
• Inspect data types being used
• Relationships across connected data tables
• Detect unusual data values

Day 3: Reading Performance Through Meaningful Measures

Calculating Descriptive Metrics

• Calculate central tendency measures
• Measure dispersion across values
• Minimum and maximum data values
• Compare metrics across categories

Interpreting Result Drivers

• Factors linked with performance outcomes
• Compare strength of influencing factors
• Distinguish correlation from causation
• Form defensible result interpretations

Building KPI Architecture

• Define primary measurement levels
• Link indicators with targeted outcomes
• Approved calculation formula reference
• Assign key monitoring owners

Day 4: Designing Dashboards That Guide Attention

Planning Dashboard Interfaces

• Primary dashboard audience profile
• Prioritize information by importance
• Allocate space for key indicators
• Set visual reading sequence

Building Visual Hierarchy

• Order messages by importance
• Highlight the most influential indicators
• Reduce distraction among visual elements
• Guide attention toward conclusions

Designing Filters and Interactions

• Criteria for most useful filters
• Align interactions with analytical purpose
• Filtering option clarity for users
• Prevent confusing user interactions

Day 5: From Analysis to Executive Action

Analyzing Possible Scenarios

• Assumptions for each scenario
• Build optimistic and conservative cases
• Impact of input changes
• Compare potential decision outcomes

Designing Executive Recommendations

• Link recommendations to available evidence
• Define the required action
• Clarify expected recommendation impact
• State major constraints and risks

Preparing Executive Summaries

• Present the main message first
• Summarize the most important numbers
• Highlight required decisions clearly
• Avoid excessive technical detail

• Analyze a professional case highlighting challenges in Framing Analytical Questions
• Practical lab creating a workplace tool for Profiling Data Structures
• Use a group exercise to test decisions around Building Visual Hierarchy
• Simulate a situation requiring Preparing Executive Summaries in practice