Digital transformation: assess what you can verify, then pick tools
The first question is not which platform or whether to add AI. It is which numbers on orders, stock, and customer contact do not match, and which steps you cannot audit.
Digitalization talks often start with platform selection or model capability. A more stable sequence starts with a status check: do core objects (orders, items, customers, collections) have a single source; do key processes have checkpoints you can audit; are operations and finance still reconciling two sets of books.
A useful assessment is short
Four questions usually set priority:
- How many handoffs from order to delivery, and which ones leave no system record
- How often stock books are counted against physical, and how variances are posted
- Whether weekly leadership numbers come from systems or from people stitching files
- Whether customer and after-sales history still lives in personal WeChat and sheets—and whether it survives staff turnover
The question you cannot answer is the chain to finish in phase one, not “roll out collaboration software and wait.” The output should be a business chain you can accept, master-data ownership, and an explicit not-to-do list—not a vendor comparison grid.
Tools come second
After master data, permissions, and one end-to-end path actually run, collaboration, dashboards, or intelligence have something to consume. Without a cadence you can accept, a new system only stacks on old habits: one more login, decisions still made from a last-minute spreadsheet.
For growing firms in Wenzhou and nearby, a practical path is: close inventory and receivables first, then production or stores, then attach stable data to KPI screens. AI belongs on already structured steps (inspection images, document classification, support drafts), not as a patch for messy master data.