Strategy Digest

Foss provides a well-anchored review of Yang et al.'s paper on CEO strategy processes, effectively connecting it to Upper Echelons Theory, Mintzberg, and his own judgment-based framework — a solid example of bridging academic research and practice. The article stays more descriptive than provocative, but the content and connections are genuinely useful.

McGrath builds a historically rich case — from Wright's 1936 cost curve through the BCG matrix — to challenge scale as a strategic axiom, arguing AI is eroding its four traditional benefits and replacing them with new moats: proprietary data, trust, and ecosystem position. Theoretically grounded and practitioner-sharp.

Fisher and Gaur offer a data-driven analysis of 32 U.S. retail chains, surfacing a useful three-stage life-cycle framework — store expansion, online growth, cost reduction — with strong case evidence from Costco, Walmart, and Dillard's. Solid analytical rigor, though the insights stay sector-specific and don't generalize much beyond retail.

Csaszar et al.'s dual-ladder framework — separating the causal hierarchy of strategic reasoning from the delegation hierarchy of when organizations will actually trust AI with autonomy — is the most precise framing of "can AI do strategy?" I've seen, anchored by the insight that AI enters strategy where performance is measurable, not where reasoning is deepest. The piece earns its weight by organizing genuinely competing perspectives (Felin's skepticism, Lakhani's call for clinical trials, Hullman on problem framing) without flattening the disagreements into false consensus.

Choudary distills Reshuffle's core thesis effectively: incumbents fail not from poor execution but from overlaying new tools onto old coordination architectures. The Figma and Shein examples concretely show how changing the unit of work unlocks strategies incumbents structurally cannot pursue, and the reframe from "are we adopting AI fast enough?" to "does our architecture of work still make sense?" should unsettle any leadership team.

Accornero's "Shopper Schism" concept — that the consumer and the shopper are splitting into separate actors as AI agents execute purchases — is a genuinely provocative reframing that any B2C business should sit with. The piece is rigorous where it counts, grounding the argument in how algorithms actually evaluate products (structured data over brand narrative, verified specs over lifestyle imagery) and honestly surfacing the hard questions around agency costs and market concentration rather than hand-waving them away. The dual-arena framework — open web versus walled garden — with tailored strategies for major brands, emerging brands, and retailers gives it practical teeth beyond the thought experiment.

This piece makes a compelling case for treating AI adoption as a portfolio of structured experiments rather than a binary bet, which is exactly the right framing given how much uncertainty surrounds real-world AI impact. The Siemens shop-floor example is particularly valuable — showing how experimentation works in physical production environments, not just software — and the distinction between proper organizational experiments and the informal pilots most companies actually run is a point more leaders need to hear. A useful antidote to the "just deploy it" pressure many organizations face right now.

McCray's piece offers a practical diagnostic for the strategy-execution gap, framed around three failure modes — pace outrunning capacity, roles mismatched to the work, and managers lacking strategic visibility. The checklists of questions for each breakdown are the real value here: they give leaders a concrete starting point to surface misalignment using existing meetings and systems rather than adding new ones. The article stays grounded in consulting experience rather than theory, which keeps it actionable, though it would benefit from exploring how these handoff failures compound in larger, more complex organizations.

Hindo's piece is a well-structured analysis of how generative and agentic AI could erode the aggregator model in online travel, using Expedia and Booking.com as the central case. The three-shift framework — from functional to emotional jobs, toward AI ecosystem positioning, and from structured data to intent interpretation — gives any aggregator business a practical lens to stress-test its own moat. Particularly sharp is the observation that incumbents are now paying for placement inside AI interfaces much as they once paid Google for search visibility, suggesting the cost structure shifts but the dependency deepens.

Martin's piece surfaces a genuinely underappreciated strategic dimension — which activities in the value system to own versus outsource — and his three-rule test (does outsourcing improve your strategy, can the partner hold you up, does it create a competitor?) is crisp and practical. The Herman Miller example is especially sharp: deliberately outsourcing your most critical activity to keep innovation fresh cuts against the usual "insource what matters" instinct.

This article offers a practical 2×2 framework — mapping value-chain control against technological breadth — that helps leaders move beyond generic AI hype and honestly assess where their organization can realistically deploy AI. The case examples are well chosen, particularly the GM/Apple opener and the Zillow cautionary tale, grounding the framework in real operational consequences. That said, the quadrant logic remains fairly static and could go deeper on how companies should sequence moves across quadrants over time.