VIFM - Virginia Institute of Finance and Management
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Analytics
Intermediate

DATA-DRIVEN DECISION MAKING

2–5 daysENclassroom · virtual

Course overview

The Data-Driven Decision-Making course is designed to provide professionals with practical skills to harness data for strategic business decisions. Participants will learn how to effectively collect, analyze, and interpret data using tools like Excel to uncover trends, identify opportunities, and solve business problems. The course focuses on practical techniques for data analysis, visualization, and reporting, enabling participants to communicate insights clearly and support decision-making processes. By developing these critical skills, attendees will be better equipped to contribute to their organization's success through informed, evidence-based decisions.

Target audience

This course is intended for professionals seeking to improve their data-driven decision-making capabilities. This includes: Business Analysts, Marketing Managers, Financial Analysts, Operations Managers, Product Managers, Project Managers

Course objectives

  • Analyze data using Excel to identify patterns and trends.
  • Interpret data to support business decision-making.
  • Create data visualizations to present findings effectively.
  • Develop structured approaches to problem-solving using data.
  • Build dynamic data models in Excel for decision support.
  • Summarize data insights in clear and actionable reports.
  • Apply data-driven techniques to improve business strategies

Target competencies

Data Analysis
Data Interpretation
Visualization
Decision-Making Techniques
Reporting
Modeling

Course methodology

The course will be delivered through interactive lectures, tool demonstrations, practical exercises, and hands-on sessions focused on using Excel for data analysis.

Course outline

INTRODUCTION TO DATA-DRIVEN DECISION MAKING

  • Importance of data in modern business decision-making.
  • Overview of data-driven decision-making frameworks.
  • Types of data and key concepts in data analytics.
  • Understanding data governance and quality management basics.

DATA COLLECTION AND CLEANING USING EXCEL

  • Methods for effective data collection.
  • Techniques for cleaning and organizing data.
  • Handling missing data and outliers.
  • Data preparation for analysis in Excel.

DATA ANALYSIS TECHNIQUES IN EXCEL

  • Descriptive statistics and their use in decision-making.
  • Using pivot tables and charts for data analysis.
  • Applying data filters, sorting, and conditional formatting.
  • Conducting trend analysis and identifying correlations.

DATA VISUALIZATION AND REPORTING

  • Principles of effective data visualization.
  • Creating charts and graphs in Excel (bar, line, pie, scatter, etc.).
  • Best practices for designing informative and compelling reports.
  • Communicating insights.

BUILDING DATA MODELS FOR DECISION SUPPORT

  • Introduction to spreadsheet modeling for business scenarios.
  • Creating dynamic models using Excel formulas and functions.
  • Sensitivity analysis and scenario planning.
  • Developing dashboards for real-time decision support.
  • Support prioritization of needs based on business value and urgency

TECHNIQUES FOR DATA-DRIVEN DECISION MAKING

  • Pareto analysis model in decision-making.
  • Structuring decision-making processes with data inputs.
  • Balancing quantitative and qualitative data for decisions.
  • Prioritizing actions based on data insights.

ADVANCED EXCEL FUNCTIONS FOR DECISION MAKING

  • Utilizing advanced Excel functions (e.g., VLOOKUP, INDEX-MATCH).
  • Implementing What-If Analysis tools (Goal Seek, Data Tables, Solver).
  • Automating data analysis with Excel macros.
  • Techniques for enhancing productivity in Excel.

COMMUNICATING DATA-DRIVEN INSIGHTS

  • Best practices for summarizing data findings in reports.
  • Preparing compelling presentations with data insights.
  • Aligning data-driven insights with business objectives.
  • Building consensus and driving decisions based on data.

DATA-DRIVEN PERFORMANCE MEASUREMENT

  • Identifying key performance indicators (KPIs) and metrics.
  • Using Excel to track and monitor performance data.
  • Analyzing performance trends to inform decision-making.
  • Linking performance metrics to strategic goals.

ENSURING SUSTAINABILITY OF DATA-DRIVEN PRACTICES

  • Data-driven decision-making in organizational culture.
  • SOP for data analysis.
  • Regularly updating and maintaining data models and dashboards.
  • Continuous improvement through feedback and iterative analysis.

Want to run this for your team?

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