跨界研究方法的应用：QYResearch如何引入其他学科的分析工具？

Core Insights - The article emphasizes the transformation of consulting and market research towards decision-centric modeling, orchestration of decision flows, and monitoring loops, aligning with the concept of Decision Intelligence Platforms (DIP) that combine data, knowledge, and AI to enhance decision quality [1][4]. Group 1: Methodology and Tools - QYResearch has integrated a systematic approach termed "D-A-T-A" (Define problem - Acquire evidence - Transform model - Action loop) with interdisciplinary tools, enhancing the feedback loop of policies, supply-demand dynamics, and delays [4]. - The introduction of tools like Design of Experiments (DOE) has led to quantifiable improvements in efficiency, analytical depth, and accuracy, reducing ineffective data collection and shortening the hypothesis-to-conclusion cycle [4]. - System dynamics has enabled a shift from point predictions to mechanism explanations and strategy simulations, providing a more forward-looking perspective on micro-decisions such as capacity rhythm and pricing strategies [4]. Group 2: Future Directions - QYResearch plans to diversify its tools by introducing and developing decision components compatible with DIP, focusing on modularization and knowledge base enhancement around modeling, execution, monitoring, and feedback [5]. - The company aims to refine causal identification and engineering processes for A/B and quasi-experiments, creating an integrated stack of diagnostics, prescriptions, scenarios, and experiments [5]. - By linking industry databases with methodology libraries, QYResearch seeks to establish a rolling calibration of "data-model-decision" dashboards, enhancing the transferability and consistency of projects across various industries and regions [5]. Group 3: Company Overview - QYResearch, established in 2007, operates with dual hubs in Beijing and Los Angeles, providing insights across high-tech industry segments, including electronic semiconductors, chemical raw materials, advanced materials, machinery manufacturing, and new energy vehicles [5].