Lecture on the metaphor of “be water” from Bruce Lee: for MBA students doing dissertation projects

Lecture on the metaphor of “be water” from Bruce Lee: for MBA students doing dissertation projects

 

The metaphor of "be water" from Bruce Lee, based on my findings, means:

1. No fixed shape: Water takes the shape of whatever holds it, whether a cup, a bottle, or a teapot. You should adjust to your environment instead of fighting it.

2. Flow or crash: Water can move smoothly as a gentle stream or strike with the raw power of a tidal wave. You choose peace or strength depending on what the moment needs.

3. Empty mind: You must clear your thoughts of ego and preset notions so you can see reality clearly and respond properly.

Could you translate these 3 core ideas into some concrete how-to advices to my part-time MBA students doing their dissertation projects?

 

Here’s how you can translate Bruce Lee’s “be water” philosophy into concrete, dissertation-focused advice for your part‑time MBA students.

1. No fixed shape → Adapt your design to the container (your context)

Water becomes the cup, bottle, or teapot. For a dissertation, the “container” is your research question, data access, time, and organisational constraints.

Practical how‑to:

• Start with a “minimum viable dissertation” (MVD):
  Define the smallest credible study that still answers your core question (e.g., one case, one sector, one method). Treat everything else as optional extensions if time permits.
• Design for constraints, not ideals:
  When you draft your proposal, explicitly list:
• What data you can realistically get (e.g., one firm, 10–15 interviews, internal reports).
• What methods you can actually execute alongside work/family (e.g., 12 interviews + document analysis instead of 30 interviews + survey).
  Then shape your methodology around those realities instead of an “ideal” design you can’t deliver.
• Build in “if–then” contingency plans:
  For example:
• If access to senior managers is denied, then shift to mid‑level managers + internal documents.
• If survey response rate < 20%, then treat it as a pilot and lean more on qualitative data.
  Write these into your methodology chapter as “limitations and adaptations” rather than pretending the design is perfect.
• Iterate your question as you learn:
  After your first 3–5 interviews or initial data scan, ask: “Does my question still fit the data I can actually get?” If not, refine the wording or scope so the question matches the “container” you really have.

The skill you’re teaching them: designing a study that fits the real world, not a textbook ideal.

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2. Flow or crash → Choose gentle persistence or focused force, depending on the moment

Water can be a gentle stream or a tidal wave. In a dissertation, this is about when to keep moving smoothly and when to push hard.

Practical how‑to:

• Default mode: flow (steady, low‑friction progress)
  Encourage habits like:
• 30–45 minutes of writing or reading most days, rather than heroic weekend marathons.
• “Next small step” thinking: instead of “finish literature review”, aim for “summarise 3 papers on X” or “draft 300 words on Y”.
• Using templates (e.g., standard headings for lit review, methods, findings) so they always have a structure to “flow” into.
• Crash mode: concentrated sprints for key milestones
  Identify 3–4 “crash points” in the timeline where they must apply focused force, e.g.:
• Finalising the proposal
• Completing data collection
• Writing the first full draft
• Final edits before submission
  For these, plan 1–2 week sprints with:
• Clear daily targets (e.g., 800–1,000 words/day, or 3–4 interviews/week).
• Protected time blocks (e.g., early morning or weekend slots agreed with family/colleagues).
• Minimal distractions (turn off notifications, use writing timers).
• Match effort to bottleneck type:
• If the bottleneck is access/data → use “flow”: many small asks, multiple channels, alternative sources.
• If the bottleneck is procrastination/perfectionism → use “crash”: time‑boxed sprints, “ugly first draft” rule, accountability partner.
• Teach them to recognise rigidity:
  When they feel stuck for more than a week on the same issue (e.g., “I can’t start writing until my theory is perfect”), prompt:
• “What’s the smallest piece you can write or analyse today?”
• “If you had to submit something in 48 hours, what would you include?”
  This shifts them from rigid thinking to adaptive action.

The skill you’re teaching them: strategic pacing—knowing when to keep moving and when to push hard.

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3. Empty mind → Clear preset notions so you can see the data and feedback clearly

“Empty your mind” means suspending ego, pet theories, and fixed ideas so you can respond to what the evidence and supervisors actually say.

Practical how‑to:

• Separate “working hypotheses” from “identity”:
  Have students write:
• “My current working hypothesis is…”
• “I am willing to change this if the data shows…”
  This frames their ideas as provisional, not personal.
• Use “surprise logs” during data collection and analysis:
  For each interview, dataset, or article, ask them to note:
• One thing that surprised them.
• One way it challenges their initial assumption.
  This trains them to look for disconfirming evidence, not just confirmation.
• Build structured feedback loops:
• After each supervision meeting, require a ½–1 page “what I heard / what I will change” memo.
• In class, do short exercises where they summarise a peer’s critique of their project in 3 bullets, then list 2 concrete changes they will make.
  This makes “empty mind” operational: listen, reflect, adjust.
• Teach them to spot “rigid language”:
  When they say things like:
• “My theory is that X causes Y, and I will prove it.”
• “I already know what the findings will be.”
  Reframe to:
• “I expect X may influence Y, but I’m open to other patterns.”
• “I will test whether X relates to Y, and report whatever the data shows.”
• Normalise iteration as professionalism, not failure:
  Share examples (anonymised) of good dissertations that changed question, method, or theory mid‑stream because the data demanded it. Emphasise: adapting to evidence is a sign of research maturity, not weakness.

The skill you’re teaching them: intellectual humility and responsiveness to evidence.

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Turning it into a simple framework you can give students

You might present “Be Water” as a three‑question checklist they revisit each month:

1.    Shape:

o   “Given my current time, data access, and constraints, what is the most realistic version of this dissertation?”

2.    Flow or crash:

o   “This week, do I need steady flow (small daily steps) or a focused crash (a sprint on a key milestone)?”

3.    Empty mind:

o   “What assumption am I holding too tightly? What evidence or feedback am I ignoring?”

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