feat: 店长工作台新增人力排班Tab及概览折叠功能
- 后端新增 /api/stores/:code/staffing 路由，返回人工成本概览、按星期/餐段排班建议、日营收明细、综合诊断 - 前端 StorePage 新增 staffing Tab，展示 MetricCard 概览、优化建议、排班图表、诊断算法说明 - 修复公司均值人工率被异常门店污染问题（过滤 wage_rate_pct > 100） - 诊断逻辑改为与公司均值动态比较，建议人工率改为动态计算 - 增强任务反馈表单（执行证据、未完成原因、下一步计划） - 点击非概览Tab时自动折叠上方概况区域
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freedakgmail
@@ -730,6 +730,201 @@ router.get('/stores/:code/anomalies', async (req: AuthRequest, res) => {
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} catch (err: any) { sendError(res, err.message) }
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})
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// 门店人力排班分析
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router.get('/stores/:code/staffing', async (req: AuthRequest, res) => {
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try {
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const code = req.params.code
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const monthStart = parseMonth(req)
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// 1. 门店人工成本概览
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const expenseResult = await query(`
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SELECT
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sales_store_code, sales_store_name,
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wage_expense,
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wage_rate_pct,
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received,
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bill_count,
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area_sqm,
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round(received / nullif(wage_expense, 0), 2) AS revenue_per_wage,
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round(wage_expense / nullif(bill_count, 0), 2) AS wage_per_bill
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FROM analytics.mv_store_operating_expense_monthly
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WHERE report_month = $1::date AND sales_store_code = $2
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`, [monthStart, code])
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// 2. 公司均值
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const avgResult = await query(`
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SELECT
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round(avg(wage_expense), 2) AS avg_wage,
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round(avg(wage_rate_pct), 2) AS avg_wage_rate,
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round(avg(received), 2) AS avg_received,
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round(avg(bill_count), 0) AS avg_bills,
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round(avg(received / nullif(wage_expense, 0)), 2) AS avg_rev_per_wage
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FROM analytics.mv_store_operating_expense_monthly
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WHERE report_month = $1::date AND wage_expense > 0 AND wage_rate_pct <= 100
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`, [monthStart])
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// 3. 按星期分析营收和账单
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const weekdayResult = await query(`
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SELECT
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extract(dow FROM business_date)::int AS dow,
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CASE extract(dow FROM business_date)
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WHEN 0 THEN '周日' WHEN 1 THEN '周一' WHEN 2 THEN '周二'
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WHEN 3 THEN '周三' WHEN 4 THEN '周四' WHEN 5 THEN '周五'
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WHEN 6 THEN '周六'
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END AS weekday,
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count(*) AS days,
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round(avg(received), 2) AS avg_received,
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round(avg(bill_count), 0) AS avg_bills,
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round(max(received), 2) AS max_received,
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round(min(received), 2) AS min_received,
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round(sum(received), 2) AS total_received,
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round(sum(bill_count), 0) AS total_bills
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FROM analytics.v_store_daily
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WHERE store_code = $1
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AND business_date >= $2::date AND business_date < $2::date + interval '1 month'
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GROUP BY 1, 2
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ORDER BY 1
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`, [code, monthStart])
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// 4. 餐段分布
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const mealResult = await query(`
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SELECT meal_period, bill_count, received, round(avg_bill, 2) AS avg_bill
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FROM analytics.v_store_meal_opportunity
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WHERE store_code = $1
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ORDER BY received DESC
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`, [code])
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// 5. 日营收明细（用于排班热力图）
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const dailyResult = await query(`
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SELECT
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business_date,
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to_char(business_date, 'Dy') AS dow_short,
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extract(dow FROM business_date)::int AS dow,
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round(received, 2) AS received,
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bill_count,
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round(received / nullif(bill_count, 0), 2) AS avg_bill_value
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FROM analytics.v_store_daily
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WHERE store_code = $1
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AND business_date >= $2::date AND business_date < $2::date + interval '1 month'
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ORDER BY business_date
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`, [code, monthStart])
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const store = expenseResult.rows[0] || {}
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const avg = avgResult.rows[0] || {}
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const weekdays = weekdayResult.rows
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const meals = mealResult.rows
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const daily = dailyResult.rows
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// 6. 计算排班建议
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const avgWageRate = Number(avg.avg_wage_rate) || 25
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const storeWageRate = Number(store.wage_rate_pct) || 0
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const suggestedWageRate = Math.max(20, Math.round((avgWageRate - 3) * 10) / 10)
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const suggestedWage = Number(store.received || 0) * suggestedWageRate / 100
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const wageSavings = Number(store.wage_expense || 0) - suggestedWage
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const savingsPct = Number(store.wage_expense) > 0
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? Math.round((wageSavings / Number(store.wage_expense)) * 100 * 10) / 10
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: 0
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// 按星期分布生成排班建议
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const maxDayRev = Math.max(...weekdays.map((w: any) => Number(w.avg_received)))
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const minDayRev = Math.min(...weekdays.map((w: any) => Number(w.avg_received)))
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const avgDayRev = weekdays.reduce((s: number, w: any) => s + Number(w.avg_received), 0) / (weekdays.length || 1)
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const staffingSuggestions = weekdays.map((w: any) => {
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const ratio = Number(w.avg_received) / avgDayRev
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let level: string, action: string
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if (ratio > 1.1) {
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level = '高峰'
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action = '建议满编排班，确保出餐效率'
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} else if (ratio < 0.85) {
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level = '低谷'
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action = '建议减少1-2人排班，控制人力成本'
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} else {
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level = '正常'
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action = '建议标准排班'
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}
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return {
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...w,
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staffing_level: level,
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staffing_action: action,
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suggested_headcount_ratio: Math.round(ratio * 100),
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}
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})
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// 餐段排班建议
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const totalMealBills = meals.reduce((s: number, m: any) => s + Number(m.bill_count), 0)
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const mealSuggestions = meals.map((m: any) => {
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const share = totalMealBills > 0 ? Number(m.bill_count) / totalMealBills : 0
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let level: string, action: string
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if (share > 0.4) {
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level = '主力时段'
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action = '建议安排全量人员，前厅后厨满编'
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} else if (share > 0.2) {
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level = '次高峰'
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action = '建议安排80%人员，保证出餐速度'
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} else if (share > 0.05) {
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level = '辅助时段'
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action = '建议安排50%人员，控制人力投入'
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} else {
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level = '低谷时段'
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action = '建议安排值班人员即可，可安排备料和清洁'
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}
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return {
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...m,
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bill_share_pct: Math.round(share * 1000) / 10,
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staffing_level: level,
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staffing_action: action,
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}
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})
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// 综合诊断
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const diagnosis: string[] = []
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if (storeWageRate > 35) {
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diagnosis.push(`人工成本率 ${storeWageRate}% 严重偏高，公司均值 ${avgWageRate}%，需立即优化排班`)
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} else if (storeWageRate > avgWageRate + 3) {
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diagnosis.push(`人工成本率 ${storeWageRate}% 高于公司均值 ${avgWageRate}%，建议优化排班结构`)
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} else if (storeWageRate > 0) {
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diagnosis.push(`人工成本率 ${storeWageRate}% 在合理范围内，公司均值 ${avgWageRate}%`)
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}
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if (maxDayRev > 0 && minDayRev > 0 && maxDayRev / minDayRev > 1.5) {
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const fmt = (v: number) => `¥${Math.round(v).toLocaleString()}`
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diagnosis.push(`日营收波动大（最高 ${fmt(maxDayRev)} vs 最低 ${fmt(minDayRev)}），建议差异化排班`)
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}
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if (wageSavings > 0) {
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const fmt = (v: number) => `¥${Math.round(v).toLocaleString()}`
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diagnosis.push(`按建议人工率 ${suggestedWageRate}% 测算，可节省人工成本 ${fmt(wageSavings)}（${savingsPct}%）`)
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}
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const peakMeal = mealSuggestions[0]
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if (peakMeal && peakMeal.bill_share_pct > 40) {
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diagnosis.push(`${peakMeal.meal_period}为绝对主力（占 ${peakMeal.bill_share_pct}%），建议集中人力保障`)
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}
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sendSuccess(res, {
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store,
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company_avg: avg,
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weekdays: staffingSuggestions,
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meals: mealSuggestions,
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daily,
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summary: {
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wage_expense: store.wage_expense,
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wage_rate_pct: store.wage_rate_pct,
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received: store.received,
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suggested_wage: Math.round(suggestedWage * 100) / 100,
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wage_savings: Math.round(wageSavings * 100) / 100,
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savings_pct: savingsPct,
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revenue_per_wage: store.revenue_per_wage,
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wage_per_bill: store.wage_per_bill,
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avg_wage_rate: avg.avg_wage_rate,
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avg_rev_per_wage: avg.avg_rev_per_wage,
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},
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diagnosis,
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})
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} catch (err: any) { sendError(res, err.message) }
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})
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// 区域汇总
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router.get('/region/summary', async (req: AuthRequest, res) => {
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try {
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