Analysing and Evaluating Information (LC 2027) (Leaving Cert Business): Revision Notes
Analysing and Evaluating Information
When conducting business research, gathering data is only the first step. The real value comes from properly analysing and evaluating this information to draw meaningful conclusions that can inform business decisions.
Understanding analysis and evaluation
Core Definitions:
Analysis involves examining data and information systematically to identify patterns, trends, and relationships. This process helps you break down complex information into manageable parts that can be understood and interpreted.
Evaluation goes further by measuring the success or value of your findings against specific criteria. This helps determine whether your research objectives have been met and what the implications are for business practice.
The key action verbs you should focus on are:
- Analyse: Break down and examine the data
- Appraise: Assess the value and quality of information
- Evaluate: Judge the effectiveness against set criteria
- Synthesise: Combine different pieces of information to form conclusions
The four-step analysis framework
When analysing any data set, use this systematic approach to ensure thorough examination:
The TIME, TREND, WHY, THEORY Framework
This four-step approach ensures comprehensive analysis of any business data:
TIME - Identify the year or month when the statistics were collected. This provides essential context for understanding the data and comparing it with other time periods.
TREND - Determine what happened to the data - did it increase, decrease, or remain stable? Look for patterns over time and quantify the changes where possible.
WHY - Provide a possible reason explaining why these changes might have occurred. Consider external factors, market conditions, or business decisions that could have influenced the results.
THEORY - Link your findings to business theory you have studied. This demonstrates your understanding of how real-world data connects to academic concepts and business principles.
Presenting your findings effectively
Once you have analysed your data, you need to communicate your findings clearly. Your presentation method will depend on your audience and the type of information you want to convey.
The three main communication methods each have distinct characteristics:
Oral communication
This involves speaking directly to share information, such as in meetings, presentations, or phone calls.
Communication Method Analysis: Oral Communication
Advantages:
- Fast and immediate delivery
- Allows for instant clarification and feedback
- Personal and engaging interaction
Disadvantages:
- No permanent record created
- Information can be misunderstood or forgotten
- Requires everyone to be available simultaneously
Written communication
This uses text-based methods to transfer information, including reports, emails, and letters.
Communication Method Analysis: Written Communication
Advantages:
- Provides a permanent record for future reference
- Allows time for careful consideration and planning
- Can be reviewed and referred to later
Disadvantages:
- Slower process than oral communication
- Less personal interaction and engagement
- Can be misinterpreted without immediate clarification
Visual communication
This relies on images, graphics, and pictures to convey information, such as charts, posters, and social media content.
Communication Method Analysis: Visual Communication
Advantages:
- Easy to understand quickly and efficiently
- Highly effective for presenting numerical data
- Memorable and engaging for audiences
Disadvantages:
- May need additional explanation or context
- Cannot convey complex details independently
- Requires design skills and technical knowledge
Choosing the right visual presentation
Different types of data require different visual presentation methods to be most effective:
Pie charts
Best for showing parts of a whole where you want to display percentages or proportions. Each segment represents a different category, and the entire circle equals 100%.
Histograms
Ideal for displaying frequency data and showing the distribution of continuous variables. The height of each bar represents how often values occur within specific ranges.
Pictograms
Effective for making data more engaging and accessible, especially when presenting to non-technical audiences. Uses symbols or images to represent quantities, making statistics more relatable.
Crafting your conclusions
When presenting your analysis conclusions, use clear and confident language that demonstrates your understanding. Your conclusions should be supported by evidence from your research and linked back to your original objectives.
Essential Conclusion Requirements:
Every conclusion you present should be backed up with specific examples, facts, or information from your investigation. This evidence-based approach strengthens your analysis and demonstrates thorough research methodology.
Remember that every conclusion should be backed up with specific examples, facts, or information from your investigation.
Key Points to Remember:
- Use the TIME, TREND, WHY, THEORY framework to analyse any data systematically
- Choose your communication method based on your audience and the type of information you're presenting
- Visual presentation methods should match the type of data you're displaying
- Always support your conclusions with evidence from your research
- Link your findings back to business theory to demonstrate deeper understanding