1. How to read a case
Case dissection·Extracting the generic structure from a specific story: the constraints faced, the key choices made, and why they paid off.
The biggest trap is copying results as playbooks. Reconstruct the constraints first, then study the moves; otherwise you learn only the surface. Read numbers as magnitudes, not as precise targets.
2. Four industries, one logic
Manufacturing
＋ Connected machines, data-driven scheduling and quality
－ Heavy investment, slow payback
适合 Asset-heavy firms with delivery and yield pain
Pharma and health
＋ Compliant data, digital channels, faster response
－ High compliance bar, long validation
适合 Regulated, evidence-heavy value chains
Retail and consumer
＋ Rebuilt audience-goods-place: private domain, small-batch fast response
－ Platform dependence, data disputes
适合 Consumer-facing, many SKUs, fast launches
Platforms and services
＋ Monetize capabilities as services, not margins
－ Complex governance, squeezed by both sides
适合 Intermediaries with data and integration power
Beneath the surface, winners do the same thing: turn operations into data, data into decisions, decisions into faster response. Industries differ in constraints, not logic.
3. Turning cases into action
Abstract the structure
Constraints, key choices, and the causal step that created the win.
Map to your constraints
Different constraints demand different moves. Copying kills.
Find the smallest loop
Run one scenario within a quarter and let results persuade the organization.
Measure and review
Define metrics in advance: cost, cycle, hit rate. Scale wins, cut losses.
4. Industry knowledge in the AI era
Once general models are commodities, industry knowledge becomes the differentiator: feeding process parameters, compliance rules and domain experience into enterprise knowledge bases. But the order stays the same: clarify business logic first, then automate.