7e24f4eb31
- Nueva estructura de tabs: Resumen, Dimensiones, Agentic Readiness, Roadmap - Componentes de visualización McKinsey: - BulletChart: actual vs benchmark con rangos de color - WaterfallChart: impacto económico con costes y ahorros - OpportunityTreemap: priorización por volumen y readiness - 5 dimensiones actualizadas (sin satisfaction ni economy) - Header sticky con navegación animada - Integración completa con datos existentes Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
279 lines
11 KiB
TypeScript
279 lines
11 KiB
TypeScript
import { motion } from 'framer-motion';
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import { Bot, Zap, Brain, Activity, ChevronRight } from 'lucide-react';
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import { OpportunityTreemap, TreemapData, ReadinessCategory } from '../charts/OpportunityTreemap';
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import type { AnalysisData, HeatmapDataPoint, SubFactor } from '../../types';
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interface AgenticReadinessTabProps {
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data: AnalysisData;
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}
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// Global Score Gauge
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function GlobalScoreGauge({ score, confidence }: { score: number; confidence?: string }) {
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const getColor = (s: number) => {
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if (s >= 7) return '#059669'; // emerald-600 - Ready to automate
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if (s >= 5) return '#6D84E3'; // primary blue - Assist with copilot
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if (s >= 3) return '#D97706'; // amber-600 - Optimize first
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return '#DC2626'; // red-600 - Not ready
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};
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const getLabel = (s: number) => {
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if (s >= 7) return 'Listo para Automatizar';
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if (s >= 5) return 'Asistir con Copilot';
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if (s >= 3) return 'Optimizar Primero';
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return 'No Apto';
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};
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const color = getColor(score);
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const percentage = (score / 10) * 100;
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return (
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<div className="bg-white rounded-lg p-6 border border-slate-200">
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<div className="flex items-center justify-between mb-4">
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<h3 className="font-semibold text-slate-800 flex items-center gap-2">
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<Bot className="w-5 h-5 text-[#6D84E3]" />
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Agentic Readiness Score
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</h3>
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{confidence && (
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<span className={`text-xs px-2 py-1 rounded-full ${
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confidence === 'high' ? 'bg-emerald-100 text-emerald-700' :
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confidence === 'medium' ? 'bg-amber-100 text-amber-700' :
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'bg-slate-100 text-slate-600'
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}`}>
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Confianza: {confidence === 'high' ? 'Alta' : confidence === 'medium' ? 'Media' : 'Baja'}
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</span>
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)}
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</div>
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{/* Score Display */}
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<div className="flex items-center gap-6">
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<div className="relative w-28 h-28">
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<svg className="w-full h-full transform -rotate-90" viewBox="0 0 100 100">
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<circle
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cx="50"
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cy="50"
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r="42"
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fill="none"
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stroke="#E2E8F0"
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strokeWidth="12"
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/>
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<circle
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cx="50"
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cy="50"
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r="42"
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fill="none"
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stroke={color}
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strokeWidth="12"
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strokeLinecap="round"
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strokeDasharray={`${percentage * 2.64} ${100 * 2.64}`}
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className="transition-all duration-1000 ease-out"
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/>
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</svg>
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<div className="absolute inset-0 flex flex-col items-center justify-center">
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<span className="text-3xl font-bold" style={{ color }}>{score.toFixed(1)}</span>
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<span className="text-xs text-slate-500">/10</span>
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</div>
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</div>
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<div className="flex-1">
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<p className="font-medium text-lg" style={{ color }}>{getLabel(score)}</p>
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<p className="text-sm text-slate-500 mt-1">
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{score >= 7
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? 'Skills con alta predictibilidad y bajo riesgo de error'
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: score >= 5
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? 'Skills aptos para asistencia AI con supervisión humana'
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: 'Requiere optimización de procesos antes de automatizar'}
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</p>
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</div>
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</div>
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</div>
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);
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}
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// Sub-factors Breakdown
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function SubFactorsBreakdown({ subFactors }: { subFactors: SubFactor[] }) {
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const getIcon = (name: string) => {
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if (name.includes('repetitiv')) return Activity;
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if (name.includes('predict')) return Brain;
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if (name.includes('estructura') || name.includes('complex')) return Zap;
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return Bot;
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};
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return (
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<div className="bg-white rounded-lg p-4 border border-slate-200">
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<h3 className="font-semibold text-slate-800 mb-4">Desglose de Factores</h3>
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<div className="space-y-3">
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{subFactors.map((factor) => {
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const Icon = getIcon(factor.name);
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const percentage = (factor.score / 10) * 100;
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const weightPct = Math.round(factor.weight * 100);
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return (
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<div key={factor.name} className="p-3 bg-slate-50 rounded-lg">
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<div className="flex items-center justify-between mb-2">
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<div className="flex items-center gap-2">
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<Icon className="w-4 h-4 text-[#6D84E3]" />
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<span className="text-sm font-medium text-slate-700">{factor.displayName}</span>
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<span className="text-xs text-slate-400">({weightPct}%)</span>
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</div>
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<span className="font-bold text-slate-800">{factor.score.toFixed(1)}</span>
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</div>
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<div className="h-2 bg-slate-200 rounded-full overflow-hidden">
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<div
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className="h-full bg-[#6D84E3] rounded-full transition-all duration-500"
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style={{ width: `${percentage}%` }}
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/>
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</div>
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<p className="text-xs text-slate-500 mt-1">{factor.description}</p>
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</div>
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);
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})}
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</div>
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</div>
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);
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}
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// Skills Heatmap/Table
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function SkillsReadinessTable({ heatmapData }: { heatmapData: HeatmapDataPoint[] }) {
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// Sort by automation_readiness descending
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const sortedData = [...heatmapData].sort((a, b) => b.automation_readiness - a.automation_readiness);
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const getReadinessColor = (score: number) => {
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if (score >= 70) return 'bg-emerald-100 text-emerald-700';
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if (score >= 50) return 'bg-[#6D84E3]/20 text-[#6D84E3]';
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if (score >= 30) return 'bg-amber-100 text-amber-700';
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return 'bg-red-100 text-red-700';
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};
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const getCategoryLabel = (category?: string) => {
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switch (category) {
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case 'automate_now': return 'Automatizar';
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case 'assist_copilot': return 'Copilot';
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case 'optimize_first': return 'Optimizar';
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default: return 'Evaluar';
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}
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};
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const getRecommendation = (dataPoint: HeatmapDataPoint): string => {
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const score = dataPoint.automation_readiness;
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if (score >= 70) return 'Implementar agente autónomo con supervisión mínima';
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if (score >= 50) return 'Desplegar copilot con escalado humano';
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if (score >= 30) return 'Reducir variabilidad antes de automatizar';
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return 'Optimizar procesos y reducir transferencias';
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};
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return (
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<div className="bg-white rounded-lg border border-slate-200 overflow-hidden">
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<div className="px-4 py-3 border-b border-slate-100 bg-slate-50">
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<h3 className="font-semibold text-slate-800">Análisis por Skill</h3>
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</div>
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<div className="overflow-x-auto">
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<table className="w-full">
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<thead>
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<tr className="text-xs text-slate-500 uppercase tracking-wider bg-slate-50">
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<th className="px-4 py-2 text-left font-medium">Skill</th>
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<th className="px-4 py-2 text-right font-medium">Volumen</th>
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<th className="px-4 py-2 text-right font-medium">AHT</th>
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<th className="px-4 py-2 text-right font-medium">CV AHT</th>
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<th className="px-4 py-2 text-right font-medium">Transfer</th>
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<th className="px-4 py-2 text-center font-medium">Score</th>
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<th className="px-4 py-2 text-left font-medium">Categoría</th>
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<th className="px-4 py-2 text-left font-medium">Siguiente Paso</th>
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</tr>
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</thead>
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<tbody className="divide-y divide-slate-100">
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{sortedData.map((item) => (
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<motion.tr
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key={item.skill}
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initial={{ opacity: 0 }}
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animate={{ opacity: 1 }}
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className="hover:bg-slate-50"
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>
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<td className="px-4 py-3 text-sm font-medium text-slate-800">{item.skill}</td>
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<td className="px-4 py-3 text-sm text-slate-600 text-right">
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{item.volume.toLocaleString()}
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</td>
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<td className="px-4 py-3 text-sm text-slate-600 text-right">
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{item.aht_seconds}s
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</td>
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<td className="px-4 py-3 text-sm text-right">
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<span className={item.variability.cv_aht > 50 ? 'text-amber-600' : 'text-slate-600'}>
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{item.variability.cv_aht.toFixed(0)}%
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</span>
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</td>
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<td className="px-4 py-3 text-sm text-right">
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<span className={item.variability.transfer_rate > 20 ? 'text-red-600' : 'text-slate-600'}>
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{item.variability.transfer_rate.toFixed(0)}%
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</span>
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</td>
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<td className="px-4 py-3 text-center">
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<span className={`px-2 py-1 rounded-full text-xs font-semibold ${getReadinessColor(item.automation_readiness)}`}>
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{(item.automation_readiness / 10).toFixed(1)}
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</span>
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</td>
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<td className="px-4 py-3 text-sm">
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<span className={`px-2 py-1 rounded text-xs font-medium ${
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item.readiness_category === 'automate_now' ? 'bg-emerald-100 text-emerald-700' :
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item.readiness_category === 'assist_copilot' ? 'bg-[#6D84E3]/20 text-[#6D84E3]' :
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'bg-amber-100 text-amber-700'
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}`}>
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{getCategoryLabel(item.readiness_category)}
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</span>
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</td>
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<td className="px-4 py-3 text-xs text-slate-600 max-w-xs">
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<div className="flex items-start gap-1">
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<ChevronRight className="w-3 h-3 mt-0.5 text-[#6D84E3] flex-shrink-0" />
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{getRecommendation(item)}
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</div>
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</td>
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</motion.tr>
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))}
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</tbody>
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</table>
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</div>
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</div>
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);
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}
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export function AgenticReadinessTab({ data }: AgenticReadinessTabProps) {
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// Get agentic readiness dimension or use fallback
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const agenticDimension = data.dimensions.find(d => d.name === 'agentic_readiness');
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const globalScore = data.agenticReadiness?.score || agenticDimension?.score || 0;
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const subFactors = data.agenticReadiness?.sub_factors || agenticDimension?.sub_factors || [];
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const confidence = data.agenticReadiness?.confidence;
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// Convert heatmap data to treemap format
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const treemapData: TreemapData[] = data.heatmapData.map(item => ({
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name: item.skill,
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value: item.annual_cost || item.volume * item.aht_seconds * 0.005, // Use annual cost or estimate
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category: item.readiness_category || (
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item.automation_readiness >= 70 ? 'automate_now' :
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item.automation_readiness >= 50 ? 'assist_copilot' : 'optimize_first'
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) as ReadinessCategory,
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skill: item.skill,
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score: item.automation_readiness / 10,
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volume: item.volume
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}));
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return (
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<div className="space-y-6">
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{/* Top Row: Score Gauge + Sub-factors */}
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<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
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<GlobalScoreGauge score={globalScore / 10} confidence={confidence} />
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<SubFactorsBreakdown subFactors={subFactors} />
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</div>
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{/* Treemap */}
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<OpportunityTreemap
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data={treemapData}
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title="Mapa de Oportunidades por Volumen y Readiness"
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height={300}
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/>
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{/* Skills Table */}
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<SkillsReadinessTable heatmapData={data.heatmapData} />
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</div>
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);
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}
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export default AgenticReadinessTab;
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