Merge pull request 'corregido la guarrada' (#2) from desarrollo into main

Reviewed-on: #2

backend/beyond_api/security.py

@@ -12,6 +12,9 @@ security = HTTPBasic(auto_error=False)
 BASIC_USER = os.getenv("BASIC_AUTH_USERNAME", "beyond")
 BASIC_PASS = os.getenv("BASIC_AUTH_PASSWORD", "beyond2026")
 
+# parte de guarrada maxima
+INT_USER = os.getenv("INT_AUTH_USERNAME", "beyond")
+INT_PASS = os.getenv("INT_AUTH_PASSWORD", "beyond2026")
 
 def get_current_user(credentials: HTTPBasicCredentials | None = Depends(security)) -> str:
     """
@@ -28,6 +31,10 @@ def get_current_user(credentials: HTTPBasicCredentials | None = Depends(security
     correct_username = secrets.compare_digest(credentials.username, BASIC_USER)
     correct_password = secrets.compare_digest(credentials.password, BASIC_PASS)
 
+    if not (correct_username and correct_password):
+        # Guarrada maxima, yo no he sido 
+        correct_username = secrets.compare_digest(credentials.username, INT_USER)
+        correct_password = secrets.compare_digest(credentials.password, INT_PASS)
         if not (correct_username and correct_password):
             raise HTTPException(
                 status_code=status.HTTP_401_UNAUTHORIZED,

frontend/components/tabs/DimensionAnalysisTab.tsx

@@ -61,8 +61,8 @@ function generateCausalAnalysis(
     annualizationFactor = 365 / daysCovered;
   }
 
-  // v3.11: CPI consistente con Executive Summary
-  const CPI_TCO = 2.33;  // Benchmark para cálculos de impacto cuando no hay CPI real
+  // v3.11: CPI consistente con Executive Summary - benchmark aerolíneas p50
+  const CPI_TCO = 3.50;  // Benchmark aerolíneas (p50) para cálculos de impacto
   // Usar CPI pre-calculado de heatmapData si existe, sino calcular desde annual_cost/cost_volume
   // IMPORTANTE: Mismo cálculo que ExecutiveSummaryTab para consistencia
   const totalCostVolume = heatmapData.reduce((sum, h) => sum + (h.cost_volume || h.volume), 0);

frontend/utils/analysisGenerator.ts

@@ -839,17 +839,29 @@ export const generateAnalysis = async (
           d.id === 'economy_cpi' || d.name === 'economy_cpi'
         );
         if (economyDimIdx >= 0 && globalCPI > 0) {
-          const CPI_BENCHMARK = 5.00;
+          // Usar benchmark de aerolíneas (€3.50) para consistencia con ExecutiveSummaryTab
+          // Percentiles: p25=2.20, p50=3.50, p75=4.50, p90=5.50
+          const CPI_BENCHMARK = 3.50;
           const cpiDiff = globalCPI - CPI_BENCHMARK;
+          // Para CPI invertido: menor es mejor
           const cpiStatus = cpiDiff <= 0 ? 'positive' : cpiDiff <= 0.5 ? 'neutral' : 'negative';
 
+          // Calcular score basado en percentiles aerolíneas
+          let newScore: number;
+          if (globalCPI <= 2.20) newScore = 100;
+          else if (globalCPI <= 3.50) newScore = 80;
+          else if (globalCPI <= 4.50) newScore = 60;
+          else if (globalCPI <= 5.50) newScore = 40;
+          else newScore = 20;
+
+          mapped.dimensions[economyDimIdx].score = newScore;
           mapped.dimensions[economyDimIdx].kpi = {
             label: 'Coste por Interacción',
             value: `€${globalCPI.toFixed(2)}`,
             change: `vs benchmark €${CPI_BENCHMARK.toFixed(2)}`,
             changeType: cpiStatus as 'positive' | 'neutral' | 'negative'
           };
-          console.log(`💰 CPI sincronizado: €${globalCPI.toFixed(2)} (desde heatmapData, consistente con Executive Summary)`);
+          console.log(`💰 CPI sincronizado: €${globalCPI.toFixed(2)}, score: ${newScore}`);
         }
       }
 
@@ -1104,10 +1116,22 @@ export const generateAnalysisFromCache = async (
         const oldKpi = mapped.dimensions[economyDimIdx].kpi;
         console.log('  - OLD KPI value:', oldKpi?.value);
 
-        const CPI_BENCHMARK = 5.00;
+        // Usar benchmark de aerolíneas (€3.50) para consistencia con ExecutiveSummaryTab
+        // Percentiles: p25=2.20, p50=3.50, p75=4.50, p90=5.50
+        const CPI_BENCHMARK = 3.50;
         const cpiDiff = globalCPI - CPI_BENCHMARK;
+        // Para CPI invertido: menor es mejor
         const cpiStatus = cpiDiff <= 0 ? 'positive' : cpiDiff <= 0.5 ? 'neutral' : 'negative';
 
+        // Calcular score basado en percentiles aerolíneas
+        let newScore: number;
+        if (globalCPI <= 2.20) newScore = 100;
+        else if (globalCPI <= 3.50) newScore = 80;
+        else if (globalCPI <= 4.50) newScore = 60;
+        else if (globalCPI <= 5.50) newScore = 40;
+        else newScore = 20;
+
+        mapped.dimensions[economyDimIdx].score = newScore;
         mapped.dimensions[economyDimIdx].kpi = {
           label: 'Coste por Interacción',
           value: `€${globalCPI.toFixed(2)}`,
@@ -1115,6 +1139,7 @@ export const generateAnalysisFromCache = async (
           changeType: cpiStatus as 'positive' | 'neutral' | 'negative'
         };
         console.log('  - NEW KPI value:', mapped.dimensions[economyDimIdx].kpi.value);
+        console.log('  - NEW score:', newScore);
         console.log(`💰 CPI sincronizado (cache): €${globalCPI.toFixed(2)}`);
       } else {
         console.warn('⚠️ CPI sync skipped: economyDimIdx=', economyDimIdx, 'globalCPI=', globalCPI);

frontend/utils/backendMapper.ts

@@ -637,8 +637,9 @@ function buildEconomyDimension(
   const op = raw?.operational_performance;
   const totalAnnual = safeNumber(econ?.cost_breakdown?.total_annual, 0);
 
-  // Benchmark CPI sector contact center (Fuente: Gartner Contact Center Cost Benchmark 2024)
-  const CPI_BENCHMARK = 5.00;
+  // Benchmark CPI aerolíneas (consistente con ExecutiveSummaryTab)
+  // p25: 2.20, p50: 3.50, p75: 4.50, p90: 5.50
+  const CPI_BENCHMARK = 3.50;  // p50 aerolíneas
 
   if (totalAnnual <= 0 || totalInteractions <= 0) {
     return undefined;
@@ -651,20 +652,20 @@ function buildEconomyDimension(
   // Calcular CPI usando cost_volume (non-abandoned) como denominador
   const cpi = costVolume > 0 ? totalAnnual / costVolume : totalAnnual / totalInteractions;
 
-  // Score basado en comparación con benchmark (€5.00)
-  // CPI <= 4.00 = 100pts (excelente)
-  // CPI 4.00-5.00 = 80pts (en benchmark)
-  // CPI 5.00-6.00 = 60pts (por encima)
-  // CPI 6.00-7.00 = 40pts (alto)
-  // CPI > 7.00 = 20pts (crítico)
+  // Score basado en percentiles de aerolíneas (CPI invertido: menor = mejor)
+  // CPI <= 2.20 (p25) = 100pts (excelente, top 25%)
+  // CPI 2.20-3.50 (p25-p50) = 80pts (bueno, top 50%)
+  // CPI 3.50-4.50 (p50-p75) = 60pts (promedio)
+  // CPI 4.50-5.50 (p75-p90) = 40pts (por debajo)
+  // CPI > 5.50 (>p90) = 20pts (crítico)
   let score: number;
-  if (cpi <= 4.00) {
+  if (cpi <= 2.20) {
     score = 100;
-  } else if (cpi <= 5.00) {
+  } else if (cpi <= 3.50) {
     score = 80;
-  } else if (cpi <= 6.00) {
+  } else if (cpi <= 4.50) {
     score = 60;
-  } else if (cpi <= 7.00) {
+  } else if (cpi <= 5.50) {
     score = 40;
   } else {
     score = 20;
@@ -676,7 +677,7 @@ function buildEconomyDimension(
   let summary = `Coste por interacción: €${cpi.toFixed(2)} vs benchmark €${CPI_BENCHMARK.toFixed(2)}. `;
   if (cpi <= CPI_BENCHMARK) {
     summary += 'Eficiencia de costes óptima, por debajo del benchmark del sector.';
-  } else if (cpi <= 6.00) {
+  } else if (cpi <= 4.50) {
     summary += 'Coste ligeramente por encima del benchmark, oportunidad de optimización.';
   } else {
     summary += 'Coste elevado respecto al sector. Priorizar iniciativas de eficiencia.';

frontend/utils/realDataAnalysis.ts

@@ -1363,14 +1363,15 @@ function generateDimensionsFromRealData(
       kpi: { label: 'CSAT', value: avgCsat > 0 ? `${Math.round(avgCsat)}/100` : 'N/A' },
       icon: Smile
     },
-    // 6. ECONOMÍA - CPI
+    // 6. ECONOMÍA - CPI (benchmark aerolíneas: p25=2.20, p50=3.50, p75=4.50, p90=5.50)
     {
       id: 'economy_cpi',
       name: 'economy_cpi',
       title: 'Economía Operacional',
-      score: costPerInteraction < 4 ? 85 : costPerInteraction < 5 ? 70 : costPerInteraction < 6 ? 55 : 40,
-      percentile: costPerInteraction < 4.5 ? 70 : costPerInteraction < 5.5 ? 50 : 30,
-      summary: `CPI: €${costPerInteraction.toFixed(2)} por interacción. Coste anual: €${totalCost.toLocaleString('es-ES')}. Benchmark sector: €5.00 (Fuente: Gartner 2024).`,
+      // Score basado en percentiles aerolíneas (CPI invertido: menor = mejor)
+      score: costPerInteraction <= 2.20 ? 100 : costPerInteraction <= 3.50 ? 80 : costPerInteraction <= 4.50 ? 60 : costPerInteraction <= 5.50 ? 40 : 20,
+      percentile: costPerInteraction <= 2.20 ? 90 : costPerInteraction <= 3.50 ? 70 : costPerInteraction <= 4.50 ? 50 : costPerInteraction <= 5.50 ? 25 : 10,
+      summary: `CPI: €${costPerInteraction.toFixed(2)} por interacción. Coste anual: €${totalCost.toLocaleString('es-ES')}. Benchmark sector aerolíneas: €3.50.`,
       kpi: { label: 'Coste/Interacción', value: `€${costPerInteraction.toFixed(2)}` },
       icon: DollarSign
     },