Management and Leadership

Data-Driven Decision Making with Analytics

• Traditional Classroom: 1-day
• Virtual Instructor-led: Two 3-hour sessions

In today’s dynamic business environment, decisions must be made quickly and with confidence, guided by reliable data rather than assumptions. Data Driven Decision Making (DDDM) equips professionals with the skills to gather, analyze, and interpret data to solve problems, mitigate risks, and drive meaningful business outcomes. This one-day interactive course provides a simple, practical framework for making informed decisions that balance data insights with organizational priorities.

Participants will learn to apply problem-solving techniques, identify and assess risks, and design a basic analysis plan to support sound decision-making. The course also explores how analytics play a pivotal role in uncovering patterns, predicting outcomes, and comparing alternatives. Through guided activities, participants will practice evaluating decisions against business goals while considering potential risks and mitigation strategies.

This training is ideal for analysts, team leaders, managers, and professionals who are involved in business analysis, operations, finance, marketing, project management, or any field where data is essential for success.

Target Audience

This course is ideal for:

• Business analysts, data analysts, and reporting specialists
• Managers and leaders seeking to incorporate analytics into strategic decisions
• Project managers and operations professionals responsible for risk assessment and mitigation
• Professionals across industries interested in strengthening their problem-solving and decision-making skills

Learning Objectives

• Apply a step-by-step framework for data-driven decision making.
• Define problems clearly and identify root causes using structured techniques.
• Develop a basic analysis plan to organize data collection and evaluation.
• Recognize risks and create actionable risk mitigation strategies.
• Use analytics to compare and evaluate decision alternatives.
• Make decisions with confidence and communicate rationale effectively to stakeholders.

Course Outline

Module 1: Introduction to Data-Driven Decision Making

• Purpose and Benefits of Data-Driven Decisions
• Common Pitfalls of Intuition-Based Decisions
• The DDDM cycle: Define → Analyze → Decide → Act → Review=
• The Analytics Process Model (APM) for DDDM
• Framework for DDDM
• Case Study: A Quick Group Exercise on Intuitive vs. Data-Driven Decision Outcomes

Module 2: Problem Solving Foundation

• Structured Problem-Solving Steps:
  • Identify and Define the Problem
  • Analyze Root Causes (e.g., 5 Whys, Fishbone diagram)
  • Establish Success Criteria
• Activity: Practice Defining a Problem and Identifying Potential Causes
• Linking Problem Solving to DDDM – Why Clarity Is Critical Before Data Analysis Begins

Module 3: Risk Identification and Mitigation

• Types of Risks: Strategic, Operational, Financial, Reputational
• Simple Risk Assessment Process:
  • Identify Potential Risks
  • Analyze Likelihood and Impact (Risk Matrix)
  • Prioritize Risks
  • Develop Mitigation Strategies
• Group Exercise: Risk Mapping for a Sample Scenario
• Integrating Risk Assessment into Decision Making

Module 4: Role of Analytics in Decision Making

• The Value of Analytics: Descriptive, Diagnostic, Predictive, and Prescriptive Analytics
• Key Steps in Creating an Analysis Plan:
  • Define the Decision Objective
  • Identify Relevant Data Sources
  • Plan for Data Collection and Preparation
  • Select Appropriate Analysis Methods
  • Document Assumptions and Limitations
  • Popular and Effective Analytics and Financial Techniques for DDDM
• Example: Translating a Business Question into an Analytical Plan
• Hands-on Activity: Building a Simple Analysis Plan for a Real-World Scenario

Module 5: Generating and Evaluating Alternatives

• Techniques for Brainstorming and Generating Options
• Criteria for Evaluating Alternatives:
  • Cost/Benefit
  • Risk Exposure
  • Alignment with Goals
  • Data Support and Confidence Level
• Decision Matrices and Scoring Tools
• Activity: Compare and Evaluate Alternatives Using Provided Data

Module 6: Decision Implementation and Monitoring

• Creating an Action Plan for Implementation
• Monitoring Outcomes and Learning from Results
• Continuous Improvement: Review and Feedback Loop

Module 7: Communicating Results and Gaining Buy-In

• Planning the Communication
• Defining the Communication Goal
• Assessing the Audience
• Presenting Findings, Implications and Recommendations

Module 8: Wrap-Up and Action Planning

• Recap of DDDM Framework and Key Steps
• Group Reflection: How Participants Will Apply These Tools in Their Roles
• Q&A and Closing Discussion

MDV1016 Course Code