A note on qualitative memoing for MBA students

A note on qualitative memoing for MBA students

 

On 6 main ideas of qualitative memoing in qualitative research.

Qualitative memoing is best understood as a running analytic practice that helps researchers think with the data rather than just about it. Here are 6 main ideas:

1.    Reflexivity — memos help you examine your own assumptions, biases, and role in shaping interpretation.

2.    Analytic thinking — they capture your emerging interpretations, hunches, and questions during coding and analysis.

3.    Constant comparison — memos support comparing new data with earlier data, codes, and categories to refine ideas.

4.    Theory building — they help turn observations into concepts, patterns, and eventually theoretical arguments.

5.    Decision trail — memos record methodological choices and analytical steps, creating an audit trail of how conclusions were reached.

6.    Communication and continuity — they preserve insights over time and make it easier to share and revisit analysis across the project.

 

To illustrate your ideas further with the MBA research theme of "to evaluate the worries of job insecurity with regard to the impact of AI on the project management employees in ABC telecom company in Hong Kong based the staff interview transcripts and structured observation at the company's office".

Here’s how those six ideas of qualitative memoing can be illustrated concretely within your MBA research theme:

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1. Reflexivity

In memos you might write reflections such as:

·        “Am I over‑interpreting job‑insecurity talk because I am worried about AI in my own sector?”

·        “My background in project management makes me more sensitive to how AI tools are framed as ‘efficiency promoters’ rather than ‘replacement tools’.”

This helps you track how your role as an academic and your own anxieties shape readings of expressions like “AI will take our jobs” or “we’ll be monitored more closely.”

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2. Analytic thinking

After each interview or observation session, you could write a short memo that:

·        Notes recurring phrases such as “we feel like we’re constantly under surveillance with AI‑driven dashboards,” or “AI‑based tools are forcing us to change how we plan.”

·        Jots down early hunches, e.g., “Job‑insecurity appears stronger among long‑tenured project managers than among younger staff,” or “‘AI monitoring’ is more worrying than ‘AI as a tool’.”

These memos push you from description to explanation.

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3. Constant comparison

In a memo you might compare:

·        How junior project officers versus senior project managers describe AI‑related changes.

·        Whether interview statements about workload (“AI‑based tracking makes me work harder”) align with what you see in structured observation (e.g., frequent checking of dashboards, overtime, or visible stress).

For example, a memo might say: “Interviewee A feared AI would replace routine tasks, whereas Interviewee B explicitly linked AI to performance pressure and fear of contract non‑renewal, which matches my observation of tighter reporting cycles.”

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4. Theory building

Memos can help you build concepts like:

·        AI‑induced surveillance stress: the idea that AI‑driven performance tracking heightens perceived job insecurity.

·        Technological boundary‑spanning work: the shift where project managers increasingly need to manage both AI tools and human teams.

You might write a memo that links interview quotations (“we’re always on the radar now”) with observation notes (e.g., managers checking dashboards before team meetings) to begin formulating a tentative conceptual framework.

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5. Decision trail

In your memos you can document:

·        How you decided which themes to label “job insecurity” versus “adaptation” or “skill development.”

·        Why you combined certain interview quotes with specific observation episodes when constructing a case‑study section.

For example: “I decided to treat ‘fear of being replaced by AI‑based scheduling tools’ as a core indicator of job‑insecurity, distinct from ‘fear of being left behind by new tools’ (which I coded as skill‑gap anxiety).” This creates an audit trail for your analytic choices.

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6. Communication and continuity

Across time, memos help you:

·        Keep consistent focus on the core question: “How AI‑related changes affect job‑insecurity among project‑management staff.”

·        Revisit earlier interviews confidently when you collect follow‑up data or feedback, because the memo states: “This interview supports the earlier pattern of fear around AI‑based monitoring, but contradicts the assumption that younger staff are less anxious.”

For supervisors or examiners, these memos can later be excerpted or summarized to show how your analysis evolved from interview transcripts and structured observation into a coherent MBA‑level discussion.

Relevant links: on ALRA 2026.

A collection of blog notes on using chatgpt for research purpose.