5df79d436f
1. DimensionAnalysisTab: Changed CPI fallback from 2.33 to 0 to match
ExecutiveSummaryTab calculation
2. ExecutiveSummaryTab: Fixed benchmark data for inverted metrics (CPI, Abandono)
- Values must be in ASCENDING order (p25 < p50 < p75 < p90)
- p25 = best performers (lowest CPI/abandono)
- p90 = worst performers (highest CPI/abandono)
- This fixes the visual comparison and gap calculation
Before: cpi { p25: 4.50, p50: 3.50, p75: 2.80, p90: 2.20 } (DESCENDING - wrong)
After: cpi { p25: 2.20, p50: 3.50, p75: 4.50, p90: 5.50 } (ASCENDING - correct)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
1275 lines
51 KiB
TypeScript
1275 lines
51 KiB
TypeScript
import React from 'react';
|
||
import { TrendingUp, TrendingDown, AlertTriangle, CheckCircle, Target, Activity, Clock, PhoneForwarded, Users, Bot, ChevronRight, BarChart3, Cpu, Map, Zap, Calendar } from 'lucide-react';
|
||
import type { AnalysisData, Finding, DrilldownDataPoint, HeatmapDataPoint } from '../../types';
|
||
import type { TabId } from '../DashboardHeader';
|
||
import {
|
||
Card,
|
||
Badge,
|
||
SectionHeader,
|
||
DistributionBar,
|
||
Stat,
|
||
} from '../ui';
|
||
import {
|
||
cn,
|
||
COLORS,
|
||
STATUS_CLASSES,
|
||
getStatusFromScore,
|
||
formatCurrency,
|
||
formatNumber,
|
||
formatPercent,
|
||
} from '../../config/designSystem';
|
||
|
||
interface ExecutiveSummaryTabProps {
|
||
data: AnalysisData;
|
||
onTabChange?: (tab: TabId) => void;
|
||
}
|
||
|
||
// ============================================
|
||
// BENCHMARKS DE INDUSTRIA
|
||
// ============================================
|
||
|
||
type IndustryKey = 'aerolineas' | 'telecomunicaciones' | 'banca' | 'utilities' | 'retail' | 'general';
|
||
|
||
interface BenchmarkMetric {
|
||
p25: number;
|
||
p50: number;
|
||
p75: number;
|
||
p90: number;
|
||
unidad: string;
|
||
invertida: boolean;
|
||
}
|
||
|
||
interface IndustryBenchmarks {
|
||
nombre: string;
|
||
fuente: string;
|
||
metricas: {
|
||
aht: BenchmarkMetric;
|
||
fcr: BenchmarkMetric;
|
||
abandono: BenchmarkMetric;
|
||
cpi: BenchmarkMetric;
|
||
};
|
||
}
|
||
|
||
const BENCHMARKS_INDUSTRIA: Record<IndustryKey, IndustryBenchmarks> = {
|
||
aerolineas: {
|
||
nombre: 'Aerolíneas',
|
||
fuente: 'COPC 2024, Dimension Data Global CX Report 2024',
|
||
metricas: {
|
||
aht: { p25: 320, p50: 380, p75: 450, p90: 520, unidad: 's', invertida: true },
|
||
fcr: { p25: 55, p50: 68, p75: 78, p90: 85, unidad: '%', invertida: false },
|
||
abandono: { p25: 2, p50: 5, p75: 8, p90: 12, unidad: '%', invertida: true },
|
||
cpi: { p25: 2.20, p50: 3.50, p75: 4.50, p90: 5.50, unidad: '€', invertida: true }
|
||
}
|
||
},
|
||
telecomunicaciones: {
|
||
nombre: 'Telecomunicaciones',
|
||
fuente: 'Contact Babel UK Report 2024, ICMI Benchmark Study',
|
||
metricas: {
|
||
aht: { p25: 380, p50: 420, p75: 500, p90: 600, unidad: 's', invertida: true },
|
||
fcr: { p25: 50, p50: 65, p75: 75, p90: 82, unidad: '%', invertida: false },
|
||
abandono: { p25: 2, p50: 6, p75: 10, p90: 15, unidad: '%', invertida: true },
|
||
cpi: { p25: 2.50, p50: 4.00, p75: 5.00, p90: 6.00, unidad: '€', invertida: true }
|
||
}
|
||
},
|
||
banca: {
|
||
nombre: 'Banca & Finanzas',
|
||
fuente: 'Deloitte Banking Benchmark 2024, McKinsey CX Survey',
|
||
metricas: {
|
||
aht: { p25: 280, p50: 340, p75: 420, p90: 500, unidad: 's', invertida: true },
|
||
fcr: { p25: 58, p50: 72, p75: 82, p90: 88, unidad: '%', invertida: false },
|
||
abandono: { p25: 1, p50: 4, p75: 6, p90: 10, unidad: '%', invertida: true },
|
||
cpi: { p25: 2.80, p50: 4.50, p75: 6.00, p90: 7.50, unidad: '€', invertida: true }
|
||
}
|
||
},
|
||
utilities: {
|
||
nombre: 'Utilities & Energía',
|
||
fuente: 'Dimension Data 2024, Utilities CX Benchmark',
|
||
metricas: {
|
||
aht: { p25: 350, p50: 400, p75: 480, p90: 560, unidad: 's', invertida: true },
|
||
fcr: { p25: 52, p50: 67, p75: 77, p90: 84, unidad: '%', invertida: false },
|
||
abandono: { p25: 2, p50: 6, p75: 9, p90: 14, unidad: '%', invertida: true },
|
||
cpi: { p25: 2.00, p50: 3.30, p75: 4.20, p90: 5.20, unidad: '€', invertida: true }
|
||
}
|
||
},
|
||
retail: {
|
||
nombre: 'Retail & E-commerce',
|
||
fuente: 'Zendesk CX Trends 2024, Salesforce State of Service',
|
||
metricas: {
|
||
aht: { p25: 240, p50: 300, p75: 380, p90: 450, unidad: 's', invertida: true },
|
||
fcr: { p25: 60, p50: 73, p75: 82, p90: 89, unidad: '%', invertida: false },
|
||
abandono: { p25: 1, p50: 4, p75: 7, p90: 12, unidad: '%', invertida: true },
|
||
cpi: { p25: 1.60, p50: 2.80, p75: 3.80, p90: 4.80, unidad: '€', invertida: true }
|
||
}
|
||
},
|
||
general: {
|
||
nombre: 'Cross-Industry',
|
||
fuente: 'Dimension Data Global CX Benchmark 2024',
|
||
metricas: {
|
||
aht: { p25: 320, p50: 380, p75: 460, p90: 540, unidad: 's', invertida: true },
|
||
fcr: { p25: 55, p50: 70, p75: 80, p90: 87, unidad: '%', invertida: false },
|
||
abandono: { p25: 2, p50: 5, p75: 8, p90: 12, unidad: '%', invertida: true },
|
||
cpi: { p25: 2.20, p50: 3.50, p75: 4.50, p90: 5.50, unidad: '€', invertida: true }
|
||
}
|
||
}
|
||
};
|
||
|
||
function calcularPercentilUsuario(valor: number, bench: BenchmarkMetric): number {
|
||
const { p25, p50, p75, p90, invertida } = bench;
|
||
if (invertida) {
|
||
// For inverted metrics (lower is better, like AHT, CPI, Abandono):
|
||
// p25 = best performers (lowest values), p90 = worst performers (highest values)
|
||
// Check from best to worst
|
||
if (valor <= p25) return 95; // Top 25% performers → beat 75%+
|
||
if (valor <= p50) return 60; // At or better than median → beat 50%+
|
||
if (valor <= p75) return 35; // Below median → beat 25%+
|
||
if (valor <= p90) return 15; // Poor → beat 10%+
|
||
return 5; // Very poor → beat <10%
|
||
} else {
|
||
// For normal metrics (higher is better, like FCR):
|
||
// p90 = best performers (highest values), p25 = worst performers (lowest values)
|
||
if (valor >= p90) return 95;
|
||
if (valor >= p75) return 82;
|
||
if (valor >= p50) return 60;
|
||
if (valor >= p25) return 35;
|
||
return 15;
|
||
}
|
||
}
|
||
|
||
|
||
// ============================================
|
||
// PRINCIPALES HALLAZGOS
|
||
// ============================================
|
||
|
||
interface Hallazgo {
|
||
tipo: 'critico' | 'warning' | 'info';
|
||
texto: string;
|
||
metrica?: string;
|
||
}
|
||
|
||
function generarHallazgos(data: AnalysisData): Hallazgo[] {
|
||
const hallazgos: Hallazgo[] = [];
|
||
const allQueues = data.drilldownData?.flatMap(s => s.originalQueues) || [];
|
||
const totalVolume = allQueues.reduce((s, q) => s + q.volume, 0);
|
||
|
||
// AHT promedio ponderado por volumen (usando aht_seconds = AHT limpio sin noise/zombies)
|
||
const heatmapVolume = data.heatmapData.reduce((sum, h) => sum + h.volume, 0);
|
||
const avgAHT = heatmapVolume > 0
|
||
? data.heatmapData.reduce((sum, h) => sum + h.aht_seconds * h.volume, 0) / heatmapVolume
|
||
: 0;
|
||
|
||
// Alta variabilidad
|
||
const colasAltaVariabilidad = allQueues.filter(q => q.cv_aht > 100);
|
||
if (colasAltaVariabilidad.length > 0) {
|
||
const pctVolumen = (colasAltaVariabilidad.reduce((s, q) => s + q.volume, 0) / totalVolume) * 100;
|
||
hallazgos.push({
|
||
tipo: 'critico',
|
||
texto: `${colasAltaVariabilidad.length} colas con variabilidad crítica (CV >100%) representan ${pctVolumen.toFixed(0)}% del volumen`,
|
||
metrica: 'CV AHT'
|
||
});
|
||
}
|
||
|
||
// Alto transfer
|
||
const colasAltoTransfer = allQueues.filter(q => q.transfer_rate > 25);
|
||
if (colasAltoTransfer.length > 0) {
|
||
hallazgos.push({
|
||
tipo: 'warning',
|
||
texto: `${colasAltoTransfer.length} colas con tasa de transferencia >25% - posible problema de routing o formación`,
|
||
metrica: 'Transfer'
|
||
});
|
||
}
|
||
|
||
// Bajo FCR (usar FCR Técnico para consistencia)
|
||
const colasBajoFCR = allQueues.filter(q => (q.fcr_tecnico ?? (100 - q.transfer_rate)) < 50);
|
||
if (colasBajoFCR.length > 0) {
|
||
hallazgos.push({
|
||
tipo: 'warning',
|
||
texto: `${colasBajoFCR.length} colas con FCR <50% - clientes requieren múltiples contactos`,
|
||
metrica: 'FCR'
|
||
});
|
||
}
|
||
|
||
// AHT elevado vs benchmark
|
||
if (avgAHT > 400) {
|
||
hallazgos.push({
|
||
tipo: 'warning',
|
||
texto: `AHT promedio de ${Math.round(avgAHT)}s supera el benchmark de industria (380s)`,
|
||
metrica: 'AHT'
|
||
});
|
||
}
|
||
|
||
// Colas Human-Only
|
||
const colasHumanOnly = allQueues.filter(q => q.tier === 'HUMAN-ONLY');
|
||
if (colasHumanOnly.length > 0) {
|
||
const pctHuman = (colasHumanOnly.reduce((s, q) => s + q.volume, 0) / totalVolume) * 100;
|
||
hallazgos.push({
|
||
tipo: 'info',
|
||
texto: `${colasHumanOnly.length} colas (${pctHuman.toFixed(0)}% volumen) requieren intervención humana completa`,
|
||
metrica: 'Tier'
|
||
});
|
||
}
|
||
|
||
// Oportunidad de automatización
|
||
const colasAutomate = allQueues.filter(q => q.tier === 'AUTOMATE');
|
||
if (colasAutomate.length > 0) {
|
||
hallazgos.push({
|
||
tipo: 'info',
|
||
texto: `${colasAutomate.length} colas listas para automatización con potencial de ahorro significativo`,
|
||
metrica: 'Oportunidad'
|
||
});
|
||
}
|
||
|
||
return hallazgos.slice(0, 5); // Máximo 5 hallazgos
|
||
}
|
||
|
||
function PrincipalesHallazgos({ data }: { data: AnalysisData }) {
|
||
const hallazgos = generarHallazgos(data);
|
||
|
||
if (hallazgos.length === 0) return null;
|
||
|
||
const getIcono = (tipo: string) => {
|
||
if (tipo === 'critico') return <AlertTriangle className="w-4 h-4 text-red-500" />;
|
||
if (tipo === 'warning') return <AlertTriangle className="w-4 h-4 text-amber-500" />;
|
||
return <CheckCircle className="w-4 h-4 text-blue-500" />;
|
||
};
|
||
|
||
const getClase = (tipo: string) => {
|
||
if (tipo === 'critico') return 'bg-red-50 border-red-200';
|
||
if (tipo === 'warning') return 'bg-amber-50 border-amber-200';
|
||
return 'bg-blue-50 border-blue-200';
|
||
};
|
||
|
||
return (
|
||
<Card>
|
||
<h3 className="font-semibold text-gray-900 mb-3">Principales Hallazgos</h3>
|
||
<div className="space-y-2">
|
||
{hallazgos.map((h, idx) => (
|
||
<div key={idx} className={cn('flex items-start gap-2 p-2 rounded-lg border', getClase(h.tipo))}>
|
||
{getIcono(h.tipo)}
|
||
<div className="flex-1">
|
||
<p className="text-sm text-gray-700">{h.texto}</p>
|
||
</div>
|
||
{h.metrica && (
|
||
<span className="text-xs px-2 py-0.5 bg-white rounded border border-gray-200 text-gray-500">
|
||
{h.metrica}
|
||
</span>
|
||
)}
|
||
</div>
|
||
))}
|
||
</div>
|
||
</Card>
|
||
);
|
||
}
|
||
|
||
// ============================================
|
||
// CABECERA CON PERIODO ANALIZADO
|
||
// ============================================
|
||
|
||
function CabeceraPeriodo({ data }: { data: AnalysisData }) {
|
||
const totalInteractions = data.heatmapData.reduce((sum, h) => sum + h.volume, 0);
|
||
|
||
// Contar colas únicas (original_queue_id) desde drilldownData
|
||
const uniqueQueues = data.drilldownData
|
||
? new Set(data.drilldownData.flatMap(d => d.originalQueues.map(q => q.original_queue_id))).size
|
||
: data.heatmapData.length;
|
||
|
||
// Contar líneas de negocio únicas (skills en drilldownData = queue_skill agrupado)
|
||
const numLineasNegocio = data.drilldownData?.length || data.heatmapData.length;
|
||
|
||
// Formatear fechas del periodo
|
||
const formatPeriodo = () => {
|
||
if (!data.dateRange?.min || !data.dateRange?.max) {
|
||
return 'Periodo no especificado';
|
||
}
|
||
const formatDate = (dateStr: string) => {
|
||
try {
|
||
const date = new Date(dateStr);
|
||
return date.toLocaleDateString('es-ES', { day: '2-digit', month: 'short', year: 'numeric' });
|
||
} catch {
|
||
return dateStr;
|
||
}
|
||
};
|
||
return `${formatDate(data.dateRange.min)} - ${formatDate(data.dateRange.max)}`;
|
||
};
|
||
|
||
return (
|
||
<div className="flex flex-col sm:flex-row items-start sm:items-center justify-between gap-2 sm:gap-4 py-3 px-3 sm:px-4 bg-gray-50 rounded-lg border border-gray-200">
|
||
<div className="flex items-center gap-2 text-gray-600">
|
||
<Calendar className="w-4 h-4 flex-shrink-0" />
|
||
<span className="text-xs sm:text-sm font-medium">Periodo:</span>
|
||
<span className="text-xs sm:text-sm">{formatPeriodo()}</span>
|
||
</div>
|
||
<div className="flex flex-wrap items-center gap-2 sm:gap-4 md:gap-6 text-xs sm:text-sm text-gray-500">
|
||
<span><strong>{formatNumber(totalInteractions)}</strong> int.</span>
|
||
<span><strong>{uniqueQueues}</strong> colas</span>
|
||
<span><strong>{numLineasNegocio}</strong> LN</span>
|
||
</div>
|
||
</div>
|
||
);
|
||
}
|
||
|
||
// ============================================
|
||
// v3.15: HEADLINE EJECUTIVO (Situación)
|
||
// ============================================
|
||
function HeadlineEjecutivo({
|
||
totalInteracciones,
|
||
oportunidadTotal,
|
||
eficienciaScore,
|
||
resolucionScore,
|
||
satisfaccionScore
|
||
}: {
|
||
totalInteracciones: number;
|
||
oportunidadTotal: number;
|
||
eficienciaScore: number;
|
||
resolucionScore: number;
|
||
satisfaccionScore: number;
|
||
}) {
|
||
const getStatusLabel = (score: number): string => {
|
||
if (score >= 80) return 'Óptimo';
|
||
if (score >= 60) return 'Aceptable';
|
||
return 'Crítico';
|
||
};
|
||
|
||
const getStatusVariant = (score: number): 'success' | 'warning' | 'critical' => {
|
||
if (score >= 80) return 'success';
|
||
if (score >= 60) return 'warning';
|
||
return 'critical';
|
||
};
|
||
|
||
return (
|
||
<div className="bg-gradient-to-r from-gray-800 to-gray-700 rounded-lg p-4 sm:p-6 text-white">
|
||
{/* Título principal */}
|
||
<div className="mb-3 sm:mb-4">
|
||
<h1 className="text-lg sm:text-xl md:text-2xl font-light mb-1">
|
||
Tu operación procesa{' '}
|
||
<span className="font-bold text-white">{formatNumber(totalInteracciones)}</span>{' '}
|
||
interacciones
|
||
</h1>
|
||
<p className="text-sm sm:text-lg text-gray-300">
|
||
con oportunidad de{' '}
|
||
<span className="font-bold text-emerald-400">
|
||
{formatCurrency(oportunidadTotal)}
|
||
</span>{' '}
|
||
en optimización
|
||
</p>
|
||
</div>
|
||
|
||
{/* Status Bar */}
|
||
<div className="flex flex-wrap gap-2 sm:gap-3 mt-3 sm:mt-4 pt-3 sm:pt-4 border-t border-gray-600">
|
||
<div className={cn(
|
||
'flex items-center gap-2 px-3 py-1.5 rounded-full',
|
||
STATUS_CLASSES[getStatusVariant(eficienciaScore)].bg
|
||
)}>
|
||
<Clock className={cn('w-4 h-4', STATUS_CLASSES[getStatusVariant(eficienciaScore)].text)} />
|
||
<span className={cn('text-sm font-medium', STATUS_CLASSES[getStatusVariant(eficienciaScore)].text)}>
|
||
Eficiencia: {getStatusLabel(eficienciaScore)}
|
||
</span>
|
||
</div>
|
||
<div className={cn(
|
||
'flex items-center gap-2 px-3 py-1.5 rounded-full',
|
||
STATUS_CLASSES[getStatusVariant(resolucionScore)].bg
|
||
)}>
|
||
<CheckCircle className={cn('w-4 h-4', STATUS_CLASSES[getStatusVariant(resolucionScore)].text)} />
|
||
<span className={cn('text-sm font-medium', STATUS_CLASSES[getStatusVariant(resolucionScore)].text)}>
|
||
Resolución: {getStatusLabel(resolucionScore)}
|
||
</span>
|
||
</div>
|
||
<div className={cn(
|
||
'flex items-center gap-2 px-3 py-1.5 rounded-full',
|
||
STATUS_CLASSES[getStatusVariant(satisfaccionScore)].bg
|
||
)}>
|
||
<Users className={cn('w-4 h-4', STATUS_CLASSES[getStatusVariant(satisfaccionScore)].text)} />
|
||
<span className={cn('text-sm font-medium', STATUS_CLASSES[getStatusVariant(satisfaccionScore)].text)}>
|
||
Satisfacción: {getStatusLabel(satisfaccionScore)}
|
||
</span>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
);
|
||
}
|
||
|
||
// v7.0: Unified KPI + Benchmark Card Component
|
||
// Combines KeyMetricsCard + BenchmarkTable into single 3x2 card grid
|
||
function UnifiedKPIBenchmark({ heatmapData }: { heatmapData: HeatmapDataPoint[] }) {
|
||
const [selectedIndustry, setSelectedIndustry] = React.useState<IndustryKey>('aerolineas');
|
||
const benchmarks = BENCHMARKS_INDUSTRIA[selectedIndustry];
|
||
|
||
// Calculate volume-weighted metrics
|
||
const totalVolume = heatmapData.reduce((sum, h) => sum + h.volume, 0);
|
||
|
||
// FCR Técnico = sin transferencia (comparable con benchmarks)
|
||
const fcrTecnico = totalVolume > 0
|
||
? heatmapData.reduce((sum, h) => sum + (h.metrics.fcr_tecnico ?? (100 - h.metrics.transfer_rate)) * h.volume, 0) / totalVolume
|
||
: 0;
|
||
|
||
// FCR Real: sin transferencia Y sin recontacto 7d (más estricto)
|
||
const fcrReal = totalVolume > 0
|
||
? heatmapData.reduce((sum, h) => sum + h.metrics.fcr * h.volume, 0) / totalVolume
|
||
: 0;
|
||
|
||
// Volume-weighted AHT (usando aht_seconds = AHT limpio sin noise/zombies)
|
||
const aht = totalVolume > 0 ? heatmapData.reduce((sum, h) => sum + h.aht_seconds * h.volume, 0) / totalVolume : 0;
|
||
|
||
// Volume-weighted AHT Total (usando aht_total = AHT con TODAS las filas - solo informativo)
|
||
const ahtTotal = totalVolume > 0
|
||
? heatmapData.reduce((sum, h) => sum + (h.aht_total ?? h.aht_seconds) * h.volume, 0) / totalVolume
|
||
: 0;
|
||
|
||
// CPI: usar el valor pre-calculado si existe, sino calcular desde annual_cost/cost_volume
|
||
const totalCostVolume = heatmapData.reduce((sum, h) => sum + (h.cost_volume || h.volume), 0);
|
||
const totalAnnualCost = heatmapData.reduce((sum, h) => sum + (h.annual_cost || 0), 0);
|
||
|
||
// Si tenemos CPI pre-calculado, usarlo ponderado por volumen
|
||
// Si no, calcular desde annual_cost / cost_volume
|
||
const hasCpiField = heatmapData.some(h => h.cpi !== undefined && h.cpi > 0);
|
||
const cpi = hasCpiField
|
||
? (totalCostVolume > 0
|
||
? heatmapData.reduce((sum, h) => sum + (h.cpi || 0) * (h.cost_volume || h.volume), 0) / totalCostVolume
|
||
: 0)
|
||
: (totalCostVolume > 0 ? totalAnnualCost / totalCostVolume : 0);
|
||
|
||
// Volume-weighted metrics
|
||
const operacion = {
|
||
aht: aht,
|
||
ahtTotal: ahtTotal, // AHT con TODAS las filas (solo informativo)
|
||
fcrTecnico: fcrTecnico,
|
||
fcrReal: fcrReal,
|
||
abandono: totalVolume > 0 ? heatmapData.reduce((sum, h) => sum + (h.metrics.abandonment_rate || 0) * h.volume, 0) / totalVolume : 0,
|
||
cpi: cpi
|
||
};
|
||
|
||
// Calculate percentile position
|
||
const getPercentileBadge = (percentile: number): { label: string; color: string } => {
|
||
if (percentile >= 90) return { label: 'Top 10%', color: 'bg-emerald-500 text-white' };
|
||
if (percentile >= 75) return { label: 'Top 25%', color: 'bg-emerald-100 text-emerald-700' };
|
||
if (percentile >= 50) return { label: 'Promedio', color: 'bg-amber-100 text-amber-700' };
|
||
if (percentile >= 25) return { label: 'Bajo Avg', color: 'bg-orange-100 text-orange-700' };
|
||
return { label: 'Bottom 25%', color: 'bg-red-100 text-red-700' };
|
||
};
|
||
|
||
// Calculate GAP vs P50 - positive is better, negative is worse
|
||
const calcularGap = (valor: number, bench: BenchmarkMetric): { gap: string; diff: number; isPositive: boolean } => {
|
||
const diff = bench.invertida ? bench.p50 - valor : valor - bench.p50;
|
||
const isPositive = diff > 0;
|
||
if (bench.unidad === 's') {
|
||
return { gap: `${isPositive ? '+' : ''}${Math.round(diff)}s`, diff, isPositive };
|
||
} else if (bench.unidad === '%') {
|
||
return { gap: `${isPositive ? '+' : ''}${diff.toFixed(1)}pp`, diff, isPositive };
|
||
} else {
|
||
return { gap: `${isPositive ? '+' : ''}€${Math.abs(diff).toFixed(2)}`, diff, isPositive };
|
||
}
|
||
};
|
||
|
||
// Get card background color based on GAP
|
||
type GapStatus = 'positive' | 'neutral' | 'negative';
|
||
const getGapStatus = (diff: number, bench: BenchmarkMetric): GapStatus => {
|
||
// Calculate threshold as 5% of P50
|
||
const threshold = bench.p50 * 0.05;
|
||
if (diff > threshold) return 'positive';
|
||
if (diff < -threshold) return 'negative';
|
||
return 'neutral';
|
||
};
|
||
|
||
const cardBgColors: Record<GapStatus, string> = {
|
||
positive: 'bg-emerald-50 border-emerald-200',
|
||
neutral: 'bg-amber-50 border-amber-200',
|
||
negative: 'bg-red-50 border-red-200'
|
||
};
|
||
|
||
// Calculate position on visual scale (0-100) for the benchmark bar
|
||
// 0 = worst performers, 100 = best performers
|
||
const calcularPosicionVisual = (valor: number, bench: BenchmarkMetric): number => {
|
||
const { p25, p50, p75, p90, invertida } = bench;
|
||
|
||
if (invertida) {
|
||
// For inverted metrics (lower is better): p25 < p50 < p75 < p90
|
||
// Better performance = lower value = higher visual position
|
||
if (valor <= p25) return 95; // Best performers (top 25%)
|
||
if (valor <= p50) return 50 + 45 * (p50 - valor) / (p50 - p25); // Between median and top
|
||
if (valor <= p75) return 25 + 25 * (p75 - valor) / (p75 - p50); // Between p75 and median
|
||
if (valor <= p90) return 5 + 20 * (p90 - valor) / (p90 - p75); // Between p90 and p75
|
||
return 5; // Worst performers (bottom 10%)
|
||
} else {
|
||
// For normal metrics (higher is better): p25 < p50 < p75 < p90
|
||
// Better performance = higher value = higher visual position
|
||
if (valor >= p90) return 95; // Best performers (top 10%)
|
||
if (valor >= p75) return 75 + 20 * (valor - p75) / (p90 - p75);
|
||
if (valor >= p50) return 50 + 25 * (valor - p50) / (p75 - p50);
|
||
if (valor >= p25) return 25 + 25 * (valor - p25) / (p50 - p25);
|
||
return Math.max(5, 25 * valor / p25); // Worst performers
|
||
}
|
||
};
|
||
|
||
// Get insight text based on percentile position
|
||
const getInsightText = (percentile: number, bench: BenchmarkMetric): string => {
|
||
if (percentile >= 90) return `Superas al 90% del mercado`;
|
||
if (percentile >= 75) return `Mejor que 3 de cada 4 empresas`;
|
||
if (percentile >= 50) return `En línea con la mediana del sector`;
|
||
if (percentile >= 25) return `Por debajo de la media del mercado`;
|
||
return `Área crítica de mejora`;
|
||
};
|
||
|
||
// Format benchmark value for display
|
||
const formatBenchValue = (value: number, unidad: string): string => {
|
||
if (unidad === 's') return `${Math.round(value)}s`;
|
||
if (unidad === '%') return `${value}%`;
|
||
return `€${value.toFixed(2)}`;
|
||
};
|
||
|
||
// Metrics data with display values
|
||
// FCR Real context: métrica más estricta que incluye recontactos 7 días
|
||
const fcrRealDiff = operacion.fcrTecnico - operacion.fcrReal;
|
||
const fcrRealContext = fcrRealDiff > 0
|
||
? `${Math.round(fcrRealDiff)}pp de recontactos 7d`
|
||
: null;
|
||
|
||
// AHT Total context: diferencia entre AHT limpio y AHT con todas las filas
|
||
const ahtTotalDiff = operacion.ahtTotal - operacion.aht;
|
||
const ahtTotalContext = Math.abs(ahtTotalDiff) > 1
|
||
? `${ahtTotalDiff > 0 ? '+' : ''}${Math.round(ahtTotalDiff)}s vs AHT limpio`
|
||
: null;
|
||
|
||
const metricsData = [
|
||
{
|
||
id: 'aht',
|
||
label: 'AHT',
|
||
valor: operacion.aht,
|
||
display: `${Math.floor(operacion.aht / 60)}:${String(Math.round(operacion.aht) % 60).padStart(2, '0')}`,
|
||
subDisplay: `(${Math.round(operacion.aht)}s)`,
|
||
bench: benchmarks.metricas.aht,
|
||
tooltip: 'Tiempo medio de gestión (solo interacciones válidas)',
|
||
// AHT Total integrado como métrica secundaria
|
||
secondaryMetric: {
|
||
label: 'AHT Total',
|
||
value: `${Math.floor(operacion.ahtTotal / 60)}:${String(Math.round(operacion.ahtTotal) % 60).padStart(2, '0')} (${Math.round(operacion.ahtTotal)}s)`,
|
||
note: ahtTotalContext,
|
||
tooltip: 'Incluye todas las filas (noise, zombie, abandon) - solo informativo',
|
||
description: 'Incluye noise, zombie y abandonos — solo informativo'
|
||
}
|
||
},
|
||
{
|
||
id: 'fcr_tecnico',
|
||
label: 'FCR',
|
||
valor: operacion.fcrTecnico,
|
||
display: `${Math.round(operacion.fcrTecnico)}%`,
|
||
subDisplay: null,
|
||
bench: benchmarks.metricas.fcr,
|
||
tooltip: 'First Contact Resolution - comparable con benchmarks de industria',
|
||
// FCR Real integrado como métrica secundaria
|
||
secondaryMetric: {
|
||
label: 'FCR Ajustado',
|
||
value: `${Math.round(operacion.fcrReal)}%`,
|
||
note: fcrRealContext,
|
||
tooltip: 'Excluye recontactos en 7 días (métrica más estricta)',
|
||
description: 'Incluye filtro de recontactos 7d — métrica interna más estricta'
|
||
}
|
||
},
|
||
{
|
||
id: 'abandono',
|
||
label: 'ABANDONO',
|
||
valor: operacion.abandono,
|
||
display: `${operacion.abandono.toFixed(1)}%`,
|
||
subDisplay: null,
|
||
bench: benchmarks.metricas.abandono,
|
||
tooltip: 'Tasa de abandono',
|
||
secondaryMetric: null
|
||
},
|
||
{
|
||
id: 'cpi',
|
||
label: 'COSTE/INTERAC.',
|
||
valor: operacion.cpi,
|
||
display: `€${operacion.cpi.toFixed(2)}`,
|
||
subDisplay: null,
|
||
bench: benchmarks.metricas.cpi,
|
||
tooltip: 'Coste por interacción',
|
||
secondaryMetric: null
|
||
}
|
||
];
|
||
|
||
return (
|
||
<Card>
|
||
{/* Header with industry selector */}
|
||
<div className="flex flex-col sm:flex-row sm:items-center sm:justify-between gap-2 mb-3">
|
||
<div>
|
||
<h3 className="font-semibold text-gray-900">Indicadores vs Industria</h3>
|
||
<p className="text-xs text-gray-500">Fuente: {benchmarks.fuente}</p>
|
||
</div>
|
||
<select
|
||
value={selectedIndustry}
|
||
onChange={(e) => setSelectedIndustry(e.target.value as IndustryKey)}
|
||
className="text-sm border border-gray-300 rounded-md px-2 py-1 bg-white w-full sm:w-auto"
|
||
>
|
||
{Object.entries(BENCHMARKS_INDUSTRIA).map(([key, val]) => (
|
||
<option key={key} value={key}>{val.nombre}</option>
|
||
))}
|
||
</select>
|
||
</div>
|
||
|
||
{/* 2x2 Card Grid - McKinsey style */}
|
||
<div className="grid grid-cols-1 sm:grid-cols-2 gap-4">
|
||
{metricsData.map((m) => {
|
||
const percentil = calcularPercentilUsuario(m.valor, m.bench);
|
||
const badge = getPercentileBadge(percentil);
|
||
const { gap, diff, isPositive } = calcularGap(m.valor, m.bench);
|
||
const gapStatus = getGapStatus(diff, m.bench);
|
||
const posicionVisual = calcularPosicionVisual(m.valor, m.bench);
|
||
const insightText = getInsightText(percentil, m.bench);
|
||
|
||
return (
|
||
<div
|
||
key={m.id}
|
||
className={cn(
|
||
'p-4 rounded-lg border transition-all',
|
||
cardBgColors[gapStatus]
|
||
)}
|
||
title={m.tooltip}
|
||
>
|
||
{/* Header: Label + Badge */}
|
||
<div className="flex items-center justify-between mb-2">
|
||
<div className="text-[11px] font-semibold text-gray-600 uppercase tracking-wider">
|
||
{m.label}
|
||
</div>
|
||
<span className={`text-[9px] px-2 py-0.5 rounded-full font-medium ${badge.color}`}>
|
||
{badge.label}
|
||
</span>
|
||
</div>
|
||
|
||
{/* Main Value + GAP */}
|
||
<div className="flex items-baseline justify-between mb-3">
|
||
<div className="text-2xl font-bold text-gray-900">
|
||
{m.display}
|
||
{m.subDisplay && (
|
||
<span className="text-xs font-normal text-gray-500 ml-1">{m.subDisplay}</span>
|
||
)}
|
||
</div>
|
||
<div className={cn(
|
||
"text-sm font-semibold",
|
||
isPositive ? "text-emerald-600" : "text-red-600"
|
||
)}>
|
||
{gap} {isPositive ? '✓' : '✗'}
|
||
</div>
|
||
</div>
|
||
|
||
{/* Secondary Metric (FCR Real for FCR card, AHT Total for AHT card) */}
|
||
{m.secondaryMetric && (
|
||
<div className="mb-3 py-2 px-3 bg-gray-50 border border-gray-200 rounded-md" title={m.secondaryMetric.tooltip}>
|
||
<div className="flex items-center justify-between">
|
||
<div className="flex items-center gap-2">
|
||
<span className="text-[10px] text-gray-500 uppercase tracking-wide">{m.secondaryMetric.label}</span>
|
||
<span className="text-sm font-semibold text-gray-700">{m.secondaryMetric.value}</span>
|
||
</div>
|
||
{m.secondaryMetric.note && (
|
||
<span className="text-[9px] text-gray-500 italic">
|
||
({m.secondaryMetric.note})
|
||
</span>
|
||
)}
|
||
</div>
|
||
{m.secondaryMetric.description && (
|
||
<div className="text-[9px] text-gray-400 mt-1">
|
||
{m.secondaryMetric.description}
|
||
</div>
|
||
)}
|
||
</div>
|
||
)}
|
||
|
||
{/* Visual Benchmark Distribution Bar */}
|
||
<div className="mb-2">
|
||
<div className="relative h-2 bg-gradient-to-r from-red-200 via-amber-200 to-emerald-200 rounded-full overflow-visible">
|
||
{/* P25, P50, P75 markers */}
|
||
<div className="absolute top-0 left-[25%] w-px h-2 bg-gray-400" title="P25" />
|
||
<div className="absolute top-0 left-[50%] w-0.5 h-2 bg-gray-600" title="P50 (Mediana)" />
|
||
<div className="absolute top-0 left-[75%] w-px h-2 bg-gray-400" title="P75" />
|
||
{/* User position indicator */}
|
||
<div
|
||
className="absolute -top-0.5 w-3 h-3 rounded-full bg-gray-800 border-2 border-white shadow-md transform -translate-x-1/2"
|
||
style={{ left: `${Math.min(98, Math.max(2, posicionVisual))}%` }}
|
||
title={`Tu posición: ${m.display}`}
|
||
/>
|
||
</div>
|
||
{/* Scale labels */}
|
||
<div className="flex justify-between text-[8px] text-gray-400 mt-0.5 px-0.5">
|
||
<span>P25</span>
|
||
<span>P50</span>
|
||
<span>P75</span>
|
||
<span>P90</span>
|
||
</div>
|
||
</div>
|
||
|
||
{/* Benchmark Reference Values */}
|
||
<div className="grid grid-cols-3 gap-1 text-center mb-2 py-1.5 bg-white/50 rounded">
|
||
<div>
|
||
<div className="text-[9px] text-gray-400">Bajo</div>
|
||
<div className="text-[10px] font-medium text-gray-600">{formatBenchValue(m.bench.p25, m.bench.unidad)}</div>
|
||
</div>
|
||
<div className="border-x border-gray-200">
|
||
<div className="text-[9px] text-gray-400">Mediana</div>
|
||
<div className="text-[10px] font-semibold text-gray-700">{formatBenchValue(m.bench.p50, m.bench.unidad)}</div>
|
||
</div>
|
||
<div>
|
||
<div className="text-[9px] text-gray-400">Top</div>
|
||
<div className="text-[10px] font-medium text-emerald-600">{formatBenchValue(m.bench.p90, m.bench.unidad)}</div>
|
||
</div>
|
||
</div>
|
||
|
||
{/* Insight Text */}
|
||
<div className={cn(
|
||
"text-[10px] text-center py-1 rounded",
|
||
percentil >= 75 ? "text-emerald-700 bg-emerald-100/50" :
|
||
percentil >= 50 ? "text-amber-700 bg-amber-100/50" :
|
||
"text-red-700 bg-red-100/50"
|
||
)}>
|
||
{insightText}
|
||
</div>
|
||
</div>
|
||
);
|
||
})}
|
||
</div>
|
||
</Card>
|
||
);
|
||
}
|
||
|
||
// v6.0: Health Score - Simplified weighted average (no penalties)
|
||
function HealthScoreDetailed({
|
||
score,
|
||
avgFCR,
|
||
avgAHT,
|
||
avgAbandonmentRate,
|
||
avgTransferRate
|
||
}: {
|
||
score: number;
|
||
avgFCR: number; // FCR Técnico (%)
|
||
avgAHT: number; // AHT en segundos
|
||
avgAbandonmentRate: number; // Tasa de abandono (%)
|
||
avgTransferRate: number; // Tasa de transferencia (%)
|
||
}) {
|
||
const getScoreColor = (s: number): string => {
|
||
if (s >= 80) return COLORS.status.success;
|
||
if (s >= 60) return COLORS.status.warning;
|
||
return COLORS.status.critical;
|
||
};
|
||
|
||
const getScoreLabel = (s: number): string => {
|
||
if (s >= 80) return 'Excelente';
|
||
if (s >= 60) return 'Bueno';
|
||
if (s >= 40) return 'Regular';
|
||
return 'Crítico';
|
||
};
|
||
|
||
const color = getScoreColor(score);
|
||
const circumference = 2 * Math.PI * 40;
|
||
const strokeDasharray = `${(score / 100) * circumference} ${circumference}`;
|
||
|
||
// ═══════════════════════════════════════════════════════════════
|
||
// Calcular scores normalizados usando benchmarks de industria
|
||
// Misma lógica que calculateHealthScore() en realDataAnalysis.ts
|
||
// ═══════════════════════════════════════════════════════════════
|
||
|
||
// FCR Técnico: P10=85%, P50=68%, P90=50%
|
||
let fcrScore: number;
|
||
if (avgFCR >= 85) {
|
||
fcrScore = 95 + 5 * Math.min(1, (avgFCR - 85) / 15);
|
||
} else if (avgFCR >= 68) {
|
||
fcrScore = 50 + 50 * (avgFCR - 68) / (85 - 68);
|
||
} else if (avgFCR >= 50) {
|
||
fcrScore = 20 + 30 * (avgFCR - 50) / (68 - 50);
|
||
} else {
|
||
fcrScore = Math.max(0, 20 * avgFCR / 50);
|
||
}
|
||
|
||
// Abandono: P10=3%, P50=5%, P90=10%
|
||
let abandonoScore: number;
|
||
if (avgAbandonmentRate <= 3) {
|
||
abandonoScore = 95 + 5 * Math.max(0, (3 - avgAbandonmentRate) / 3);
|
||
} else if (avgAbandonmentRate <= 5) {
|
||
abandonoScore = 50 + 45 * (5 - avgAbandonmentRate) / (5 - 3);
|
||
} else if (avgAbandonmentRate <= 10) {
|
||
abandonoScore = 20 + 30 * (10 - avgAbandonmentRate) / (10 - 5);
|
||
} else {
|
||
abandonoScore = Math.max(0, 20 - 2 * (avgAbandonmentRate - 10));
|
||
}
|
||
|
||
// AHT: P10=240s, P50=380s, P90=540s
|
||
let ahtScore: number;
|
||
if (avgAHT <= 240) {
|
||
if (avgFCR > 65) {
|
||
ahtScore = 95 + 5 * Math.max(0, (240 - avgAHT) / 60);
|
||
} else {
|
||
ahtScore = 70;
|
||
}
|
||
} else if (avgAHT <= 380) {
|
||
ahtScore = 50 + 45 * (380 - avgAHT) / (380 - 240);
|
||
} else if (avgAHT <= 540) {
|
||
ahtScore = 20 + 30 * (540 - avgAHT) / (540 - 380);
|
||
} else {
|
||
ahtScore = Math.max(0, 20 * (600 - avgAHT) / 60);
|
||
}
|
||
|
||
// CSAT Proxy: 60% FCR + 40% Abandono
|
||
const csatProxyScore = 0.60 * fcrScore + 0.40 * abandonoScore;
|
||
|
||
type FactorStatus = 'success' | 'warning' | 'critical';
|
||
const getFactorStatus = (s: number): FactorStatus => s >= 80 ? 'success' : s >= 50 ? 'warning' : 'critical';
|
||
|
||
// Nueva ponderación: FCR 35%, Abandono 30%, CSAT Proxy 20%, AHT 15%
|
||
const factors = [
|
||
{
|
||
name: 'FCR Técnico',
|
||
weight: '35%',
|
||
score: Math.round(fcrScore),
|
||
status: getFactorStatus(fcrScore),
|
||
insight: fcrScore >= 80 ? 'Óptimo' : fcrScore >= 50 ? 'En P50' : 'Bajo P90',
|
||
rawValue: `${avgFCR.toFixed(0)}%`
|
||
},
|
||
{
|
||
name: 'Accesibilidad',
|
||
weight: '30%',
|
||
score: Math.round(abandonoScore),
|
||
status: getFactorStatus(abandonoScore),
|
||
insight: abandonoScore >= 80 ? 'Bajo' : abandonoScore >= 50 ? 'Moderado' : 'Crítico',
|
||
rawValue: `${avgAbandonmentRate.toFixed(1)}% aband.`
|
||
},
|
||
{
|
||
name: 'CSAT Proxy',
|
||
weight: '20%',
|
||
score: Math.round(csatProxyScore),
|
||
status: getFactorStatus(csatProxyScore),
|
||
insight: csatProxyScore >= 80 ? 'Óptimo' : csatProxyScore >= 50 ? 'Mejorable' : 'Bajo',
|
||
rawValue: '(FCR+Aband.)'
|
||
},
|
||
{
|
||
name: 'Eficiencia',
|
||
weight: '15%',
|
||
score: Math.round(ahtScore),
|
||
status: getFactorStatus(ahtScore),
|
||
insight: ahtScore >= 80 ? 'Rápido' : ahtScore >= 50 ? 'En rango' : 'Lento',
|
||
rawValue: `${Math.floor(avgAHT / 60)}:${String(Math.round(avgAHT) % 60).padStart(2, '0')}`
|
||
}
|
||
];
|
||
|
||
const statusBarColors: Record<FactorStatus, string> = {
|
||
success: 'bg-emerald-500',
|
||
warning: 'bg-amber-500',
|
||
critical: 'bg-red-500'
|
||
};
|
||
|
||
const statusTextColors: Record<FactorStatus, string> = {
|
||
success: 'text-emerald-600',
|
||
warning: 'text-amber-600',
|
||
critical: 'text-red-600'
|
||
};
|
||
|
||
// Score final = media ponderada (sin penalizaciones en v6.0)
|
||
const finalScore = Math.round(
|
||
fcrScore * 0.35 +
|
||
abandonoScore * 0.30 +
|
||
csatProxyScore * 0.20 +
|
||
ahtScore * 0.15
|
||
);
|
||
|
||
const displayColor = getScoreColor(finalScore);
|
||
const displayStrokeDasharray = `${(finalScore / 100) * circumference} ${circumference}`;
|
||
|
||
return (
|
||
<Card>
|
||
<div className="flex flex-col sm:flex-row items-start gap-4 sm:gap-5">
|
||
{/* Single Gauge: Final Score (weighted average) */}
|
||
<div className="flex-shrink-0">
|
||
<div className="text-center">
|
||
<div className="relative w-20 h-20 sm:w-24 sm:h-24">
|
||
<svg className="w-full h-full transform -rotate-90" viewBox="0 0 100 100">
|
||
<circle cx="50" cy="50" r="40" fill="none" stroke="#e5e7eb" strokeWidth="8" />
|
||
<circle
|
||
cx="50" cy="50" r="40" fill="none" stroke={displayColor} strokeWidth="8"
|
||
strokeLinecap="round" strokeDasharray={displayStrokeDasharray}
|
||
className="transition-all duration-1000"
|
||
/>
|
||
</svg>
|
||
<div className="absolute inset-0 flex flex-col items-center justify-center">
|
||
<span className="text-2xl sm:text-3xl font-bold" style={{ color: displayColor }}>{finalScore}</span>
|
||
</div>
|
||
</div>
|
||
<p className="text-xs font-semibold mt-1" style={{ color: displayColor }}>{getScoreLabel(finalScore)}</p>
|
||
</div>
|
||
</div>
|
||
|
||
{/* Breakdown */}
|
||
<div className="flex-1 min-w-0">
|
||
<h3 className="font-semibold text-gray-900 mb-2">Health Score</h3>
|
||
<p className="text-[10px] text-gray-400 mb-2">
|
||
Benchmarks: FCR P10=85%, Aband. P10=3%, AHT P10=240s
|
||
</p>
|
||
|
||
<div className="space-y-2">
|
||
{factors.map((factor) => (
|
||
<div key={factor.name} className="flex items-center gap-2">
|
||
<div className="w-20 text-xs text-gray-600 truncate">{factor.name}</div>
|
||
<div className="w-7 text-[10px] text-gray-400 text-center font-medium">{factor.weight}</div>
|
||
<div className="flex-1 h-2 bg-gray-100 rounded-full overflow-hidden">
|
||
<div
|
||
className={cn('h-full rounded-full transition-all', statusBarColors[factor.status])}
|
||
style={{ width: `${factor.score}%` }}
|
||
/>
|
||
</div>
|
||
<div className="w-6 text-xs text-gray-500 text-right">{factor.score}</div>
|
||
<div className={cn('w-16 text-[10px]', statusTextColors[factor.status])}>
|
||
{factor.rawValue}
|
||
</div>
|
||
</div>
|
||
))}
|
||
</div>
|
||
|
||
{/* Nota de cálculo */}
|
||
<div className="mt-3 pt-2 border-t border-gray-100">
|
||
<p className="text-[9px] text-gray-400 text-center">
|
||
Score = FCR×35% + Accesibilidad×30% + CSAT Proxy×20% + Eficiencia×15%
|
||
</p>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
</Card>
|
||
);
|
||
}
|
||
|
||
// v3.16: Potencial de Automatización - Sin gauge confuso, solo distribución clara
|
||
function AgenticReadinessScore({ data }: { data: AnalysisData }) {
|
||
const allQueues = data.drilldownData?.flatMap(skill => skill.originalQueues) || [];
|
||
const totalQueueVolume = allQueues.reduce((sum, q) => sum + q.volume, 0);
|
||
|
||
// Calcular volúmenes por tier
|
||
const tierVolumes = {
|
||
AUTOMATE: allQueues.filter(q => q.tier === 'AUTOMATE').reduce((s, q) => s + q.volume, 0),
|
||
ASSIST: allQueues.filter(q => q.tier === 'ASSIST').reduce((s, q) => s + q.volume, 0),
|
||
AUGMENT: allQueues.filter(q => q.tier === 'AUGMENT').reduce((s, q) => s + q.volume, 0),
|
||
'HUMAN-ONLY': allQueues.filter(q => q.tier === 'HUMAN-ONLY').reduce((s, q) => s + q.volume, 0)
|
||
};
|
||
|
||
const tierCounts = {
|
||
AUTOMATE: allQueues.filter(q => q.tier === 'AUTOMATE').length,
|
||
ASSIST: allQueues.filter(q => q.tier === 'ASSIST').length,
|
||
AUGMENT: allQueues.filter(q => q.tier === 'AUGMENT').length,
|
||
'HUMAN-ONLY': allQueues.filter(q => q.tier === 'HUMAN-ONLY').length
|
||
};
|
||
|
||
// Porcentajes por tier
|
||
const tierPcts = {
|
||
AUTOMATE: totalQueueVolume > 0 ? (tierVolumes.AUTOMATE / totalQueueVolume) * 100 : 0,
|
||
ASSIST: totalQueueVolume > 0 ? (tierVolumes.ASSIST / totalQueueVolume) * 100 : 0,
|
||
AUGMENT: totalQueueVolume > 0 ? (tierVolumes.AUGMENT / totalQueueVolume) * 100 : 0,
|
||
'HUMAN-ONLY': totalQueueVolume > 0 ? (tierVolumes['HUMAN-ONLY'] / totalQueueVolume) * 100 : 0
|
||
};
|
||
|
||
// Datos de tiers con descripción clara
|
||
const tiers = [
|
||
{ key: 'AUTOMATE', label: 'AUTOMATE', bgColor: 'bg-emerald-500', desc: 'Bot autónomo' },
|
||
{ key: 'ASSIST', label: 'ASSIST', bgColor: 'bg-cyan-500', desc: 'Bot + agente' },
|
||
{ key: 'AUGMENT', label: 'AUGMENT', bgColor: 'bg-amber-500', desc: 'Agente asistido' },
|
||
{ key: 'HUMAN-ONLY', label: 'HUMAN', bgColor: 'bg-gray-400', desc: 'Solo humano' }
|
||
];
|
||
|
||
return (
|
||
<Card>
|
||
<div className="flex items-center gap-2 mb-4">
|
||
<Bot className="w-5 h-5 text-blue-600" />
|
||
<h3 className="font-semibold text-gray-900">Potencial de Automatización</h3>
|
||
</div>
|
||
|
||
{/* Distribución por tier */}
|
||
<div className="space-y-3">
|
||
{tiers.map((tier) => {
|
||
const pct = tierPcts[tier.key as keyof typeof tierPcts];
|
||
const count = tierCounts[tier.key as keyof typeof tierCounts];
|
||
const vol = tierVolumes[tier.key as keyof typeof tierVolumes];
|
||
return (
|
||
<div key={tier.key} className="flex items-center gap-3">
|
||
<div className="w-20">
|
||
<div className="text-xs font-medium text-gray-700">{tier.label}</div>
|
||
<div className="text-[10px] text-gray-400">{tier.desc}</div>
|
||
</div>
|
||
<div className="flex-1 h-2.5 bg-gray-100 rounded-full overflow-hidden">
|
||
<div
|
||
className={cn('h-full rounded-full transition-all', tier.bgColor)}
|
||
style={{ width: `${pct}%` }}
|
||
/>
|
||
</div>
|
||
<div className="w-14 text-right">
|
||
<div className="text-sm font-semibold text-gray-700">{Math.round(pct)}%</div>
|
||
</div>
|
||
<div className="w-16 text-xs text-gray-400 text-right">{count} colas</div>
|
||
</div>
|
||
);
|
||
})}
|
||
</div>
|
||
|
||
{/* Resumen */}
|
||
<div className="mt-4 pt-3 border-t border-gray-100">
|
||
<div className="grid grid-cols-2 gap-3 text-center">
|
||
<div className="p-2 bg-emerald-50 rounded-lg">
|
||
<p className="text-lg font-bold text-emerald-700">{Math.round(tierPcts.AUTOMATE)}%</p>
|
||
<p className="text-[10px] text-emerald-600">Automatización completa</p>
|
||
</div>
|
||
<div className="p-2 bg-cyan-50 rounded-lg">
|
||
<p className="text-lg font-bold text-cyan-700">{Math.round(tierPcts.AUTOMATE + tierPcts.ASSIST)}%</p>
|
||
<p className="text-[10px] text-cyan-600">Con asistencia IA</p>
|
||
</div>
|
||
</div>
|
||
<p className="text-[10px] text-gray-400 text-center mt-2">
|
||
Basado en {formatNumber(totalQueueVolume)} interacciones analizadas
|
||
</p>
|
||
</div>
|
||
</Card>
|
||
);
|
||
}
|
||
|
||
|
||
// Top Opportunities Component (legacy - kept for reference)
|
||
function TopOpportunities({ findings, opportunities }: {
|
||
findings: Finding[];
|
||
opportunities: { name: string; impact: number; savings: number }[];
|
||
}) {
|
||
const items = [
|
||
...findings
|
||
.filter(f => f.type === 'critical' || f.type === 'warning')
|
||
.slice(0, 3)
|
||
.map((f, i) => ({
|
||
rank: i + 1,
|
||
title: f.title || f.text.split(':')[0],
|
||
metric: f.text.includes(':') ? f.text.split(':')[1].trim() : '',
|
||
action: f.description || 'Acción requerida',
|
||
type: f.type as 'critical' | 'warning' | 'info'
|
||
})),
|
||
].slice(0, 3);
|
||
|
||
if (items.length < 3) {
|
||
const remaining = 3 - items.length;
|
||
opportunities
|
||
.sort((a, b) => b.savings - a.savings)
|
||
.slice(0, remaining)
|
||
.forEach(() => {
|
||
const opp = opportunities[items.length];
|
||
if (opp) {
|
||
items.push({
|
||
rank: items.length + 1,
|
||
title: opp.name,
|
||
metric: `€${opp.savings.toLocaleString()} ahorro potencial`,
|
||
action: 'Implementar',
|
||
type: 'info' as const
|
||
});
|
||
}
|
||
});
|
||
}
|
||
|
||
const getIcon = (type: string) => {
|
||
if (type === 'critical') return <AlertTriangle className="w-4 h-4 text-red-500" />;
|
||
if (type === 'warning') return <Target className="w-4 h-4 text-amber-500" />;
|
||
return <CheckCircle className="w-4 h-4 text-emerald-500" />;
|
||
};
|
||
|
||
return (
|
||
<div className="bg-white rounded-lg p-4 border border-slate-200">
|
||
<h3 className="font-semibold text-slate-800 mb-3">Top 3 Oportunidades</h3>
|
||
<div className="space-y-2">
|
||
{items.map((item) => (
|
||
<div key={item.rank} className="flex items-start gap-2 p-2.5 bg-slate-50 rounded-lg">
|
||
<div className="flex-shrink-0 w-5 h-5 rounded-full bg-slate-200 flex items-center justify-center text-xs font-bold text-slate-600">
|
||
{item.rank}
|
||
</div>
|
||
<div className="flex-1 min-w-0">
|
||
<div className="flex items-center gap-1.5">
|
||
{getIcon(item.type)}
|
||
<span className="text-sm font-medium text-slate-700">{item.title}</span>
|
||
</div>
|
||
{item.metric && (
|
||
<p className="text-xs text-slate-500 mt-0.5">{item.metric}</p>
|
||
)}
|
||
<p className="text-xs text-[#6D84E3] mt-0.5 font-medium">→ {item.action}</p>
|
||
</div>
|
||
</div>
|
||
))}
|
||
</div>
|
||
</div>
|
||
);
|
||
}
|
||
|
||
// v3.15: Economic Summary Compact
|
||
function EconomicSummary({ economicModel }: { economicModel: AnalysisData['economicModel'] }) {
|
||
return (
|
||
<Card padding="md">
|
||
<h3 className="font-semibold text-gray-900 mb-3">Impacto Económico</h3>
|
||
|
||
<div className="grid grid-cols-2 gap-3 mb-3">
|
||
<Stat
|
||
value={formatCurrency(economicModel.currentAnnualCost)}
|
||
label="Coste Anual"
|
||
/>
|
||
<Stat
|
||
value={formatCurrency(economicModel.annualSavings)}
|
||
label="Ahorro Potencial"
|
||
status="success"
|
||
/>
|
||
</div>
|
||
|
||
<div className="flex items-center justify-between p-2.5 bg-blue-50 rounded-lg">
|
||
<div>
|
||
<p className="text-xs text-blue-600">ROI 3 años</p>
|
||
<p className="text-lg font-bold text-blue-600">{economicModel.roi3yr}%</p>
|
||
</div>
|
||
<div className="text-right">
|
||
<p className="text-xs text-gray-500">Payback</p>
|
||
<p className="text-lg font-bold text-gray-700">{economicModel.paybackMonths}m</p>
|
||
</div>
|
||
</div>
|
||
</Card>
|
||
);
|
||
}
|
||
|
||
export function ExecutiveSummaryTab({ data, onTabChange }: ExecutiveSummaryTabProps) {
|
||
// Métricas básicas - VOLUME-WEIGHTED para consistencia con calculateHealthScore()
|
||
const totalInteractions = data.heatmapData.reduce((sum, h) => sum + h.volume, 0);
|
||
|
||
// AHT ponderado por volumen (usando aht_seconds = AHT limpio sin noise/zombies)
|
||
const avgAHT = totalInteractions > 0
|
||
? data.heatmapData.reduce((sum, h) => sum + h.aht_seconds * h.volume, 0) / totalInteractions
|
||
: 0;
|
||
|
||
// FCR Técnico: solo sin transferencia (comparable con benchmarks de industria) - ponderado por volumen
|
||
const avgFCRTecnico = totalInteractions > 0
|
||
? data.heatmapData.reduce((sum, h) => sum + (h.metrics.fcr_tecnico ?? (100 - h.metrics.transfer_rate)) * h.volume, 0) / totalInteractions
|
||
: 0;
|
||
|
||
// Transfer rate ponderado por volumen
|
||
const avgTransferRate = totalInteractions > 0
|
||
? data.heatmapData.reduce((sum, h) => sum + h.metrics.transfer_rate * h.volume, 0) / totalInteractions
|
||
: 0;
|
||
|
||
// Abandonment rate ponderado por volumen
|
||
const avgAbandonmentRate = totalInteractions > 0
|
||
? data.heatmapData.reduce((sum, h) => sum + (h.metrics.abandonment_rate || 0) * h.volume, 0) / totalInteractions
|
||
: 0;
|
||
|
||
// DEBUG: Validar métricas GLOBALES calculadas (ponderadas por volumen)
|
||
console.log('📊 ExecutiveSummaryTab - MÉTRICAS GLOBALES MOSTRADAS:', {
|
||
totalInteractions,
|
||
avgFCRTecnico: avgFCRTecnico.toFixed(2) + '%',
|
||
avgTransferRate: avgTransferRate.toFixed(2) + '%',
|
||
avgAbandonmentRate: avgAbandonmentRate.toFixed(2) + '%',
|
||
avgAHT: Math.round(avgAHT) + 's',
|
||
// Detalle por skill para verificación
|
||
perSkill: data.heatmapData.map(h => ({
|
||
skill: h.skill,
|
||
vol: h.volume,
|
||
fcr_tecnico: h.metrics?.fcr_tecnico,
|
||
transfer: h.metrics?.transfer_rate
|
||
}))
|
||
});
|
||
|
||
// Métricas para navegación
|
||
const allQueues = data.drilldownData?.flatMap(s => s.originalQueues) || [];
|
||
const colasAutomate = allQueues.filter(q => q.tier === 'AUTOMATE');
|
||
const ahorroTotal = data.economicModel?.annualSavings || 0;
|
||
const dimensionesConProblemas = data.dimensions.filter(d => d.score < 60).length;
|
||
|
||
return (
|
||
<div className="space-y-5">
|
||
{/* ========================================
|
||
1. CABECERA CON PERIODO
|
||
======================================== */}
|
||
<CabeceraPeriodo data={data} />
|
||
|
||
{/* ========================================
|
||
2. KPIs + BENCHMARK (Unified Card Grid)
|
||
======================================== */}
|
||
<UnifiedKPIBenchmark heatmapData={data.heatmapData} />
|
||
|
||
{/* ========================================
|
||
3. HEALTH SCORE
|
||
======================================== */}
|
||
<HealthScoreDetailed
|
||
score={data.overallHealthScore}
|
||
avgFCR={avgFCRTecnico}
|
||
avgAHT={avgAHT}
|
||
avgAbandonmentRate={avgAbandonmentRate}
|
||
avgTransferRate={avgTransferRate}
|
||
/>
|
||
|
||
{/* ========================================
|
||
4. PRINCIPALES HALLAZGOS
|
||
======================================== */}
|
||
<PrincipalesHallazgos data={data} />
|
||
|
||
{/* ========================================
|
||
5. NAVEGACIÓN RÁPIDA (Explorar más)
|
||
======================================== */}
|
||
{onTabChange && (
|
||
<div className="bg-gray-50 rounded-lg p-4">
|
||
<p className="text-xs font-medium text-gray-500 uppercase tracking-wider mb-3">
|
||
Explorar análisis detallado
|
||
</p>
|
||
|
||
<div className="grid grid-cols-1 md:grid-cols-3 gap-3">
|
||
{/* Dimensiones */}
|
||
<button
|
||
onClick={() => onTabChange('dimensions')}
|
||
className="group flex items-center gap-3 p-3 bg-white rounded-lg border border-gray-200 text-left transition-all hover:shadow-sm hover:border-gray-300"
|
||
>
|
||
<div className={cn('p-2 rounded-lg', dimensionesConProblemas > 0 ? 'bg-amber-100' : 'bg-gray-100')}>
|
||
<BarChart3 className={cn('w-4 h-4', dimensionesConProblemas > 0 ? 'text-amber-600' : 'text-gray-600')} />
|
||
</div>
|
||
<div className="flex-1 min-w-0">
|
||
<div className="flex items-center gap-2">
|
||
<span className="font-medium text-gray-700 text-sm">Dimensiones</span>
|
||
{dimensionesConProblemas > 0 && (
|
||
<Badge label={`${dimensionesConProblemas} críticas`} variant="warning" size="sm" />
|
||
)}
|
||
</div>
|
||
<p className="text-xs text-gray-400">Eficiencia, resolución, satisfacción</p>
|
||
</div>
|
||
<ChevronRight className="w-4 h-4 text-gray-300 group-hover:text-gray-500 group-hover:translate-x-0.5 transition-all" />
|
||
</button>
|
||
|
||
{/* Agentic Readiness */}
|
||
<button
|
||
onClick={() => onTabChange('readiness')}
|
||
className="group flex items-center gap-3 p-3 bg-white rounded-lg border border-gray-200 text-left transition-all hover:shadow-sm hover:border-gray-300"
|
||
>
|
||
<div className={cn('p-2 rounded-lg', colasAutomate.length > 0 ? 'bg-emerald-100' : 'bg-gray-100')}>
|
||
<Cpu className={cn('w-4 h-4', colasAutomate.length > 0 ? 'text-emerald-600' : 'text-gray-600')} />
|
||
</div>
|
||
<div className="flex-1 min-w-0">
|
||
<div className="flex items-center gap-2">
|
||
<span className="font-medium text-gray-700 text-sm">Agentic Readiness</span>
|
||
{colasAutomate.length > 0 && (
|
||
<Badge label={`${colasAutomate.length} listas`} variant="success" size="sm" />
|
||
)}
|
||
</div>
|
||
<p className="text-xs text-gray-400">Colas elegibles para automatización</p>
|
||
</div>
|
||
<ChevronRight className="w-4 h-4 text-gray-300 group-hover:text-gray-500 group-hover:translate-x-0.5 transition-all" />
|
||
</button>
|
||
|
||
{/* Plan de Acción */}
|
||
<button
|
||
onClick={() => onTabChange('roadmap')}
|
||
className="group flex items-center gap-3 p-3 bg-white rounded-lg border border-gray-200 text-left transition-all hover:shadow-sm hover:border-gray-300"
|
||
>
|
||
<div className="p-2 rounded-lg bg-blue-100">
|
||
<Zap className="w-4 h-4 text-blue-600" />
|
||
</div>
|
||
<div className="flex-1 min-w-0">
|
||
<div className="flex items-center gap-2">
|
||
<span className="font-medium text-gray-700 text-sm">Plan de Acción</span>
|
||
<Badge label="Prioridad" variant="critical" size="sm" />
|
||
</div>
|
||
<p className="text-xs text-gray-400">
|
||
{ahorroTotal > 0 ? `Potencial: ${formatCurrency(ahorroTotal)}/año` : 'Roadmap de implementación'}
|
||
</p>
|
||
</div>
|
||
<ChevronRight className="w-4 h-4 text-gray-300 group-hover:text-gray-500 group-hover:translate-x-0.5 transition-all" />
|
||
</button>
|
||
</div>
|
||
</div>
|
||
)}
|
||
</div>
|
||
);
|
||
}
|
||
|
||
export default ExecutiveSummaryTab;
|