Skill UI

This skill provides a rigorous, operational framework for product and user research. It helps researchers select the appropriate study method (generative, evaluative, validation) based on goals and product stages. It also calculates defensible sample sizes and saturation levels, and synthesizes raw observations into governed, evidence-based insights, ensuring all findings are rooted in cross-participant recurrence.

This powerful orchestrator guides the planning, funding, scoping, and synthesis of enterprise research across four critical domains: clinical R&D, finance, market analysis, and product usability. It acts as a central hub, routing complex inquiries to specialized sub-skills and generating structured digests with actionable insights and critical 'grill challenges' for operational rigor.

This guide helps researchers structure and articulate the core contribution of an Operations Management manuscript for high-impact journals like JOM. It emphasizes the necessity of meeting a dual standard: demonstrating specific theoretical advances in OM theory and providing concrete, actionable practical recommendations, while rigorously ensuring operations remains the central phenomenon.

This guide provides a framework for authors to strategically position their empirical research within the ongoing academic debates of Operations and Supply Chain Management (OM/SCM). It teaches authors to move beyond merely identifying knowledge gaps by problematizing shared assumptions, explicitly distinguishing empirical observation from analytical modeling, and aligning the contribution with the target department's specific mission.

This guide helps researchers select and defend the appropriate empirical methodology for Operations Management (OM) studies. It covers diverse design types—including surveys, archival data analysis, behavioral experiments, field studies, and intervention-based research—ensuring the design is observation-grounded, matches the operational claim, and anticipates rigorous methodological checks.

This guide helps researchers evaluate if their operations management (OM) paper is suitable for the Manufacturing and Service Operations Management (M&SOM) journal. It provides detailed criteria on scope, required operational insight, method rigor (analytical or empirical), and structural house style, ensuring the core contribution addresses practical operations problems rather than just technical methodology.

This guide instructs authors on how to strategically position their research manuscript within the established body of Operations Management (OM) literature. Instead of claiming an unstudied 'void,' the focus is on joining and advancing specific 'operational conversations' within canonical OM streams (e.g., queueing, supply chain, revenue management). It emphasizes differentiating contributions based on novel operational mechanisms or decision levers, ensuring the paper's fit is clear to expert reviewers and editors.

A comprehensive guide for researchers writing about Manufacturing and Service Operations Management (M&SOM). It mandates that the method chosen must be dictated by the core operational decision. Provides detailed frameworks for both the analytical lane (e.g., stochastic optimization, queueing theory, game theory) and the empirical/causal lane (e.g., Difference-in-Differences, Instrumental Variables), ensuring the research delivers actionable operational insights.

This guide provides a critical framework for academic authorship targeting top-tier Operations Management journals. It instructs researchers on how to centralize the operational decision, select the appropriate analytical or empirical 'lane,' and correctly map the research question to a specific editorial department, ensuring the work meets the journal's core scope before any modeling or data analysis begins.

Guides the rigorous development of theoretical models and research frameworks for Production and Operations Management (POM) manuscripts. It covers analytical, empirical, and behavioral tracks, ensuring that all assumptions and mechanisms are deeply grounded in real-world operational constraints and decision-making processes, thereby building a defensible academic argument.