Kingdee Cloud Xingchen to Feishu Purchase Order Sync: A Qeasy Hands-On Tutorial

What This Strategy Solves

Pushing purchase orders from an ERP into a collaboration platform may look like a simple data movement, but in practice it usually stalls on three things: codes, organizations, and status. In one of our retail supply-chain integration projects, we saw a typical request: buyers enter orders in Xingchen, while business owners need to see them in Feishu immediately, run approval flows, and keep audit trails. The problem is that supplier codes, organization codes, currencies, and document state machines differ between the two sides.

The core goal of this strategy is to push purchase orders from Xingchen into Feishu according to predefined rules, serving as the authoritative baseline for approval and collaboration. It does not handle reverse writes and does not require strict one-to-one field parity—its job is to make orders visible, searchable, and actionable.

Data Flow and Field Mapping

The flow is unidirectional: Xingchen (A) → Qeasy middleware layer → Feishu (B). The middleware mainly handles code mapping, null-value cleansing, and field standardization, so dirty data never lands directly in Feishu. Below is a key-field mapping example (exact field names depend on the customer environment):

One thing to watch is the header/line split: Xingchen purchase orders are header+line composite structures, while Feishu prefers a "one order, many lines" structure. In Qeasy, we split the header and lines into two sub-tasks, with the lines as child records of the header, to avoid oversized payloads being truncated.

How to Configure in Qeasy

The whole strategy is configured in the Qeasy Data Integration Platform and roughly falls into four blocks:

1. Source connection: Connect to the Xingchen V2 open API and scope data extraction by business organization and document type. We recommend filtering the initial value of FDocumentStatus at the source to avoid pushing invalid drafts downstream.

2. Target connection: Configure Feishu-side application credentials (key details are not disclosed in this document), locate the target multi-dimensional table or approval form, and confirm write permissions.

3. Field mapping and converters: This is the most error-prone area. Our habit is to centralize code mappings (supplier, organization, currency) in Qeasy's "centralized mapping table" rather than scattering them across strategies. When new strategies are added later, they can simply reference this table—one change, effect everywhere.

4. Scheduling and fault tolerance: Configure scheduling frequency, failure retries, and alert channels in Qeasy. Purchase orders do not require extreme real-time performance, so we usually recommend a 5–15 minute cycle, with SMS or Feishu bot alerts on failure.

Implementation Steps

We split the rollout of this strategy into three phases, each with clear exit criteria:

• Phase 1: Increment start point. Pick the first day of a natural month as the "increment start point"—data before that goes through the full-sync channel, data after that goes through the increment channel. On the Xingchen side, we usually use modify_time as the increment cursor. The safe approach is to combine modify_time with the document number as the idempotency key to avoid duplicate pushes.

• Phase 2: Full-sync trigger and reconciliation. Full sync runs only once. After it finishes, reconcile both sides: take the FBillNo set from Xingchen and the order-number set from Feishu, and check the difference. An initial verification is considered passing only when the difference is within one-thousandth. We typically run the reconciliation script directly using Qeasy's "Data Comparison" component—no external tools required.

• Phase 3: Steady-state scheduling. Move to 5–15 minute increment cycles and observe for one week, focusing on three types of anomalies: mapping failures (usually missing values in the code table), status-machine mismatches (drafts that should not appear on the Feishu side), and oversized line items (too many lines causing truncation).

Lessons Learned

Across several customer projects, this strategy tends to fail in these places:

• Code mapping scattered across scripts. In the first version we wrote supplier mappings directly into transformation scripts; later, when the business changed the coding rules, we had to fix five strategies. After switching to a centralized mapping table, only one place needs to be updated. The safe rule: all code-class mappings should be managed centrally.

• Status machine not translated cleanly. Xingchen's "In Review" status does not exist on the Feishu side. Without translation, you get awkward situations where statuses don't match and the wrong person gets pinged. We recommend translating status fields in the middleware layer—the target side should only receive enum values.

• Header and lines processed together. Serializing an entire order into one Feishu field looks convenient but makes later statistics and filtering painful. Header/line split processing greatly improves maintainability.

• Wrong increment start point. Using creation time as the increment cursor is a common mistake—orders modified after approval get missed. The safe approach is a combined judgment of "last modified time + document status change."

• Unbounded failure retries. Unlimited retries during network jitter will block subsequent tasks. We recommend setting a retry cap in Qeasy's scheduler configuration, e.g., three retries, after which the task goes to a manual queue.

Applicable and Non-Applicable Scenarios

This strategy applies when: Xingchen is the system of record for purchase orders, Feishu serves as the approval and collaboration front end, organizations and codes are relatively stable, and the business accepts 5–15 minute latency.

It does not apply when: Feishu needs to write purchase orders back to Xingchen (that is a separate reverse strategy); organizations change frequently and code mappings cannot be stably maintained; or the business requires second-level real-time synchronization.