Deep insights into digital transformation and data-driven change; the "external brain for digital transformation" for enterprise decision-makers; sharing practical transformation experience; providing actionable strategic insights beyond conventional trend analysis; focusing on pain-point analysis and solutions in transformation; offering digital transformation maturity assessment and improvement.
This article introduces MDM (Master Data Management) platform fundamentals for manufacturing newcomers, covering five core modules, comparing SAP MDG with domestic MDM products, and providing a 7-day hands-on learning plan to master data application, query, quality checks, and distribution monitoring.
The article outlines three pressures squeezing ERP consultants—AI automating standardized tasks, clients handling basic configurations themselves, and demand shifting from system go-live to measurable business impact—and proposes two transformation paths: evolving into solution consultants who diagnose business problems and design decisions, or building ERP+AI composite skills to address gaps beyond native ERP AI capabilities.
The article argues that the demand for IT to understand business better than business departments is a manipulative myth; true business understanding in digital transformation means grasping underlying business logic — why processes exist — and seamlessly integrating digital systems so they become invisible, enabling cross-departmental alignment without overstepping boundaries.
This article analyzes the conflict between ERP and MES production reporting systems in manufacturing, explaining how their differing perspectives, data granularity, and timing cause cost accounting errors, and outlines a four-step integration approach to align shop-floor data with financial records.
This article evaluates two critiques of enterprise ontology and TOGAF ADM, validating their observed pain points — redundant modeling and expert dependency — while correcting the conclusion that the theories are flawed, arguing instead that failures stem from scenario mismatch, mechanical adoption, and missing governance, and offering tailored implementation guidelines.
This concluding article of a 24-part series distills Huawei's 25-year digital transformation into 10 core insights and 10 actionable steps, emphasizing that successful transformation requires adapting principles to one's own context rather than copying Huawei's practices, with leadership commitment, process-first approach, data governance, and cultural change as key pillars.
This article argues that traditional enterprises should pursue digital transformation by activating their decades-old core advantages — industry expertise, trusted channels, supply chains — through a three-step process: inventory strengths, pilot digital integration points, and gradually reconstruct business models, illustrated by cases in agricultural supplies, ceramics, and machine tools.
Midea transformed its supply chain from a 58-day inventory turnover push model to an 18-day order-driven T+3 system, restructuring sales, R&D, planning, procurement, production, and logistics through modular design, daily rolling plans, flexible manufacturing, and supplier collaboration, achieving 63% less capital tied up in inventory.
The article argues business architecture and ontology are not competing replacements but complementary layers: architecture defines governance boundaries while ontology standardizes semantics, and practical digital transformation requires first clarifying their distinct responsibilities then continuously integrating them bidirectionally.
This article outlines S&OP's three-tier value progression — immediate efficiency gains, mid-term resilience, and long-term competitive advantage — and forecasts its evolution toward AI-driven, end-to-end, real-time intelligent supply chains that adapt dynamically to uncertainty.
