This course empowers professionals to make better business decisions through systematic use of data and analytics. Participants will learn frameworks for incorporating data into decision processes while understanding the limitations and biases that can affect judgment. The curriculum covers quantitative and qualitative data analysis techniques, hypothesis testing, and evidence-based decision frameworks. Through practical exercises, learners will develop the ability to transform data into actionable insights that drive organizational success.
Data-Driven Decision Making
Data Analytics and Business Intelligence
October 25, 2025
Introduction
Objectives
Key learning objectives include:
- Apply structured frameworks for data-driven decisions
- Identify and mitigate cognitive biases in decision-making
- Utilize hypothesis testing for business problems
- Interpret analytical results for decision support
- Balance quantitative and qualitative factors
- Communicate data-driven recommendations effectively
- Implement decision monitoring and feedback systems
- Evaluate decision outcomes and learn from results
Target Audience
- Managers and team leaders
- Business analysts and strategists
- Project managers
- Department heads and executives
- Marketing and product managers
- Operations and supply chain managers
Methodology
The course uses a combination of case studies, group discussions, and practical exercises to develop decision-making skills. Real-world business scenarios from various industries provide context for applying data-driven approaches. Group activities focus on collaborative decision-making processes, while individual exercises build personal analytical capabilities. Mini-case studies present specific decision challenges, and syndicate discussions explore different perspectives and solutions.
Personal Impact
- Enhanced critical thinking and analytical skills
- Improved ability to interpret and use data effectively
- Reduced influence of cognitive biases on decisions
- Stronger confidence in making data-supported choices
- Better communication of rationale behind decisions
- Increased awareness of decision quality factors
Organizational Impact
- More consistent and rational decision-making processes
- Improved alignment between decisions and strategic goals
- Reduced risk through evidence-based approaches
- Enhanced organizational learning from decisions
- Better resource allocation based on data insights
- Increased accountability in decision processes
Course Outline
Unit 1: Foundations of Data-Driven Decisions
Decision Making Fundamentals- Types of business decisions and their data needs
- Data-driven vs intuition-based approaches
- Decision frameworks and methodologies
- Role of analytics in modern organizations
Unit 2: Cognitive Biases and Critical Thinking
Understanding Biases- Common cognitive biases in decision-making
- Statistical misconceptions and pitfalls
- Critical thinking techniques
- Evidence evaluation methods
Unit 3: Data Analysis for Decisions
Analytical Techniques- Descriptive analytics for context setting
- Diagnostic analysis for root cause identification
- Predictive modeling for future outcomes
- Prescriptive analytics for action planning
Unit 4: Decision Frameworks and Tools
Structured Decision Making- Hypothesis-driven approach
- Cost-benefit analysis frameworks
- Scenario planning and analysis
- Risk assessment and management
Unit 5: Implementation and Communication
Action Planning- Translating insights into actions
- Stakeholder alignment strategies
- Change management considerations
- Implementation roadmap development
- Data storytelling techniques
- Visualization for decision support
- Executive summary development
- Presentation skills for different audiences
Unit 6: Monitoring and Evaluation
Decision Quality Assessment- Key performance indicators for decisions
- Feedback loop establishment
- Continuous improvement processes
- Learning from decision outcomes
Ready to Learn More?
Have questions about this course? Get in touch with our training consultants.
Submit Your Enquiry