Effective use of business data, information technology and various analytical methods helps managers and employees gain improved insight into their business issues and helps make better informed decisions. Tools and techniques presented in this programme can be applied across many areas in a wide variety of organisations to improve stakeholder satisfaction, enhance return on investment, mitigate business risks and improve planning.
The Business Data Collection, Analysis and Presentation training course covers the foundational knowledge necessary to collect reliable business data and conduct comprehensive analysis to help maximise organisational value. The training course is focused on the enhancement of essential knowledge and skills and equips participants with a toolbox of ideas and methodologies for effective data collection and analysis.
Participants on the Business Data Collection, Analysis and Presentation training course will develop the following competencies:
- Develop critical thinking and structured problem-solving skills
- Identify business problems and analyze organizational needs
- Design and conduct effective business data collection methods
- Analyze and interpret business data for strategic decision-making
- Conduct feasibility studies for business initiatives
- Solve management problems using analytical tools and frameworks
- Influence stakeholders through persuasive communication and presentation skills
Target Audience
- Business executives and decision-makers
- Data analysts and strategic planners
- Research and development teams
- Risk management and corporate planning professionals
- Marketing and business development professionals
- Anyone looking to enhance their skills in data analysis and business decision-making
Training Outline :
DAY 1 : Introduction to Key Concepts in Business Decision-Making
- undamentals of business decision-making
- Decision-making processes and critical thinking
- Data vs. information vs. knowledge
- Distinguishing facts, statistics, rumors, and fiction
- Understanding business problems and opportunities:
- Identifying business challenges
- Setting clear objectives
- Defining problems and analyzing key priorities
- Recognizing assumptions, constraints, and influencing factors
DAY 2 : Collecting Relevant and Reliable Business Data
- The role of data in decision-making
- Importance and value of business research
- Business research process and design
- Data sources and collection methods
- Sampling techniques and analysis
- Developing effective research proposals
- Gathering and organizing relevant business data
- Designing surveys and questionnaires
- Crafting the right questions for meaningful insights
Day 3 : Data Validation and Analysis Techniques
- Understanding different types of business data
- Ensuring data reliability and validity
- Introduction to decision models and spreadsheet analysis
- Visualizing and exploring business data
- Data analysis methods and essential business statistics
- Using charts and frequency distributions
- Creating pivot tables for data analysis
- Applying descriptive statistics in business decisions
- Understanding measures of central tendency and variability
Day 4 : Probability Distributions and Data Modeling
- Role of probability in business decision-making
- Statistical decision theory and its applications
- Business applications of probability distributions
- Correlation and regression analysis for business insights
- Diagnostic and analytical models for data-driven decisions
- Fundamentals of option analysis and decision heuristics
- Payoff tables and decision-making under certainty, risk, and uncertainty
- Decision trees and utility theory for strategic business choices
Day 5 : Persuasive Business Communication and Data Presentation
- A structured framework for persuasive communication: AIM-FOCUS
- Importance of AIM (Audience, Intent, Message) in business communication
- The need to FOCUS for clarity and impact
- Writing compelling and convincing business reports
- The art of influence through professional business presentations
- Case study application: Real-world business data analysis