fix: 战略地图P0修复 — KPI code统一+放开同层连线+数据迁移

backend/scripts/erp_daily_sync.sh

@@ -0,0 +1,45 @@
+#!/bin/bash
+# 每日ERP数据同步 — 凌晨3点执行
+# 由Hermes cron调度
+# P1扩展: 增加CRM模块和产模块同步
+source /root/cma-management/backend/venv/bin/activate
+cd /root/cma-management/backend
+
+log() {
+    echo "[$(date '+%Y-%m-%d %H:%M:%S')] $*"
+}
+
+log "=" 60
+log "ERP每日同步开始"
+log "=" 60
+
+# 1. 总账模块同步（原有）
+log "--- 总账模块同步 ---"
+python3 -c "
+from scripts.erp_sync import run_sync
+import logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s')
+run_sync(dry_run=False, use_api=False)
+" >> /root/cma-management/backend/logs/erp_sync_daily.log 2>&1
+
+# 2. CRM模块同步（P1新增）
+log "--- CRM模块同步 ---"
+python3 -c "
+from scripts.erp_sync import run_sync
+import logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s')
+run_sync(dry_run=False, kpi_codes=['C_RETENTION_RATE', 'C_NEW_CLIENTS'], use_api=False)
+" >> /root/cma-management/backend/logs/erp_sync_crm.log 2>&1
+
+# 3. 生产模块同步（P1新增）
+log "--- 生产模块同步 ---"
+python3 -c "
+from scripts.erp_sync import run_sync
+import logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s')
+run_sync(dry_run=False, kpi_codes=['F_QUALITY_RATE', 'F_REWORK_RATE'], use_api=False)
+" >> /root/cma-management/backend/logs/erp_sync_production.log 2>&1
+
+log "=" 60
+log "ERP每日同步完成"
+log "=" 60

backend/scripts/erp_data_source_config.py

@@ -0,0 +1,127 @@
+"""
+ERP数据源配置首批 — 任务8
+配置data_source_config + 同步端点 + 定时任务
+"""
+import sys, os
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from dotenv import load_dotenv
+load_dotenv()
+
+from app.database import get_engine
+from sqlalchemy import text
+from datetime import datetime
+
+engine = get_engine()
+
+# 首批8个ERP-KPI的数据源配置
+ERP_SOURCES = [
+    {
+        "name": "ERP总账-营业收入",
+        "kpi_codes": ["F_REVENUE"],
+        "source_type": "erp",
+        "api_endpoint": "http://127.0.0.1:8300/api/v1/stats/monthly",
+        "query_sql": "SELECT COALESCE(SUM(SumMoney), 0) as value FROM MasterBill WHERE BillType=1 AND BillState>=3 AND Period=:period",
+        "sync_type": "daily",
+    },
+    {
+        "name": "ERP总账-毛利率",
+        "kpi_codes": ["F_GROSS_MARGIN", "F_PROFIT_RATE"],
+        "source_type": "erp",
+        "api_endpoint": "http://127.0.0.1:8300/api/v1/stats/gross-profit",
+        "query_sql": "SELECT CASE WHEN SUM(SumMoney) > 0 THEN ROUND((SUM(SumMoney)-COALESCE(SUM(SumCostMoney),0))/SUM(SumMoney)*100,2) ELSE 0 END as value FROM MasterBill WHERE BillType=1 AND BillState>=3 AND Period=:period",
+        "sync_type": "daily",
+    },
+    {
+        "name": "ERP总账-净利润",
+        "kpi_codes": ["F_NET_PROFIT", "F_NET_PROFIT_RATE"],
+        "source_type": "erp",
+        "api_endpoint": "http://127.0.0.1:8300/api/v1/stats/monthly",
+        "query_sql": "SELECT COALESCE(SUM(SumMoney),0)-COALESCE(SUM(SumCostMoney),0)-COALESCE(SUM(SumExpense),0) as value FROM MasterBill WHERE BillType IN (1,2,3) AND BillState>=3 AND Period=:period",
+        "sync_type": "daily",
+    },
+    {
+        "name": "ERP总账-费用率",
+        "kpi_codes": ["F_COST_RATIO"],
+        "source_type": "erp",
+        "api_endpoint": "http://127.0.0.1:8300/api/v1/stats/monthly",
+        "query_sql": "SELECT CASE WHEN SUM(CASE WHEN BillType=1 THEN SumMoney ELSE 0 END) > 0 THEN ROUND((COALESCE(SUM(CASE WHEN BillType=2 THEN SumMoney ELSE 0 END),0)+COALESCE(SUM(CASE WHEN BillType=3 THEN SumMoney ELSE 0 END),0))/SUM(CASE WHEN BillType=1 THEN SumMoney ELSE 0 END)*100,2) ELSE 0 END as value FROM MasterBill WHERE BillState>=3 AND Period=:period",
+        "sync_type": "daily",
+    },
+    {
+        "name": "ERP总账-经营性现金流",
+        "kpi_codes": ["F_OP_CFLOW", "F_CASH_FLOW"],
+        "source_type": "erp",
+        "api_endpoint": "http://127.0.0.1:8300/api/v1/cashflow",
+        "query_sql": "SELECT COALESCE(SUM(CashIn),0)-COALESCE(SUM(CashOut),0) as value FROM CashFlow WHERE Period=:period",
+        "sync_type": "daily",
+    },
+    {
+        "name": "ERP应收-周转天数",
+        "kpi_codes": ["F_AR_DAYS", "F_AR_TURNOVER"],
+        "source_type": "erp",
+        "api_endpoint": "http://127.0.0.1:8300/api/v1/ar/aging",
+        "query_sql": "SELECT CASE WHEN total_sales > 0 THEN ROUND(AVG_receivable/total_sales*365,0) ELSE 0 END as value FROM (SELECT SUM(CASE WHEN BillType=1 THEN SumMoney ELSE 0 END) as total_sales, AVG(CASE WHEN BillType=1 THEN SumMoney ELSE 0 END) as AVG_receivable FROM MasterBill WHERE BillState>=3 AND Period<=:period) t",
+        "sync_type": "daily",
+    },
+    {
+        "name": "ERP交付-及时率",
+        "kpi_codes": ["P_DELIVERY", "P_DELIVERY_ON_TIME"],
+        "source_type": "erp",
+        "api_endpoint": "http://127.0.0.1:8300/api/v1/delivery/rate",
+        "query_sql": "SELECT CASE WHEN total_orders > 0 THEN ROUND(on_time_orders/total_orders*100,2) ELSE 0 END as value FROM (SELECT COUNT(*) as total_orders, SUM(CASE WHEN ActualDelivery<=PlanDelivery THEN 1 ELSE 0 END) as on_time_orders FROM OrderDelivery WHERE Period=:period) t",
+        "sync_type": "daily",
+    },
+    {
+        "name": "ERP质量-缺陷率",
+        "kpi_codes": ["P_BUG_RATE", "P_DEFECT_RATE"],
+        "source_type": "erp",
+        "api_endpoint": "http://127.0.0.1:8300/api/v1/quality/defect",
+        "query_sql": "SELECT CASE WHEN total_qty > 0 THEN ROUND(defect_qty/total_qty*100,2) ELSE 0 END as value FROM (SELECT COUNT(*) as total_qty, SUM(CASE WHEN QualityStatus='NG' THEN 1 ELSE 0 END) as defect_qty FROM QualityInspection WHERE Period=:period) t",
+        "sync_type": "daily",
+    },
+]
+
+def log(msg):
+    print(f"[{datetime.now():%H:%M:%S}] {msg}")
+
+with engine.connect() as conn:
+    print("=" * 70)
+    log("配置ERP数据源 (data_source_config)")
+    print("=" * 70)
+
+    existing = conn.execute(text("SELECT COUNT(*) FROM data_source_config")).scalar()
+    log(f"当前已有 {existing} 条数据源配置")
+
+    created = 0
+    for src in ERP_SOURCES:
+        exists = conn.execute(
+            text("SELECT id FROM data_source_config WHERE name=:name"),
+            {"name": src["name"]}
+        ).fetchone()
+        if exists:
+            log(f"  ⏭️  已存在: {src['name']} (id={exists[0]})")
+            continue
+
+        conn.execute(text("""
+            INSERT INTO data_source_config 
+            (name, source_type, api_endpoint, query_sql, sync_type, status, created_at)
+            VALUES (:name, :source_type, :api_endpoint, :query_sql, :sync_type, 'active', NOW())
+        """), {
+            "name": src["name"],
+            "source_type": src["source_type"],
+            "api_endpoint": src["api_endpoint"],
+            "query_sql": src["query_sql"],
+            "sync_type": src["sync_type"],
+        })
+        created += 1
+        log(f"  ✅ 新增: {src['name']} — 关联KPI: {', '.join(src['kpi_codes'])}")
+
+    conn.commit()
+    log(f"\n✅ 数据源配置完成: 新增 {created} 条, 当前共 {existing + created} 条")
+
+    # 打印所有数据源
+    rows = conn.execute(text("SELECT id, name, source_type, sync_type, status FROM data_source_config ORDER BY id")).fetchall()
+    print("\n数据源清单:")
+    for r in rows:
+        print(f"  [{r[0]}] {r[1]:30s} type={r[2]:10s} sync={r[3]:10s} status={r[4]}")

backend/scripts/erp_p1_crm_prod.py

@@ -0,0 +1,148 @@
+""""
+ERP数据源扩展 — 任务5: CRM+生产模块对接
+执行: cd /root/cma-management/backend && python3 scripts/erp_p1_crm_prod.py
+"""
+import sys, os
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from dotenv import load_dotenv
+load_dotenv()
+
+from app.database import get_engine
+from sqlalchemy import text
+from datetime import datetime
+
+engine = get_engine()
+
+def log(msg):
+    print(f"[{datetime.now():%H:%M:%S}] {msg}")
+
+# CRM + 生产模块数据源配置
+NEW_SOURCES = [
+    # ─── CRM模块 ───
+    {
+        "name": "ERP-CRM-客户保留率",
+        "kpi_codes": ["C_RETENTION_RATE"],
+        "source_type": "erp",
+        "api_endpoint": "http://erp-api.sxbh.ltd/api/v1/crm/retention-rate",
+        "query_sql": """SELECT CASE WHEN total_customers > 0 
+THEN ROUND(renew_customers/total_customers*100, 2) ELSE 0 END as value 
+FROM (SELECT COUNT(*) as total_customers, 
+SUM(CASE WHEN DATEDIFF(day, last_order_date, GETDATE()) <= 365 THEN 1 ELSE 0 END) as renew_customers 
+FROM Units WHERE UnitType='Customer') t""",
+        "sync_type": "daily",
+    },
+    {
+        "name": "ERP-CRM-新客户数",
+        "kpi_codes": ["C_NEW_CLIENTS"],
+        "source_type": "erp",
+        "api_endpoint": "http://erp-api.sxbh.ltd/api/v1/crm/new-customers",
+        "query_sql": "SELECT COUNT(*) as value FROM Units WHERE UnitType='Customer' AND DATEDIFF(day, CreateDate, GETDATE()) <= 30",
+        "sync_type": "daily",
+    },
+    # ─── 生产模块 ───
+    {
+        "name": "ERP-生产-产品合格率",
+        "kpi_codes": ["F_QUALITY_RATE"],
+        "source_type": "erp",
+        "api_endpoint": "http://erp-api.sxbh.ltd/api/v1/production/quality-rate",
+        "query_sql": """SELECT CASE WHEN total_qty > 0 
+THEN ROUND(qualified_qty/total_qty*100, 2) ELSE 0 END as value 
+FROM (SELECT COUNT(*) as total_qty, 
+SUM(CASE WHEN QualityStatus='OK' THEN 1 ELSE 0 END) as qualified_qty 
+FROM QualityInspection WHERE Period=:period) t""",
+        "sync_type": "daily",
+    },
+    {
+        "name": "ERP-生产-返工率",
+        "kpi_codes": ["F_REWORK_RATE"],
+        "source_type": "erp",
+        "api_endpoint": "http://erp-api.sxbh.ltd/api/v1/production/rework-rate",
+        "query_sql": """SELECT CASE WHEN total_qty > 0 
+THEN ROUND(rework_qty/total_qty*100, 2) ELSE 0 END as value 
+FROM (SELECT COUNT(*) as total_qty, 
+SUM(CASE WHEN ReworkStatus='Rework' THEN 1 ELSE 0 END) as rework_qty 
+FROM ProductionOrder WHERE Period=:period) t""",
+        "sync_type": "daily",
+    },
+]
+
+with engine.connect() as conn:
+    print("=" * 70)
+    log("开始ERP数据源扩展 — 任务5: CRM+生产模块")
+    print("=" * 70)
+
+    created = 0
+    for src in NEW_SOURCES:
+        exists = conn.execute(
+            text("SELECT id FROM data_source_config WHERE name=:name"),
+            {"name": src["name"]}
+        ).fetchone()
+        if exists:
+            log(f"  ⏭️  已存在: {src['name']} (id={exists[0]})")
+            continue
+
+        conn.execute(text("""
+            INSERT INTO data_source_config 
+            (name, source_type, api_endpoint, query_sql, sync_type, status, created_at)
+            VALUES (:name, :source_type, :api_endpoint, :query_sql, :sync_type, 'active', NOW())
+        """), {
+            "name": src["name"],
+            "source_type": src["source_type"],
+            "api_endpoint": src["api_endpoint"],
+            "query_sql": src["query_sql"],
+            "sync_type": src["sync_type"],
+        })
+        created += 1
+        log(f"  ✅ 新增: {src['name']} — 关联KPI: {', '.join(src['kpi_codes'])}")
+
+    conn.commit()
+
+    # 打印所有数据源
+    rows = conn.execute(text(
+        "SELECT id, name, source_type, sync_type, status FROM data_source_config ORDER BY id"
+    )).fetchall()
+    print("\n数据源清单:")
+    for r in rows:
+        print(f"  [{r[0]}] {r[1]:35s} type={r[2]:10s} sync={r[3]:10s} status={r[4]}")
+    log(f"\n✅ CRM+生产模块数据源配置完成: 新增 {created} 条, 共 {len(rows)} 条")
+
+    # 更新KPI的data_source_config字段（存储关联的数据源ID）
+    log("\n更新KPI的data_source_config字段...")
+    for src in NEW_SOURCES:
+        src_row = conn.execute(
+            text("SELECT id FROM data_source_config WHERE name=:name"),
+            {"name": src["name"]}
+        ).fetchone()
+        if not src_row:
+            continue
+        for kpi_code in src["kpi_codes"]:
+            kpi = conn.execute(
+                text("SELECT id, data_source_config FROM kpi_definitions WHERE kpi_code=:code AND status='active'"),
+                {"code": kpi_code}
+            ).fetchone()
+            if kpi:
+                existing_config = kpi[1] or {}
+                if isinstance(existing_config, str):
+                    import json
+                    try:
+                        existing_config = json.loads(existing_config)
+                    except:
+                        existing_config = {}
+                # 确保是dict
+                if not isinstance(existing_config, dict):
+                    existing_config = {"source_ids": []}
+                if "source_ids" not in existing_config:
+                    existing_config["source_ids"] = []
+                if src_row[0] not in existing_config["source_ids"]:
+                    existing_config["source_ids"].append(src_row[0])
+                import json
+                conn.execute(
+                    text("UPDATE kpi_definitions SET data_source_config=:config WHERE id=:id"),
+                    {"config": json.dumps(existing_config, ensure_ascii=False), "id": kpi[0]}
+                )
+                log(f"  ✅ KPI {kpi_code}: data_source_config 已更新")
+
+    conn.commit()
+    log("\n✅ 任务5: CRM+生产模块对接完成")
+    print("=" * 70)

backend/scripts/erp_sync.py

@@ -110,6 +110,12 @@ def fetch_via_api(kpi: KPIDefinition, parsed: dict, period: str) -> float:
         "CUSTOMER_COUNT": f"{ERP_API_BASE}/stats/monthly?year={period_year}",
         "SALES_PROFIT_RATE": f"{ERP_API_BASE}/stats/gross-profit?year={period_year}&month={period_month}",
         "TOP5_CUSTOMER_RATIO": f"{ERP_API_BASE}/stats/customer-top?year={period_year}&limit=5",
+        # P1: CRM模块
+        "C_RETENTION_RATE": f"{ERP_API_BASE}/crm/retention-rate?year={period_year}&month={period_month}",
+        "C_NEW_CLIENTS": f"{ERP_API_BASE}/crm/new-customers?year={period_year}&month={period_month}",
+        # P1: 生产模块
+        "F_QUALITY_RATE": f"{ERP_API_BASE}/production/quality-rate?year={period_year}&month={period_month}",
+        "F_REWORK_RATE": f"{ERP_API_BASE}/production/rework-rate?year={period_year}&month={period_month}",
     }
 
     headers = {"X-API-Key": ERP_API_KEY, "User-Agent": "CMA-ERP-SYNC/1.0"}
@@ -159,6 +165,22 @@ def fetch_via_api(kpi: KPIDefinition, parsed: dict, period: str) -> float:
             return round(top5_total / total_amount * 100, 2)
         return 0
 
+    # P1: CRM模块 — 客户保留率
+    elif kpi_code == "C_RETENTION_RATE":
+        return float(data.get("retention_rate", data.get("value", 0)))
+
+    # P1: CRM模块 — 新客户数
+    elif kpi_code == "C_NEW_CLIENTS":
+        return float(data.get("new_customers", data.get("value", 0)))
+
+    # P1: 生产模块 — 产品合格率
+    elif kpi_code == "F_QUALITY_RATE":
+        return float(data.get("quality_rate", data.get("value", 0)))
+
+    # P1: 生产模块 — 返工率
+    elif kpi_code == "F_REWORK_RATE":
+        return float(data.get("rework_rate", data.get("value", 0)))
+
     raise ValueError(f"未实现的API映射: {kpi_code}")
 
 

backend/scripts/kpi_p0_optimization.py

@@ -0,0 +1,354 @@
+"""
+KPI字典库优化P0阶段 — 批量脚本
+涵盖任务1-6: 激活模板KPI + 新增KPI + 修复员工满意度
+"""
+import sys, os
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from dotenv import load_dotenv
+load_dotenv()
+
+from app.database import get_engine
+from sqlalchemy import text
+from datetime import datetime
+
+engine = get_engine()
+
+def log(msg):
+    print(f"[{datetime.now():%H:%M:%S}] {msg}")
+
+def insert_kpi(conn, **kw):
+    """安全插入KPI（检查唯一性）"""
+    code = kw["kpi_code"]
+    exists = conn.execute(text("SELECT id FROM kpi_definitions WHERE kpi_code=:code"), {"code": code}).fetchone()
+    if exists:
+        log(f"  ⏭️  已存在: {code} (id={exists[0]})")
+        return exists[0], False
+    cols = ", ".join(kw.keys())
+    vals = ", ".join(f":{k}" for k in kw.keys())
+    conn.execute(text(f"INSERT INTO kpi_definitions ({cols}) VALUES ({vals})"), kw)
+    new_id = conn.execute(text("SELECT LAST_INSERT_ID()")).scalar()
+    log(f"  ✅ 新增: {code} (id={new_id})")
+    return new_id, True
+
+with engine.connect() as conn:
+    print("=" * 70)
+    log("开始KPI字典库优化P0 — 任务1~6")
+    print("=" * 70)
+
+    # =========================================================
+    # 任务1: 激活4个系统模板KPI
+    # =========================================================
+    log("\n【任务1】激活系统模板KPI")
+    print("-" * 50)
+
+    # 从kpi_templates读取模板数据
+    templates = conn.execute(text(
+        "SELECT id, kpi_code, kpi_name, dimension, category, formula, formula_desc, "
+        "unit, target_value, description FROM kpi_templates WHERE kpi_code IN "
+        "('F_ASSET_TURNOVER', 'F_REVENUE_GROWTH', 'L_EMPLOYEE_TURNOVER', 'L_TECH_COVERAGE')"
+    )).fetchall()
+
+    for t in templates:
+        tid, code, name, dim, cat, formula, fdesc, unit, target, desc = t
+        nid, is_new = insert_kpi(conn,
+            template_id=tid,
+            is_system=1,
+            kpi_code=code,
+            kpi_name=name,
+            dimension=dim,
+            category=cat,
+            formula=formula or "",
+            formula_desc=fdesc or desc or "",
+            unit=unit or "%",
+            target_value=target,
+            data_source_type="manual",
+            frequency="monthly",
+            status="active",
+            epic="Epic2",
+            created_at=datetime.now(),
+            updated_at=datetime.now(),
+        )
+        if is_new:
+            # 设置阈值
+            if code == "F_ASSET_TURNOVER":
+                conn.execute(text("UPDATE kpi_definitions SET threshold_green='>=1.0', threshold_yellow='>=0.8', threshold_red='<0.8' WHERE id=:id"), {"id": nid})
+            elif code == "F_REVENUE_GROWTH":
+                conn.execute(text("UPDATE kpi_definitions SET threshold_green='>=20', threshold_yellow='>=15', threshold_red='<15' WHERE id=:id"), {"id": nid})
+            elif code == "L_EMPLOYEE_TURNOVER":
+                conn.execute(text("UPDATE kpi_definitions SET threshold_green='<=5', threshold_yellow='<=10', threshold_red='>10' WHERE id=:id"), {"id": nid})
+            elif code == "L_TECH_COVERAGE":
+                conn.execute(text("UPDATE kpi_definitions SET threshold_green='>=90', threshold_yellow='>=80', threshold_red='<80' WHERE id=:id"), {"id": nid})
+            # 更新模板使用计数
+            conn.execute(text("UPDATE kpi_templates SET usage_count = IFNULL(usage_count,0)+1 WHERE id=:id"), {"id": tid})
+            log(f"    阈值已配置")
+
+    # =========================================================
+    # 任务2: 新增6个财务KPI
+    # =========================================================
+    log("\n【任务2】新增6个财务KPI")
+    print("-" * 50)
+
+    finance_kpis = [
+        ("F_CURRENT_RATIO", "流动比率", "finance", "cash_risk",
+         "流动资产/流动负债", "%", 200.0, ">=200", ">=150", "<150", "erp"),
+        ("F_QUICK_RATIO", "速动比率", "finance", "cash_risk",
+         "(流动资产-存货)/流动负债", "%", 100.0, ">=100", ">=80", "<80", "erp"),
+        ("F_INV_DAYS", "存货周转天数", "finance", "asset_efficiency",
+         "365/存货周转率", "天", 45.0, "<=30", "<=45", ">45", "erp"),
+        ("F_ROI", "总资产报酬率(ROI)", "finance", "profitability",
+         "净利润/平均总资产*100", "%", 8.0, ">=12", ">=8", "<8", "erp"),
+        ("F_QUALITY_RATE", "产品合格率", "finance", "delivery_quality",
+         "正品数/总产量*100", "%", 98.0, ">=99", ">=98", "<98", "erp"),
+        ("F_REWORK_RATE", "返工率", "finance", "delivery_quality",
+         "返工工时/总工时*100", "%", 5.0, "<=3", "<=5", ">5", "erp"),
+    ]
+
+    for code, name, dim, cat, formula, unit, target, tg, ty, tr, src in finance_kpis:
+        nid, is_new = insert_kpi(conn,
+            is_system=0,
+            kpi_code=code,
+            kpi_name=name,
+            dimension=dim,
+            category=cat,
+            formula=formula,
+            formula_desc=f"CMA标准{name}指标",
+            unit=unit,
+            target_value=target,
+            threshold_green=tg,
+            threshold_yellow=ty,
+            threshold_red=tr,
+            data_source_type=src,
+            frequency="monthly",
+            status="active",
+            epic="Epic2",
+            created_at=datetime.now(),
+            updated_at=datetime.now(),
+        )
+
+    # =========================================================
+    # 任务3: 新增3个客户KPI
+    # =========================================================
+    log("\n【任务3】新增3个客户KPI")
+    print("-" * 50)
+
+    # 激活C_CUSTOMER_CONCENTRATION模板
+    t = conn.execute(text(
+        "SELECT id, kpi_code, kpi_name, dimension, category, formula, formula_desc, "
+        "unit, target_value, description FROM kpi_templates WHERE kpi_code='C_CUSTOMER_CONCENTRATION'"
+    )).fetchone()
+    if t:
+        nid, is_new = insert_kpi(conn,
+            template_id=t[0],
+            is_system=1,
+            kpi_code="C_CUST_CONCENTRATION",
+            kpi_name="客户集中度",
+            dimension=t[3],
+            category=t[4],
+            formula=t[5] or "",
+            formula_desc=t[6] or t[9] or "",
+            unit=t[7] or "%",
+            target_value=t[8],
+            data_source_type="erp",
+            frequency="monthly",
+            status="active",
+            epic="Epic2",
+            threshold_green="<=20",
+            threshold_yellow="<=30",
+            threshold_red=">30",
+            created_at=datetime.now(),
+            updated_at=datetime.now(),
+        )
+        if is_new:
+            conn.execute(text("UPDATE kpi_templates SET usage_count = IFNULL(usage_count,0)+1 WHERE id=:id"), {"id": t[0]})
+
+    # C_RETENTION_RATE
+    insert_kpi(conn,
+        is_system=0,
+        kpi_code="C_RETENTION_RATE",
+        kpi_name="客户保留率",
+        dimension="customer",
+        category="customer_scale",
+        formula="续约客户数/总客户数*100",
+        formula_desc="CMA标准客户保留率指标，反映客户粘性",
+        unit="%",
+        target_value=85.0,
+        threshold_green=">=90",
+        threshold_yellow=">=85",
+        threshold_red="<85",
+        data_source_type="erp",
+        frequency="monthly",
+        status="active",
+        epic="Epic2",
+        created_at=datetime.now(),
+        updated_at=datetime.now(),
+    )
+
+    # C_CAC — 注意C_CAC可能已存在（reset_kpi_dict中有定义），改用C_ACQUISITION_COST
+    insert_kpi(conn,
+        is_system=0,
+        kpi_code="C_ACQUISITION_COST",
+        kpi_name="获客成本(CAC)",
+        dimension="customer",
+        category="customer_scale",
+        formula="营销费用/新客户数",
+        formula_desc="CMA标准客户获取成本指标",
+        unit="元",
+        target_value=None,
+        threshold_green="<=500",
+        threshold_yellow="<=800",
+        threshold_red=">800",
+        data_source_type="erp",
+        frequency="monthly",
+        status="active",
+        epic="Epic2",
+        created_at=datetime.now(),
+        updated_at=datetime.now(),
+    )
+
+    # =========================================================
+    # 任务4: 新增2个流程KPI
+    # =========================================================
+    log("\n【任务4】新增2个流程KPI")
+    print("-" * 50)
+
+    insert_kpi(conn,
+        is_system=0,
+        kpi_code="P_PASS_RATE",
+        kpi_name="过程合格率",
+        dimension="process",
+        category="delivery_quality",
+        formula="过程合格批次数/总检验批次数*100",
+        formula_desc="流程层关注过程质量合格率，区别于财务层产品合格率",
+        unit="%",
+        target_value=95.0,
+        threshold_green=">=98",
+        threshold_yellow=">=95",
+        threshold_red="<95",
+        data_source_type="erp",
+        frequency="monthly",
+        status="active",
+        epic="Epic2",
+        created_at=datetime.now(),
+        updated_at=datetime.now(),
+    )
+
+    insert_kpi(conn,
+        is_system=0,
+        kpi_code="P_REWORK_RATE",
+        kpi_name="流程返工率",
+        dimension="process",
+        category="delivery_quality",
+        formula="返工批次/总生产批次*100",
+        formula_desc="流程层返工率，体现过程质量控制水平",
+        unit="%",
+        target_value=5.0,
+        threshold_green="<=3",
+        threshold_yellow="<=5",
+        threshold_red=">5",
+        data_source_type="erp",
+        frequency="monthly",
+        status="active",
+        epic="Epic2",
+        created_at=datetime.now(),
+        updated_at=datetime.now(),
+    )
+
+    # =========================================================
+    # 任务5: 新增2个学习KPI
+    # =========================================================
+    log("\n【任务5】新增2个学习KPI")
+    print("-" * 50)
+
+    # 激活L_TRAINING_HOURS模板
+    t = conn.execute(text(
+        "SELECT id, kpi_code, kpi_name, dimension, category, formula, formula_desc, "
+        "unit, target_value, description FROM kpi_templates WHERE kpi_code='L_TRAINING_HOURS'"
+    )).fetchone()
+    if t:
+        nid, is_new = insert_kpi(conn,
+            template_id=t[0],
+            is_system=1,
+            kpi_code="L_TRAINING_HOURS",
+            kpi_name="人均培训时长",
+            dimension=t[3],
+            category=t[4],
+            formula=t[5] or "",
+            formula_desc=t[6] or t[9] or "",
+            unit=t[7] or "小时",
+            target_value=t[8],
+            data_source_type="manual",
+            frequency="monthly",
+            status="active",
+            epic="Epic2",
+            threshold_green=">=40",
+            threshold_yellow=">=20",
+            threshold_red="<20",
+            created_at=datetime.now(),
+            updated_at=datetime.now(),
+        )
+        if is_new:
+            conn.execute(text("UPDATE kpi_templates SET usage_count = IFNULL(usage_count,0)+1 WHERE id=:id"), {"id": t[0]})
+
+    # L_COMPETENCY
+    insert_kpi(conn,
+        is_system=0,
+        kpi_code="L_COMPETENCY",
+        kpi_name="关键岗位胜任度",
+        dimension="learning",
+        category="talent_pipeline",
+        formula="胜任评估得分≥80分人数/关键岗位总人数*100",
+        formula_desc="CMA标准关键岗位胜任度指标，通过胜任力评估获取",
+        unit="%",
+        target_value=85.0,
+        threshold_green=">=90",
+        threshold_yellow=">=85",
+        threshold_red="<85",
+        data_source_type="manual",
+        frequency="quarterly",
+        status="active",
+        epic="Epic2",
+        created_at=datetime.now(),
+        updated_at=datetime.now(),
+    )
+
+    # =========================================================
+    # 任务6: 修复员工满意度阈值
+    # =========================================================
+    log("\n【任务6】修复员工满意度阈值")
+    print("-" * 50)
+
+    sat = conn.execute(text("SELECT id FROM kpi_definitions WHERE kpi_code='L_EMPLOYEE_SAT'")).fetchone()
+    if sat:
+        conn.execute(text(
+            "UPDATE kpi_definitions SET threshold_green='>=80', threshold_yellow='>=60', threshold_red='<60' WHERE id=:id"
+        ), {"id": sat[0]})
+        log(f"  ✅ 员工满意度(id={sat[0]}) 阈值已设置: 绿>=80, 黄>=60, 红<60")
+    else:
+        log("  ⚠️  员工满意度KPI不存在")
+
+    # =========================================================
+    # 提交事务
+    # =========================================================
+    conn.commit()
+
+    # 统计
+    total = conn.execute(text("SELECT COUNT(*) FROM kpi_definitions WHERE status='active'")).scalar()
+    by_dim = conn.execute(text(
+        "SELECT dimension, COUNT(*) FROM kpi_definitions WHERE status='active' GROUP BY dimension ORDER BY dimension"
+    )).fetchall()
+    no_threshold = conn.execute(text(
+        "SELECT kpi_code, kpi_name FROM kpi_definitions WHERE status='active' AND (threshold_green IS NULL OR threshold_yellow IS NULL OR threshold_red IS NULL)"
+    )).fetchall()
+
+    print("\n" + "=" * 70)
+    log(f"✅ 任务1~6完成！KPI字典共 {total} 条")
+    for d, c in by_dim:
+        print(f"   {d}: {c} 条")
+    if no_threshold:
+        print(f"\n⚠️  以下KPI仍缺阈值:")
+        for code, name in no_threshold:
+            print(f"   {code}: {name}")
+    else:
+        print("\n✅ 所有KPI均有阈值配置")
+    print("=" * 70)

backend/scripts/kpi_p1_optimization.py

@@ -0,0 +1,256 @@
+""""
+KPI字典库优化P1阶段 — Tasks 1-4: 新增9个P1级KPI
+执行: cd /root/cma-management/backend && python3 scripts/kpi_p1_optimization.py
+"""
+import sys, os
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from dotenv import load_dotenv
+load_dotenv()
+
+from app.database import get_engine
+from sqlalchemy import text
+from datetime import datetime
+
+engine = get_engine()
+
+def log(msg):
+    print(f"[{datetime.now():%H:%M:%S}] {msg}")
+
+def insert_kpi(conn, **kw):
+    code = kw["kpi_code"]
+    exists = conn.execute(text("SELECT id FROM kpi_definitions WHERE kpi_code=:code"), {"code": code}).fetchone()
+    if exists:
+        log(f"  ⏭️  已存在: {code} (id={exists[0]})")
+        return exists[0], False
+    cols = ", ".join(kw.keys())
+    vals = ", ".join(f":{k}" for k in kw.keys())
+    conn.execute(text(f"INSERT INTO kpi_definitions ({cols}) VALUES ({vals})"), kw)
+    new_id = conn.execute(text("SELECT LAST_INSERT_ID()")).scalar()
+    log(f"  ✅ 新增: {code} (id={new_id})")
+    return new_id, True
+
+def activate_template(conn, template_code, target_code, target_name, threshold_green, threshold_yellow, threshold_red, data_source_type="manual", frequency="monthly"):
+    """从模板激活KPI"""
+    t = conn.execute(text(
+        "SELECT id, kpi_code, kpi_name, dimension, category, formula, formula_desc, "
+        "unit, target_value, description FROM kpi_templates WHERE kpi_code=:code"
+    ), {"code": template_code}).fetchone()
+    if not t:
+        log(f"  ❌ 模板不存在: {template_code}")
+        return None, False
+    nid, is_new = insert_kpi(conn,
+        template_id=t[0],
+        is_system=1,
+        kpi_code=target_code,
+        kpi_name=target_name or t[2],
+        dimension=t[3],
+        category=t[4],
+        formula=t[5] or "",
+        formula_desc=t[6] or t[9] or "",
+        unit=t[7] or "%",
+        target_value=t[8],
+        data_source_type=data_source_type,
+        frequency=frequency,
+        status="active",
+        epic="Epic2",
+        threshold_green=threshold_green,
+        threshold_yellow=threshold_yellow,
+        threshold_red=threshold_red,
+        created_at=datetime.now(),
+        updated_at=datetime.now(),
+    )
+    if is_new:
+        conn.execute(text("UPDATE kpi_templates SET usage_count = IFNULL(usage_count,0)+1 WHERE id=:id"), {"id": t[0]})
+    return nid, is_new
+
+with engine.connect() as conn:
+    print("=" * 70)
+    log("开始KPI字典库优化P1 — 任务1~4: 新增9个P1级KPI")
+    print("=" * 70)
+
+    # =========================================================
+    # 任务1: 新增财务P1级KPI（3个）
+    # =========================================================
+    log("\n【任务1】新增财务P1级KPI")
+    print("-" * 50)
+
+    finance_kpis = [
+        ("F_DEBT_RATIO", "资产负债率", "finance", "cash_risk",
+         "总负债/总资产", "%", 50.0, "<50", "<70", ">=70", "erp"),
+        ("F_INTEREST_COVER", "利息保障倍数", "finance", "profitability",
+         "EBIT/利息费用", "倍", 5.0, ">5", ">2", "<=2", "erp"),
+        ("F_EVA", "经济增加值(EVA)", "finance", "profitability",
+         "税后净营业利润-资本成本", "元", 0.0, ">0", ">-100000", "<=-100000", "erp"),
+    ]
+
+    for code, name, dim, cat, formula, unit, target, tg, ty, tr, src in finance_kpis:
+        nid, is_new = insert_kpi(conn,
+            is_system=0,
+            kpi_code=code,
+            kpi_name=name,
+            dimension=dim,
+            category=cat,
+            formula=formula,
+            formula_desc=f"CMA标准{name}指标",
+            unit=unit,
+            target_value=target,
+            threshold_green=tg,
+            threshold_yellow=ty,
+            threshold_red=tr,
+            data_source_type=src,
+            frequency="monthly",
+            status="active",
+            epic="Epic2",
+            created_at=datetime.now(),
+            updated_at=datetime.now(),
+        )
+
+    # =========================================================
+    # 任务2: 新增客户P1级KPI（2个）
+    # =========================================================
+    log("\n【任务2】新增客户P1级KPI")
+    print("-" * 50)
+
+    customer_kpis = [
+        ("C_MARKET_SHARE", "市场份额", "customer", "customer_scale",
+         "公司收入/行业总收入", "%", 10.0, ">10", ">5", "<=5", "erp"),
+        ("C_NPS", "净推荐值(NPS)", "customer", "customer_satisfaction",
+         "NPS评分(-100~100)", "分", 50.0, ">50", ">0", "<=0", "manual"),
+    ]
+
+    for code, name, dim, cat, formula, unit, target, tg, ty, tr, src in customer_kpis:
+        nid, is_new = insert_kpi(conn,
+            is_system=0,
+            kpi_code=code,
+            kpi_name=name,
+            dimension=dim,
+            category=cat,
+            formula=formula,
+            formula_desc=f"CMA标准{name}指标",
+            unit=unit,
+            target_value=target,
+            threshold_green=tg,
+            threshold_yellow=ty,
+            threshold_red=tr,
+            data_source_type=src,
+            frequency="monthly",
+            status="active",
+            epic="Epic2",
+            created_at=datetime.now(),
+            updated_at=datetime.now(),
+        )
+
+    # =========================================================
+    # 任务3: 新增流程P1级KPI（3个）
+    # =========================================================
+    log("\n【任务3】新增流程P1级KPI")
+    print("-" * 50)
+
+    # 3.1 激活P_SUPPLY_CYCLE模板
+    log("  --- 激活模板: P_SUPPLY_CYCLE (供应链响应周期)")
+    activate_template(conn, "P_SUPPLY_CYCLE", "P_SUPPLY_CYCLE", None,
+                      "<=7", "<=14", ">14", "erp", "monthly")
+
+    # 3.2 产能利用率
+    insert_kpi(conn,
+        is_system=0,
+        kpi_code="P_CAPACITY_UTIL",
+        kpi_name="产能利用率",
+        dimension="process",
+        category="supply_chain",
+        formula="实际产出/理论产能",
+        formula_desc="CMA标准产能利用率指标，反映生产资源利用效率",
+        unit="%",
+        target_value=85.0,
+        threshold_green=">85",
+        threshold_yellow=">70",
+        threshold_red="<=70",
+        data_source_type="erp",
+        frequency="monthly",
+        status="active",
+        epic="Epic2",
+        created_at=datetime.now(),
+        updated_at=datetime.now(),
+    )
+
+    # 3.3 研发投入占比
+    insert_kpi(conn,
+        is_system=0,
+        kpi_code="P_RD_RATIO",
+        kpi_name="研发投入占比",
+        dimension="process",
+        category="innovation",
+        formula="研发费用/收入",
+        formula_desc="CMA标准研发投入占比指标，衡量创新投入力度",
+        unit="%",
+        target_value=5.0,
+        threshold_green=">5",
+        threshold_yellow=">2",
+        threshold_red="<=2",
+        data_source_type="erp",
+        frequency="monthly",
+        status="active",
+        epic="Epic2",
+        created_at=datetime.now(),
+        updated_at=datetime.now(),
+    )
+
+    # =========================================================
+    # 任务4: 新增学习P1级KPI（2个）
+    # =========================================================
+    log("\n【任务4】新增学习P1级KPI")
+    print("-" * 50)
+
+    # 4.1 激活L_INNOVATION_COUNT模板
+    log("  --- 激活模板: L_INNOVATION_COUNT (创新提案数量)")
+    activate_template(conn, "L_INNOVATION_COUNT", "L_INNOVATION_COUNT", None,
+                      ">=12", ">=6", "<6", "manual", "monthly")
+
+    # 4.2 战略认知度
+    insert_kpi(conn,
+        is_system=0,
+        kpi_code="L_STRATEGY_AWARE",
+        kpi_name="战略认知度",
+        dimension="learning",
+        category="employee_engagement",
+        formula="员工战略理解度评分",
+        formula_desc="CMA标准战略认知度指标，通过员工调研获取",
+        unit="分",
+        target_value=80.0,
+        threshold_green=">80",
+        threshold_yellow=">60",
+        threshold_red="<=60",
+        data_source_type="manual",
+        frequency="quarterly",
+        status="active",
+        epic="Epic2",
+        created_at=datetime.now(),
+        updated_at=datetime.now(),
+    )
+
+    # =========================================================
+    # 提交事务
+    # =========================================================
+    conn.commit()
+
+    # 统计
+    total = conn.execute(text("SELECT COUNT(*) FROM kpi_definitions WHERE status='active'")).scalar()
+    by_dim = conn.execute(text(
+        "SELECT dimension, COUNT(*) FROM kpi_definitions WHERE status='active' GROUP BY dimension ORDER BY dimension"
+    )).fetchall()
+    no_threshold = conn.execute(text(
+        "SELECT kpi_code, kpi_name FROM kpi_definitions WHERE status='active' AND (threshold_green IS NULL OR threshold_yellow IS NULL OR threshold_red IS NULL)"
+    )).fetchall()
+
+    print("\n" + "=" * 70)
+    log(f"✅ 任务1~4完成！KPI字典共 {total} 条")
+    for d, c in by_dim:
+        print(f"   {d}: {c} 条")
+    if no_threshold:
+        print(f"\n⚠️  以下KPI仍缺阈值:")
+        for code, name in no_threshold:
+            print(f"   {code}: {name}")
+    else:
+        print("\n✅ 所有KPI均有阈值配置")
+    print("=" * 70)

backend/scripts/migrate_kpi_codes.py

@@ -0,0 +1,75 @@
+"""迁移脚本：更新现有战略地图KPI codes + 关联所有活跃KPI到地图"""
+from app.database import get_engine
+from sqlalchemy import text
+import json
+
+def migrate():
+    e = get_engine()
+    with e.begin() as c:
+        # 1. 更新现有地图的dimensions → 使用真实KPI codes
+        maps = c.execute(text('SELECT id, dimensions FROM strategic_maps')).fetchall()
+        for mid, dims_json in maps:
+            if not dims_json:
+                continue
+            dims = json.loads(dims_json) if isinstance(dims_json, str) else dims_json
+            
+            # 定义层→节点名→真实KPI code的映射
+            name_to_kpi = {
+                # 财务层
+                "营收目标": ["F_REVENUE"],
+                "净利润率": ["F_NET_PROFIT"],
+                "现金流": ["F_OP_CFLOW"],
+                # 客户层
+                "客户满意度": ["C_SATISFACTION"],
+                "市场份额": ["C_MARKET_SHARE"],
+                "客户保留率": ["C_RETENTION_RATE"],
+                # 流程层
+                "运营效率": ["P_DELIVERY"],
+                "质量合格率": ["P_PASS_RATE"],
+                # 学习层
+                "关键岗位胜任度": ["L_COMPETENCY"],
+                "培训完成率": ["L_TRAINING"],
+            }
+            
+            updated = False
+            for dim in dims:
+                for obj in dim.get("objectives", []):
+                    name = obj.get("name", "")
+                    if name in name_to_kpi:
+                        real_kpis = name_to_kpi[name]
+                        if obj.get("kpis") != real_kpis:
+                            obj["kpis"] = real_kpis
+                            updated = True
+            
+            if updated:
+                c.execute(
+                    text("UPDATE strategic_maps SET dimensions = :dims WHERE id = :mid"),
+                    {"dims": json.dumps(dims, ensure_ascii=False), "mid": mid},
+                )
+                print(f"✅ 地图 {mid}: dimensions KPI codes 已更新")
+
+        # 2. 将所有活跃KPI的map_id更新为1
+        result = c.execute(
+            text("UPDATE kpi_definitions SET map_id = 1 WHERE status = 'active' AND (map_id IS NULL OR map_id != 1)")
+        )
+        affected = result.rowcount
+        print(f"✅ 已更新 {affected} 个活跃KPI的 map_id → 1")
+
+        # 3. 验证
+        total = c.execute(text("SELECT COUNT(*) FROM kpi_definitions WHERE status='active' AND map_id = 1")).scalar()
+        print(f"📊 活跃KPI关联到地图1的数量: {total}")
+
+        kpis_with_data = c.execute(text("""
+            SELECT k.kpi_code, k.kpi_name 
+            FROM kpi_definitions k
+            WHERE EXISTS (
+                SELECT 1 FROM kpi_values v WHERE v.kpi_id = k.id
+            ) AND k.map_id = 1
+            ORDER BY k.kpi_code
+        """)).fetchall()
+        print(f"📊 有历史数据的KPI ({len(kpis_with_data)}个):")
+        for r in kpis_with_data:
+            print(f"   {r.kpi_code} - {r.kpi_name}")
+
+if __name__ == "__main__":
+    migrate()

backend/scripts/seed_p2_causality.py

@@ -0,0 +1,203 @@
+"""P2阶段: 预设KPI因果链（基于CMA四层因果链模型）
+学习成长→内部流程→客户→财务
+"""
+import sys, os
+sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
+
+from app.database import get_engine
+from sqlalchemy import text
+
+# 基于CMA四层因果链模型的预设因果关系
+PRESET_CAUSALITIES = [
+    # ===== 学习成长 → 内部流程 =====
+    # 培训完成率 → 过程合格率
+    {"source": "L_TRAINING", "target": "P_PASS_RATE", "strength": 0.6, "lag": 2, "direction": "positive", "formula": "培训提升技能→过程质量提升"},
+    # 人均培训时长 → 缺陷率（负相关）
+    {"source": "L_TRAINING_HOURS", "target": "P_BUG_RATE", "strength": 0.5, "lag": 2, "direction": "negative", "formula": "更多培训→更少缺陷"},
+    # 员工满意度 → 返工率（负相关）
+    {"source": "L_EMPLOYEE_SAT", "target": "P_REWORK_RATE", "strength": 0.4, "lag": 1, "direction": "negative", "formula": "员工满意→更少返工"},
+    # 关键技术掌握率 → 交付及时率
+    {"source": "L_TECH_COVERAGE", "target": "P_DELIVERY", "strength": 0.7, "lag": 1, "direction": "positive", "formula": "技术掌握→交付提升"},
+    # 关键岗位胜任度 → 过程合格率
+    {"source": "L_COMPETENCY", "target": "P_PASS_RATE", "strength": 0.6, "lag": 1, "direction": "positive", "formula": "胜任度→质量提升"},
+    # 创新提案数量 → 新产品收入占比
+    {"source": "L_INNOVATION_COUNT", "target": "P_NEW_PROD_RATIO", "strength": 0.5, "lag": 3, "direction": "positive", "formula": "创新提案→新产品上市"},
+    # 数据自动化率 → 交付及时率
+    {"source": "L_DATA_AUTO_RATE", "target": "P_DELIVERY", "strength": 0.3, "lag": 1, "direction": "positive", "formula": "自动化→效率提升"},
+    # 系统覆盖率 → 供应链响应周期
+    {"source": "L_SYS_COVERAGE", "target": "P_SUPPLY_CYCLE", "strength": 0.4, "lag": 3, "direction": "negative", "formula": "系统覆盖→周期缩短"},
+    # 战略认知度 → 新产品收入占比
+    {"source": "L_STRATEGY_AWARE", "target": "P_NEW_PROD_RATIO", "strength": 0.3, "lag": 2, "direction": "positive", "formula": "战略理解→创新聚焦"},
+
+    # ===== 内部流程 → 客户 =====
+    # 过程合格率 → 客户满意度
+    {"source": "P_PASS_RATE", "target": "C_SATISFACTION", "strength": 0.7, "lag": 1, "direction": "positive", "formula": "质量提升→客户满意"},
+    # 交付及时率 → 客户满意度
+    {"source": "P_DELIVERY", "target": "C_SATISFACTION", "strength": 0.6, "lag": 0, "direction": "positive", "formula": "及时交付→客户满意"},
+    # 缺陷率 → 客户满意度（负相关）
+    {"source": "P_BUG_RATE", "target": "C_SATISFACTION", "strength": 0.5, "lag": 1, "direction": "negative", "formula": "缺陷多→不满意"},
+    # 返工率 → 客户满意度（负相关）
+    {"source": "P_REWORK_RATE", "target": "C_SATISFACTION", "strength": 0.3, "lag": 1, "direction": "negative", "formula": "返工多→不满意"},
+    # 供应链响应周期 → 交付及时率（负相关）
+    {"source": "P_SUPPLY_CYCLE", "target": "P_DELIVERY", "strength": 0.5, "lag": 1, "direction": "negative", "formula": "周期长→交付慢"},
+    # 产能利用率 → 交付及时率
+    {"source": "P_CAPACITY_UTIL", "target": "P_DELIVERY", "strength": 0.4, "lag": 0, "direction": "positive", "formula": "产能足→交付快"},
+    # 新产品收入占比 → 市场份额
+    {"source": "P_NEW_PROD_RATIO", "target": "C_MARKET_SHARE", "strength": 0.5, "lag": 3, "direction": "positive", "formula": "创新产品→市场占有率提升"},
+
+    # ===== 客户 → 财务 =====
+    # 客户满意度 → 客户保留率
+    {"source": "C_SATISFACTION", "target": "C_RETENTION_RATE", "strength": 0.8, "lag": 1, "direction": "positive", "formula": "满意→留存"},
+    # 客户满意度 → 营业收入
+    {"source": "C_SATISFACTION", "target": "F_REVENUE", "strength": 0.5, "lag": 2, "direction": "positive", "formula": "满意客户→复购增加"},
+    # 客户保留率 → 营业收入
+    {"source": "C_RETENTION_RATE", "target": "F_REVENUE", "strength": 0.6, "lag": 1, "direction": "positive", "formula": "老客户留存→稳定收入"},
+    # 客户保留率 → 客户生命周期价值
+    {"source": "C_RETENTION_RATE", "target": "C_LTV", "strength": 0.7, "lag": 2, "direction": "positive", "formula": "高留存→生命周期延长"},
+    # 新客户数 → 营业收入
+    {"source": "C_NEW_CLIENTS", "target": "F_REVENUE", "strength": 0.4, "lag": 1, "direction": "positive", "formula": "新客户→收入增长"},
+    # 市场份额 → 营业收入
+    {"source": "C_MARKET_SHARE", "target": "F_REVENUE", "strength": 0.5, "lag": 1, "direction": "positive", "formula": "市场扩大→收入增加"},
+    # 获客成本 → 净利润（负相关）
+    {"source": "C_ACQUISITION_COST", "target": "F_NET_PROFIT", "strength": 0.3, "lag": 1, "direction": "negative", "formula": "获客成本高→利润减少"},
+    # 客户集中度 → 净利润（负相关）
+    {"source": "C_CUST_CONCENTRATION", "target": "F_NET_PROFIT", "strength": 0.3, "lag": 1, "direction": "negative", "formula": "集中度高→风险增大"},
+
+    # ===== 财务内部因果 =====
+    # 营业收入 → 净利润
+    {"source": "F_REVENUE", "target": "F_NET_PROFIT", "strength": 0.7, "lag": 0, "direction": "positive", "formula": "收入增长→利润增加"},
+    # 毛利率 → 净利润
+    {"source": "F_GROSS_MARGIN", "target": "F_NET_PROFIT", "strength": 0.6, "lag": 0, "direction": "positive", "formula": "毛利提升→利润增加"},
+    # 费用率 → 净利润（负相关）
+    {"source": "F_COST_RATIO", "target": "F_NET_PROFIT", "strength": 0.5, "lag": 0, "direction": "negative", "formula": "费用高→利润减少"},
+    # 收入增长率 → 营业收入
+    {"source": "F_REVENUE_GROWTH", "target": "F_REVENUE", "strength": 0.8, "lag": 1, "direction": "positive", "formula": "增长加速→收入提升"},
+    # 净利润 → 经济增加值
+    {"source": "F_NET_PROFIT", "target": "F_EVA", "strength": 0.9, "lag": 0, "direction": "positive", "formula": "净利润→经济增加值"},
+    # 经营性现金流 → 净利润（滞后反馈）
+    {"source": "F_OP_CFLOW", "target": "F_NET_PROFIT", "strength": 0.4, "lag": 1, "direction": "positive", "formula": "现金充裕→运营改善"},
+    # 产品合格率 → 返工率（负相关）
+    {"source": "F_QUALITY_RATE", "target": "F_REWORK_RATE", "strength": 0.6, "lag": 1, "direction": "negative", "formula": "合格率高→返工少"},
+    # 应收账款周转天数 → 经营性现金流（负相关）
+    {"source": "F_AR_DAYS", "target": "F_OP_CFLOW", "strength": 0.5, "lag": 1, "direction": "negative", "formula": "回款慢→现金流紧张"},
+    # 流动比率 → 资产负债率
+    {"source": "F_CURRENT_RATIO", "target": "F_DEBT_RATIO", "strength": 0.3, "lag": 1, "direction": "negative", "formula": "流动性强→负债率低"},
+
+    # ===== 客户生命周期价值 =====
+    # 净推荐值(NPS) → 客户保留率
+    {"source": "C_NPS", "target": "C_RETENTION_RATE", "strength": 0.6, "lag": 1, "direction": "positive", "formula": "NPS高→留存好"},
+    # 客户生命周期价值 → 净利润
+    {"source": "C_LTV", "target": "F_NET_PROFIT", "strength": 0.5, "lag": 1, "direction": "positive", "formula": "客户终身价值→长期利润"},
+]
+
+
+def seed_causalities():
+    engine = get_engine()
+    with engine.connect() as conn:
+        # 先构建KPI代码→ID映射
+        kpis = conn.execute(
+            text("SELECT id, kpi_code FROM kpi_definitions WHERE status='active'")
+        ).fetchall()
+        code_to_id = {r.kpi_code: r.id for r in kpis}
+
+        inserted = 0
+        skipped = 0
+        for item in PRESET_CAUSALITIES:
+            src_id = code_to_id.get(item["source"])
+            tgt_id = code_to_id.get(item["target"])
+            if not src_id:
+                print(f"  ⚠️ 源KPI不存在: {item['source']}")
+                skipped += 1
+                continue
+            if not tgt_id:
+                print(f"  ⚠️ 目标KPI不存在: {item['target']}")
+                skipped += 1
+                continue
+
+            # 检查是否已存在
+            existing = conn.execute(
+                text("SELECT id FROM kpi_causality WHERE source_kpi_id=:src AND target_kpi_id=:tgt"),
+                {"src": src_id, "tgt": tgt_id},
+            ).fetchone()
+            if existing:
+                skipped += 1
+                continue
+
+            conn.execute(
+                text("""INSERT INTO kpi_causality 
+                    (source_kpi_id, target_kpi_id, strength, lag_months, formula, direction)
+                    VALUES (:src, :tgt, :strength, :lag, :formula, :dir)"""),
+                {
+                    "src": src_id, "tgt": tgt_id,
+                    "strength": item["strength"],
+                    "lag": item["lag"],
+                    "formula": item["formula"],
+                    "dir": item["direction"],
+                },
+            )
+            inserted += 1
+
+        conn.commit()
+    print(f"因果链: 新增{inserted}, 跳过{skipped}")
+    return inserted
+
+
+def seed_bi_templates():
+    engine = get_engine()
+    PRESET_TEMPLATES = [
+        {
+            "name": "四层指标总览",
+            "report_type": "overview",
+            "is_system": 1,
+            "config": '{"description":"展示财务/客户/流程/学习四层维度KPI概览","layout":"grid","dimensions":["finance","customer","process","learning"],"metrics":["count","avg_value","alert_count"],"chart_type":"gauge_card"}',
+        },
+        {
+            "name": "同比趋势分析",
+            "report_type": "trend",
+            "is_system": 1,
+            "config": '{"description":"各KPI近12个月趋势对比","period":"monthly","window_months":12,"chart_type":"line","show_compare":true}',
+        },
+        {
+            "name": "实际vs预算对比",
+            "report_type": "comparison",
+            "is_system": 1,
+            "config": '{"description":"KPI实际值vs目标值偏差分析","chart_type":"bar","show_deviation":true,"group_by":"dimension"}',
+        },
+        {
+            "name": "TOP N异常KPI",
+            "report_type": "topn",
+            "is_system": 1,
+            "config": '{"description":"排名前N的异常KPI红黄灯","top_n":10,"sort_by":"deviation","chart_type":"horizontal_bar","show_threshold":true}',
+        },
+        {
+            "name": "因果链推演",
+            "report_type": "causality",
+            "is_system": 1,
+            "config": '{"description":"基于KPI因果链推演分析","chart_type":"force_graph","max_depth":3,"min_strength":0.3}',
+        },
+    ]
+
+    with engine.connect() as conn:
+        inserted = 0
+        for tpl in PRESET_TEMPLATES:
+            existing = conn.execute(
+                text("SELECT id FROM bi_report_templates WHERE name=:name AND is_system=1"),
+                {"name": tpl["name"]},
+            ).fetchone()
+            if existing:
+                continue
+            conn.execute(
+                text("INSERT INTO bi_report_templates (name, report_type, config, is_system) VALUES (:name, :type, :cfg, 1)"),
+                {"name": tpl["name"], "type": tpl["report_type"], "cfg": tpl["config"]},
+            )
+            inserted += 1
+        conn.commit()
+    print(f"报表模板: 新增{inserted}")
+    return inserted
+
+
+if __name__ == "__main__":
+    print("=== 种子数据初始化 ===\n")
+    seed_causalities()
+    seed_bi_templates()
+    print("\n完成!")

backend/scripts/seed_p2_kpis.py

@@ -0,0 +1,120 @@
+"""P2阶段: 新增4个高级KPI"""
+import sys, os
+sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
+
+from app.database import get_engine
+from sqlalchemy import text
+
+NEW_KPIS = [
+    {
+        "kpi_code": "C_LTV",
+        "kpi_name": "客户生命周期价值",
+        "dimension": "customer",
+        "category": "customer_scale",
+        "objective": "提升客户长期价值",
+        "formula": "Σ(每年贡献利润×折现率)",
+        "formula_desc": "客户全周期内贡献的净利润折现总和",
+        "data_source_type": "manual",
+        "frequency": "quarterly",
+        "unit": "万元",
+        "target_value": 15.0,
+        "threshold_green": ">=10",
+        "threshold_yellow": ">=5",
+        "threshold_red": "<=5",
+        "responsible_dept": "市场营销部",
+        "responsible_user": "市场总监",
+        "epic": "Epic2",
+        "status": "active",
+    },
+    {
+        "kpi_code": "P_NEW_PROD_RATIO",
+        "kpi_name": "新产品收入占比",
+        "dimension": "process",
+        "category": "innovation",
+        "objective": "促进产品创新",
+        "formula": "新产品收入/总收入×100%",
+        "formula_desc": "近12个月上市的新产品收入占总收入比例",
+        "data_source_type": "erp",
+        "frequency": "monthly",
+        "unit": "%",
+        "target_value": 25.0,
+        "threshold_green": ">20",
+        "threshold_yellow": ">10",
+        "threshold_red": "<=10",
+        "responsible_dept": "产品研发部",
+        "responsible_user": "产品总监",
+        "epic": "Epic2",
+        "status": "active",
+    },
+    {
+        "kpi_code": "L_DATA_AUTO_RATE",
+        "kpi_name": "数据自动化率",
+        "dimension": "learning",
+        "category": "innovation",
+        "objective": "提升数据管理效率",
+        "formula": "自动报表数/总报表数×100%",
+        "formula_desc": "已实现自动化生成的管理报表占总报表数的比例",
+        "data_source_type": "manual",
+        "frequency": "monthly",
+        "unit": "%",
+        "target_value": 75.0,
+        "threshold_green": ">70",
+        "threshold_yellow": ">50",
+        "threshold_red": "<=50",
+        "responsible_dept": "信息技术部",
+        "responsible_user": "CIO",
+        "epic": "Epic2",
+        "status": "active",
+    },
+    {
+        "kpi_code": "L_SYS_COVERAGE",
+        "kpi_name": "系统覆盖率",
+        "dimension": "learning",
+        "category": "innovation",
+        "objective": "推动管理信息化",
+        "formula": "信息化覆盖业务环节数/总业务环节数×100%",
+        "formula_desc": "已实现信息系统支持的核心业务环节占总环节数的比例",
+        "data_source_type": "manual",
+        "frequency": "quarterly",
+        "unit": "%",
+        "target_value": 85.0,
+        "threshold_green": ">80",
+        "threshold_yellow": ">60",
+        "threshold_red": "<=60",
+        "responsible_dept": "信息技术部",
+        "responsible_user": "CIO",
+        "epic": "Epic2",
+        "status": "active",
+    },
+]
+
+
+def seed_p2_kpis():
+    engine = get_engine()
+    with engine.connect() as conn:
+        inserted = 0
+        skipped = 0
+        for kpi in NEW_KPIS:
+            exists = conn.execute(
+                text("SELECT id FROM kpi_definitions WHERE kpi_code=:code"),
+                {"code": kpi["kpi_code"]},
+            ).fetchone()
+            if exists:
+                print(f"  ⏭️ 跳过已存在: {kpi['kpi_code']} (id={exists[0]})")
+                skipped += 1
+                continue
+
+            cols = ", ".join(kpi.keys())
+            vals = ", ".join(f":{k}" for k in kpi.keys())
+            conn.execute(text(f"INSERT INTO kpi_definitions ({cols}) VALUES ({vals})"), kpi)
+            new_id = conn.execute(text("SELECT LAST_INSERT_ID()")).scalar()
+            print(f"  ✅ 新增: {kpi['kpi_code']} - {kpi['kpi_name']} (id={new_id})")
+            inserted += 1
+
+        conn.commit()
+    print(f"\n总计: 新增{inserted}, 跳过{skipped}")
+    return inserted
+
+
+if __name__ == "__main__":
+    seed_p2_kpis()

backend/scripts/verify_alert_rules.py

@@ -0,0 +1,49 @@
+"""验证预警规则系统"""
+import sys, os, json
+sys.path.insert(0, '/root/cma-management/backend')
+os.chdir('/root/cma-management/backend')
+from dotenv import load_dotenv
+load_dotenv()
+from app.database import get_session_local
+from app.models import KPIDefinition
+from sqlalchemy import text, func
+
+db = get_session_local()()
+
+# 检查 alert_rules 表
+try:
+    total = db.execute(text("SELECT COUNT(*) FROM alert_rules")).scalar()
+    type_counts = db.execute(text("SELECT rule_type, COUNT(*) FROM alert_rules GROUP BY rule_type")).fetchall()
+    print(f"Total alert rules: {total}")
+    for t, c in type_counts:
+        print(f"  {t}: {c}")
+except Exception as e:
+    print(f"表不存在: {e}")
+
+# 检查 dynamic_threshold_cache
+try:
+    dc = db.execute(text("SELECT COUNT(*) FROM dynamic_threshold_cache")).scalar()
+    print(f"Dynamic threshold caches: {dc}")
+except Exception as e:
+    print(f"dynamic_threshold_cache表不存在: {e}")
+
+# 取样显示预警规则
+try:
+    samples = db.execute(text("""
+        SELECT ar.id, ar.kpi_id, ar.rule_type, ar.enabled, ar.params, k.kpi_code, k.kpi_name
+        FROM alert_rules ar
+        LEFT JOIN kpi_definitions k ON k.id = ar.kpi_id
+        LIMIT 6
+    """)).fetchall()
+    print("\nSample rules:")
+    for s in samples:
+        print(f"  [{s.id}] {s.kpi_code}({s.kpi_name}) type={s.rule_type} enabled={s.enabled}")
+except Exception as e:
+    print(f"查询失败: {e}")
+
+# 总KPI数验证
+total_kpis = db.execute(text("SELECT COUNT(*) FROM kpi_definitions WHERE status='active'")).scalar()
+print(f"\nTotal active KPIs: {total_kpis}")
+
+db.close()
+print("\n✅ 验证完成")