Business Administration

Organizational Analysis Under Uncertainty

Faculty

Jeffrey Schatten, Washington and Lee University · schattenj@wlu.edu

Course

Managing Uncertainty

Level

Undergraduate, 200-level

Faculty Reflection

This assignment emerged from watching students struggle to distinguish between what they actually observed and what they thought organizations "should" do according to theory. I wanted them to develop the foundational skill of evidence-based reasoning—seeing what's actually there before explaining it. The three-stage structure ensures they build genuine observational skills before layering on conceptual frameworks, and only then use AI to refine communication. Students consistently report that this constraint makes them notice behavioral details they would have missed if they'd gone straight to interpretation.

What Students Create

An organizational analysis paper examining how a student organization functions under uncertainty, anchored in one personally observed high-stakes moment and interpreted using concepts from Morgan Housel's Same As Ever.

Why This Assignment Matters

Students learn to distinguish between human behavior they can observe and theories they impose. By starting from authentic observation before interpretation, they develop the foundational skill of evidence-based reasoning—seeing what's actually there before explaining it.

Assignment Instructions

Pick an organization you can actually observe. Not one you read about—one you can watch in action. Could be your workplace, a sports team, a student organization, a family business, even your friend group planning something complicated.

Now watch. How do people actually work together? Who talks to whom? Where do decisions get made? What happens when there's conflict or confusion? Write 500-750 words describing exactly what you see. No analysis yet—that's Stage 2. Right now, just capture the reality in front of you.

AI Permissions

None. Zero. Not happening. This stage is about developing your own observational instincts. AI can't watch the world for you, and you can't build analytical skills on someone else's observations.

What Students Learn

How to watch closely without jumping to conclusions
The difference between description and interpretation
How to notice patterns in real organizational behavior

Examples

A golfer breaking down their own swing mechanics and practice habits
Communication patterns between doctors and patients in a physical therapy clinic
How a private equity team makes investment decisions under pressure
The way students really plan their schedules (versus how they think they do it)

WHY NO AI HERE?

Students need unmediated access to their own observations before introducing any analytical framework. If students use AI to "help reconstruct" events or "enhance" descriptions, they lose the authenticity of what they actually noticed in the moment. The goal is to preserve their unique vantage point as someone who was present.

WHAT WOULD BREAK?

If students could use AI in this stage, they'd unconsciously shift from describing what happened to describing what "should" have happened according to organizational theory. AI would smooth over the messy, contradictory, or surprising details that make the observation valuable. Students would lose the raw material that makes their interpretation genuinely grounded.

WHAT SURPRISES EMERGED?

Students often resist this constraint initially, wanting to "write better" with AI's help. But they consistently report that forcing themselves to rely on memory and perception makes them notice different things—small behavioral details, who had actual vs. formal authority, what went unsaid. The constraint creates more observational richness, not less.

DISCIPLINARY CONNECTION

In business and organizational analysis, the ability to observe workplace dynamics without theoretical preconceptions is essential for consultants, managers, and analysts. This mirrors ethnographic field research methods used in organizational studies.

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