如何开发人事及OA管理系统的绩效管理板块？（附架构图+流程图+代码参考）

mermaid
graph TD
  A[用户界面 - Web/移动] --> B(API 网关 / 后端)
  B --> C[绩效服务]
  B --> D[用户/组织服务]
  B --> E[审批/流程引擎]
  B --> F[统计/看板服务]
  C --> G[(PostgreSQL)]
  F --> H[(数据仓库 / OLAP)]
  I[消息队列 Kafka/RabbitMQ] --> C
  C --> I
  E --> C
  click G "db://postgres" "数据库"

mermaid
flowchart TD
  A[创建考核计划] --> B{是否发布？}
  B -- 否 --> A
  B -- 是 --> C[生成考核任务]
  C --> D[通知参评人]
  D --> E[自评提交]
  E --> F[主管评分]
  F --> G[互评（可选）]
  G --> H[HR复核]
  H --> I[面谈记录]
  I --> J[结果冻结与归档]
  J --> K[看板 & 导出 & 薪酬联动]

sql
-- 考核计划
CREATE TABLE perf_plan (
  id SERIAL PRIMARY KEY,
  name TEXT NOT NULL,
  template_id INT,
  start_date DATE NOT NULL,
  end_date DATE NOT NULL,
  status TEXT NOT NULL, -- draft,published,closed
  config JSONB, -- 存储维度/权重/公式等
  created_by INT,
  created_at TIMESTAMP DEFAULT now()
);
-- 参评任务（计划生成后）
CREATE TABLE perf_task (
  id SERIAL PRIMARY KEY,
  plan_id INT REFERENCES perf_plan(id),
  employee_id INT,
  manager_id INT,
  status TEXT, -- pending,completed,locked
  created_at TIMESTAMP DEFAULT now()
);
-- 评分记录（每个评分维度一条或一组）
CREATE TABLE perf_score (
  id SERIAL PRIMARY KEY,
  task_id INT REFERENCES perf_task(id),
  rater_id INT,
  role TEXT, -- self,manager,peer,hr
  scores JSONB, -- {"kpi_sales": 80, "kpi_quality": 90}
  total_score NUMERIC,
  comment TEXT,
  created_at TIMESTAMP DEFAULT now()
);
-- 审计日志
CREATE TABLE perf_audit (
  id SERIAL PRIMARY KEY,
  entity TEXT,
  entity_id INT,
  action TEXT,
  before JSONB,
  after JSONB,
  operator INT,
  created_at TIMESTAMP DEFAULT now()
);

ts
// app.ts (简化)
import express from 'express';
import bodyParser from 'body-parser';
import { createPlan, submitScore, getDashboard } from './controllers/perf';
const app = express();
app.use(bodyParser.json());
app.post('/api/perf/plan', createPlan);
app.post('/api/perf/task/:taskId/score', submitScore);
app.get('/api/perf/dashboard', getDashboard);
app.listen(3000, ()=>console.log('perf service on 3000'));

ts
// controllers/perf.ts
import { db } from '../db';
export async function createPlan(req, res) {
  const { name, start_date, end_date, config } = req.body;
  // 简化：插入并返回
  const plan = await db.query(
    `INSERT INTO perf_plan(name,start_date,end_date,status,config,created_by) VALUES($1,$2,$3,'draft',$4,$5) RETURNING *`,
    [name, start_date, end_date, config, req.user.id]
  );
  res.json(plan.rows[0]);
}
export async function submitScore(req, res) {
  const taskId = req.params.taskId;
  const { role, scores, comment } = req.body;
  // 计算 total_score 由服务端按 config 进行
  const total = computeTotalScore(taskId, scores);
  await db.query(
    `INSERT INTO perf_score(task_id, rater_id, role, scores, total_score, comment) VALUES($1,$2,$3,$4,$5,$6)`,
    [taskId, req.user.id, role, JSON.stringify(scores), total, comment]
  );
  // 写审计
  res.json({ ok: true });
}
export async function getDashboard(req, res) {
  // 简化的聚合：最新周期平均分、待办数
  const avg = await db.query('SELECT AVG(total_score) FROM perf_score WHERE created_at > now() - interval \'90 days\'');
  const pending = await db.query('SELECT count(*) FROM perf_task WHERE status = $1', ['pending']);
  res.json({ avg: avg.rows[0].avg, pending: pending.rows[0].count });
}
function computeTotalScore(taskId, scores) {
  // 伪：在真实系统要读取 plan.config 中权重并计算
  let total = 0;
  let count = 0;
  for (const k in scores) { total += scores[k]; count++; }
  return total / Math.max(count,1);
}

jsx
// ScoreSheet.jsx (简化)
function ScoreSheet({taskId, config}) {
  const [scores, setScores] = useState({});
  function onChange(k,v){ setScores(prev=>({...prev,[k]:v})); }
  async function submit(){ await api.post(`/api/perf/task/${taskId}/score`, {scores, role:'manager'}); }
  return (
    <div>
      {config.dimensions.map(d => (
        <div key={d.key}>
          <label>{d.name}</label>
          <input type="number" min="0" max="100" value={scores[d.key]||0}
                 onChange={e=>onChange(d.key, Number(e.target.value))}/>
        </div>
      ))}
      <button onClick={submit}>提交评分</button>
    </div>
  );
}

js
function aggregateScores(allScores, config) {
  // allScores: [{role:'self', scores:{kpi_sales:80,...}}, {...}]
  const dimWeight = {};
  config.dimensions.forEach(d=>dimWeight[d.key]=d.weight);
  // 先按 role 求维度分
  const roleAgg = {};
  for (const s of allScores) {
    for (const k in s.scores) {
      roleAgg[s.role] = roleAgg[s.role] || {};
      roleAgg[s.role][k] = (roleAgg[s.role][k] || 0) + s.scores[k];
      // 注意：如果多个评审同 role，需要取平均，这里省略细节
    }
  }
  // 按维度先合并 role，再总合
  let totalScore = 0;
  for (const d of config.dimensions) {
    let dimScore = 0;
    for (const role in roleAgg) {
      const roleWeight = config.rolesWeight[role] || 0;
      dimScore += (roleAgg[role][d.key] || 0) * roleWeight;
    }
    totalScore += dimScore * d.weight;
  }
  return totalScore;
}