The Abductive Execution Lab: Real-Time Diagnosis of Strategy–Outcome Discrepancies with Seed-Spot Process Mining

Implement Lee’s (2025) abductive methodology inside organizations as a standing “Execution Lab.” When outcomes deviate from expectations, the Lab runs structured cycles: re-specify models, revise hypotheses, and seek new data. Use process mining to pinpoint “seed spots” that initiated later failures, borrowing Chen et al.’s lesion-origin logic. Apply across domains where drivers are known but outcomes still disappoint (banking, airports, seaports). This moves beyond post-hoc reviews to a disciplined, real-time discrepancy science that separates conflicting findings from practice issues, addressing strategic management’s credibility gap. It integrates abductive reasoning with digital trace data and governance levers, challenging the assumption that execution shortfalls are purely behavioral by showing how micro-events cascade into systemic failure. Potential impacts include faster model improvement, fewer repeated failures, stronger evidence bases for frameworks like CADAP and PPM, and a blueprint for continuous improvement embedded in OKR cycles.

References:

1. Surprises, Conflicting Findings, or Questionable Research Practices? A Methodology for Evaluating Cumulative Empirical Analyses and Replication Studies. Gwendolyn K. Lee (2025). Strategic Management Review.
2. A Comprehensive Framework for Strategy Execution: CADAP Strategy Execution Framework. Aneek Choudhury, P.N. Ram Kumar, Ramesh Krishnan (2025). IIM Kozhikode Society & Management Review.