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Reports & Analytics

The Reports & Analytics module provides comprehensive visualization and analysis tools for production quality, commercial performance, and yield metrics. Reports FTQ Reports Commercial

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Overview

The module is organized into three analytical dashboards, each addressing specific business intelligence needs:
Quality conformity analysis with control charts and defect Pareto.

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Global Filters

All dashboards share a consistent filter toolbar for data slicing:

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Filter Options

Filter data by production location.Options: All 40 GINEZ branches + “All”Visibility:
  • Admin/Quality Manager: All branches available
  • Branch Manager: Locked to assigned branch
  • Preparador: Locked to assigned branch
Filters apply instantly to all charts and KPIs without page reload. Use the refresh button to reload data from the server.

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First Time Quality (FTQ) Dashboard

The FTQ dashboard focuses on quality conformity analysis with statistical process control charts.

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Key Performance Indicators

Total Registros

Total batch count and volume produced (Liters)Displays:
  • Number of batches
  • Total liters produced

Total Conformes

Conforming batches count and percentage.FTQ Metric: First Time Quality rate (target: >95%)

Semi-Conformes

Batches within tolerance range.Indicates process capability needs improvement.

No Conformes

Failing batches requiring rework or scrap.Triggers NCR creation.

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Pareto Chart: Defects by Parameter

Purpose: Identify the most frequent quality defects to prioritize corrective actions. Chart Type: Combined Bar + Line Chart Data Displayed:
  • Bars: Count of defects by parameter (pH, Sólidos, Apariencia)
  • Line: Cumulative percentage of defects
How to Read:
  1. Tallest bar = most frequent defect
  2. Cumulative line shows 80/20 rule
  3. Focus corrective actions on top defects
Example Interpretation: 
Defect      | Count | Cumulative %
------------|-------|-------------
Sólidos     | 45    | 60%
pH          | 20    | 87%
Apariencia  | 10    | 100%
Action: Address solids control first (60% of defects).

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Conformity by Branch (Stacked Bar Chart)

Purpose: Compare quality performance across branches. Chart Type: Stacked Bar Chart Data Displayed:
  • Green Stack: Conforming batches
  • Yellow Stack: Semi-conforming batches
  • Red Stack: Non-conforming batches
Sorting: Branches sorted by total production volume (descending) Use Cases:
  • Identify branches needing quality training
  • Recognize high-performing branches
  • Allocate quality resources geographically

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Control Chart: % Solids Conformity

Purpose: Visualize solids measurement conformity over time with specification and tolerance limits. Chart Type: Scatter Plot with Reference Lines Elements:
  • Data Points: Individual batch measurements (scatter)
  • Red Lines: Specification limits (min and max from PRODUCT_STANDARDS)
  • Yellow Lines: Tolerance limits (±5% relative error)
Color Coding:
  • Green Points: Within specification (Conforme)
  • Yellow Points: Within tolerance (Semi-Conforme)
  • Red Points: Outside tolerance (No Conforme)
How to Use:
  1. Select a specific product from filters
  2. Observe if points trend toward limits
  3. Identify systematic drift vs. random variation
  4. Use for process capability analysis
Control charts only display when a specific product is selected (not “All”). This ensures accurate specification limit rendering.
Example: 
Product: DETDON (Detergente Don)
Spec: 22-28% solids
Tolerance: 20.9-29.4% solids

Chart shows:
- Most points green (22-28)
- Few yellow points (20.9-22 or 28-29.4)
- Any red points require investigation

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Control Chart: pH Conformity

Purpose: Monitor pH measurements against specification limits. Chart Type: Line Chart with Reference Lines Elements:
  • Line: pH measurements over time
  • Red Lines: pH specification limits (min and max)
Color Coding:
  • Green Segments: Within specification
  • Red Segments: Outside specification
Use Cases:
  • Detect pH drift over production runs
  • Identify equipment calibration needs
  • Verify raw material pH consistency

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Commercial Analysis Dashboard

The Commercial Analysis dashboard provides production volume insights by product hierarchy.

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KPI Summary Cards

Similar to FTQ dashboard but focused on volume metrics:
  • Total Registros (batches)
  • Volumen Total (liters)
  • Piezas Total (pieces for certain categories)

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Production by Branch (Bar Chart)

Purpose: Compare production volume across branches. Chart Type: Bar Chart Y-Axis: Liters or Pieces (depending on dominant product type) Sorting: Descending by volume Top 3 Highlight: Top 3 branches displayed in summary cards

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Production by Family (Donut Charts)

Purpose: Visualize production mix by product family. Chart Type: Donut Chart (one per family) Families Displayed:
  1. Cuidado del Hogar (Home Care)
  2. Lavandería (Laundry)
  3. Cuidado Personal (Personal Care)
  4. Línea Automotriz (Automotive)
  5. Línea Antibacterial (Antibacterial)
  6. Productos Intermedios (Intermediate)
Drill-Down Feature:
  • Click a family donut to open category breakdown modal
  • Modal shows products within each category
  • Displays volume and percentage per product
Example Drill-Down: 
Family: Lavandería
  ├── Detergente Ropa: 5,000 L (50%)
  │   ├── DETDON: 2,000 L
  │   ├── GIRIEL: 1,500 L
  │   └── PERGIN: 1,500 L
  ├── Suavizante: 3,000 L (30%)
  └── Especialidades: 2,000 L (20%)

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Top Products Ranking (Bar Chart)

Purpose: Identify best-selling SKUs for inventory and demand planning. Chart Type: Horizontal Bar Chart Display Options:
  • Default: Top 10 products
  • Expanded: Toggle to show all products
Category Filter: Dropdown to filter by specific category Data Displayed:
  • Product Code (SKU)
  • Volume (Liters or Pieces)
  • Horizontal bar (scaled to max product volume)
Color Scheme: Corporate GINEZ colors (red/blue palette) Use Cases:
  • Demand forecasting
  • Raw material planning
  • Production scheduling
  • Sales team insights

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Product Variants Distribution (Top 20)

Purpose: Analyze SKU proliferation and production diversity. Chart Type: Bar Chart Display: Top 20 products by volume Insights:
  • Identify long-tail SKUs
  • Assess product line complexity
  • Support SKU rationalization decisions

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SPY (Standard Product Yield) Dashboard

The SPY dashboard tracks production efficiency and raw material consumption.
This is a separate sub-module with dedicated page: /reportes/spy

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Purpose

Measure actual yield against theoretical yield to identify:
  • Raw material waste
  • Process inefficiencies
  • Formula accuracy
  • Equipment losses

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Key Metrics

SPY Calculation: 
SPY (%) = (Actual Output / Theoretical Output) × 100

Where:
- Actual Output = Recorded batch size (Liters)
- Theoretical Output = Formula yield at 100% efficiency
Target: SPY ≥ 98% (industry standard)

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SPY KPI Cards

Average SPY

Mean yield percentage across all batches.Color codes:
  • Green: Above 98%
  • Yellow: 95-97.9%
  • Red: Below 95%

Best SPY

Highest yield batch with product code.Benchmark for optimization.

Worst SPY

Lowest yield batch with product code.Requires investigation.

Total Waste

Cumulative liters lost to inefficiency.Calculation: Sum of (Theoretical - Actual)

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SPY by Product (Bar Chart)

Purpose: Compare yield performance across products. Chart Type: Bar Chart with Target Line Elements:
  • Bars: Average SPY per product
  • Reference Line: 98% target
  • Color coding: Above/below target
Sorting: By SPY percentage (ascending) Use Cases:
  • Identify problematic formulas
  • Prioritize process improvement
  • Validate formula changes

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SPY Trend Over Time (Line Chart)

Purpose: Monitor yield performance trends. Chart Type: Time Series Line Chart X-Axis: Manufacturing date Y-Axis: SPY percentage Reference Lines:
  • 98% target (green dashed)
  • 95% minimum acceptable (yellow dashed)
Use Cases:
  • Detect yield degradation over time
  • Verify effectiveness of improvement actions
  • Correlate yield with raw material batches

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Raw Material Consumption Analysis

Purpose: Track ingredient usage efficiency. Data Displayed:
  • Material Code
  • Theoretical Consumption (kg or L)
  • Actual Consumption (from inventory system)
  • Variance (%)
Color Coding:
  • Green: Within ±2% variance
  • Yellow: ±2-5% variance
  • Red: >5% variance
Raw material consumption data requires integration with inventory system. Speak with IT to enable this feature.

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Access Control by Role

Access: LimitedVisible Dashboards:
  • ✅ First Time Quality (FTQ)
  • ✅ SPY Dashboard
  • ❌ Commercial Analysis (restricted)
Data Scope: Own records onlyFilters: Branch locked, product and date available

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Best Practices

Recommended Workflow:
  1. Open FTQ Dashboard
  2. Set date range to “Last 7 days”
  3. Review conformity KPIs
  4. Check Pareto for new defect patterns
  5. Examine control charts for drift
  6. Create NCRs for outliers
  7. Schedule corrective actions
Recommended Workflow:
  1. Open Commercial Analysis Dashboard
  2. Set date range to “Last 30 days”
  3. Review production by branch
  4. Analyze top products ranking
  5. Check family distribution
  6. Forecast next month’s demand
  7. Plan raw material purchases
Recommended Workflow:
  1. Open SPY Dashboard
  2. Set date range to “Last 3 months”
  3. Identify lowest SPY products
  4. Analyze raw material variances
  5. Review process changes
  6. Implement improvement actions
  7. Track SPY trend for validation
When investigating quality issues:
  1. Use filters to isolate affected scope
  2. Compare conformity across branches
  3. Check if defects correlate with specific preparers
  4. Review control charts for patterns
  5. Cross-reference with raw material batches
  6. Document findings in NCR system

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Frequently Asked Questions

Control charts require a specific product selection.Solution: Use the “Product” filter and select a single SKU (not “All”).This ensures accurate specification and tolerance limits are displayed.
SPY (Standard Product Yield) measures efficiency:
SPY = (Actual Output ÷ Theoretical Output) × 100
Example:
  • Formula yields 100L theoretically
  • Actual batch produced 97L
  • SPY = (97 ÷ 100) × 100 = 97%
Target: ≥98%
Quality Managers and Admins: YesExport Options:
  • Excel (.xlsx) - Raw data tables
  • PDF - Dashboard snapshot
Location: Export button in top-right toolbarOther Roles: Contact admin for manual exports
FTQ (First Time Quality):
  • Measures product conformity to specifications
  • Focus: Does the product meet standards?
  • Example: 95% of batches conform on first attempt
SPY (Standard Product Yield):
  • Measures production efficiency
  • Focus: How much waste/loss occurred?
  • Example: 97% yield (3% material loss)
Both metrics are important for holistic quality management.

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