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Fully discuss the technique that will be used to analyse the text provided. Explain the process in a step-by-step approach

MARKING RUBRIC – SOE11446 - Data Analysis for Business Decision-making

SOE11446

Assignment 2: Report

	SCALES
CRITERIA and WEIGHTING	FAIL GRADES F1-F6	PASS GRADES P1-P5	DISTINCTION GRADE D1-D5
Question 1. 20% Discussion of appropriate technique (LO1)	The answer shows little evidence or understanding of qualitative analysis.	The answer shows a sound understanding of qualitative data analysis and an appropriate route has been identified.	The answer shows a comprehensive grasp of qualitative data analysis and excellent justification of the rationale of choice is evident.
2. Question 2. 40% Analysing transcripts (LO3)	There is a poor or no understanding of the necessary actions in relation to the analysis of the transcripts.	The analysis has been completed to a sound level with a clear understanding of the analysis technique.	The analysis has been completed to an excellent level with a clear understanding of the analysis technique and interpretation of the data.
3. Question 3. 40% Critically discussion findings (LO4)	Absent or poor understanding shown when interpretating the findings.	Mostly correct with some critical analysis evident. Generally sound evaluation and interpretation present.	All aspects covered in the document which demonstrates a strong level of evaluation and critical interpretation.

 Expert Guidance

1. Understanding Qualitative Data

• Definition: Qualitative data refers to non-numeric information that can capture the complexity of human behaviour, perceptions, and motivations. This data is often gathered through interviews, focus groups, observations, and open-ended survey responses.
• Purpose: In business decision-making, qualitative data is invaluable for understanding customer experiences, employee satisfaction, market trends, and more. Unlike quantitative data, which provides numerical trends, qualitative data offers insights into the why behind those trends.

2. Key Steps in Qualitative Data Analysis

a) Data Collection

• This involves gathering data through methods like interviews, surveys, focus groups, or ethnographic studies.
• For this assignment, ensure your data is relevant to the business problem at hand. You may need to transcribe interviews or code survey responses if they are in text format.

b) Data Preparation

• Transcription: If you have audio or video data, you will need to transcribe it to create a text-based document for analysis.
• Data Familiarisation: Read through the data several times to get a sense of emerging themes, patterns, and key points.

c) Coding

• Definition: Coding is the process of labelling sections of the data that relate to specific themes or ideas.
• Approach: You can use two types of coding:
  • Open Coding: This involves identifying and labelling every significant section of data.
  • Axial Coding: Once initial codes are developed, group them into larger categories or themes.
• Tools: If permitted by your course, software like NVivo or Atlas.ti can help you code and organise qualitative data more efficiently.

d) Theme Identification

• Once the data is coded, your next task is to identify patterns or themes. This is often done by grouping codes into broader categories. For example, if you’re analysing customer feedback, common themes might include customer service, product quality, or price perception.
• Tip: Look for both explicit themes (what is directly stated) and latent themes (what is implied or suggested by the data).

e) Interpretation

• Here you’ll provide meaning to the themes you’ve identified. What do these patterns tell you about the business problem or decision-making process?
• Link your findings to relevant business theories or models. For instance, if the data reveals customer dissatisfaction, you might refer to customer relationship management (CRM) theories to explain the impact on long-term business success.

3. Writing the Assignment

a) Introduction

• Clearly outline the purpose of your analysis. What business decision or problem are you addressing? What methods did you use to gather qualitative data?

b) Literature Review

• Summarise relevant literature on qualitative data analysis in business decision-making. Discuss the importance of qualitative insights in understanding complex human behaviours that affect business outcomes.

c) Methodology

• Provide a detailed explanation of how you collected and analysed the data. Describe your coding process and how you identified themes. Be sure to justify why qualitative analysis is appropriate for your business problem.

d) Findings

• Present the key themes and patterns that emerged from your data. Use direct quotes or examples from your data to illustrate these findings.

e) Discussion

• Interpret the findings in the context of your business problem. How do these insights help in making informed business decisions? Relate your interpretation to the theories or models discussed in the literature review.

f) Conclusion and Recommendations

• Summarise your main findings and discuss their implications for the business decision at hand. Offer practical recommendations based on your analysis. For example, if your data suggests customer dissatisfaction with pricing, you could recommend a pricing strategy review.

g) References

• Ensure you reference all the academic sources you consulted, following the required citation style (e.g., Harvard, APA).