🔗 Relationship Between EIQ Matrix Table & Traditional Calculation

Mutual Relationship and Integrated Utilization of Two Logistics Analysis Methods

📋 Overview of the Relationship

🎯 Core Relationship
The EIQ Matrix Table and Traditional Calculation (Traditional Analysis) are mutually complementary logistics analysis methodologies developed by the same inventor, Toshiyuki Teramoto. Both generate output from the same underlying dataset (T200 master table) and apply an identical 5-tier rank classification system, achieving multi-dimensional and mathematically aligned analytics.

While each method can function independently, using them together delivers the greatest engineering insight. A phased analytical approach is recommended: establish macro volume distributions via Traditional Calculation first, then dissect two-dimensional intersections using the EIQ Matrix.

👤 Common Developer

🎓 Systematic Engineering by Toshiyuki Teramoto
Toshiyuki Teramoto of the Logistics Technology Institute developed these integrated methodologies to overcome the limitations of standard 3-tier ABC analysis for practical warehouse design:
  • EIQ Matrix Analysis: Visualizes the two-dimensional matrix relationship between Entry (customers) and Item (SKUs).
  • Traditional Calculation (5-Tier ABC): Subdivides conventional ABC analysis into 5 distinct stages matching EIQ rank definitions.

Engineered together from inception, both share identical ranking boundaries, aggregation logic, and volume metrics for seamless cross-validation.

🏗️ Common Foundation

1. Identical Data Source

📊 T200 Master Table (Extracted Shipping Dataset)

Both analyses process the filtered T200 table as their single source of truth.

Item Details
Table Name T200 (Extracted shipping master table)
Key Metrics Date, Item, Customer, Category, Line Counts, Pieces, Cases, Pallets, Volume (m³), Weight (kg)
Rank Columns CI Rank, CE Rank, BI Rank, BE Rank, IQ Category, E-Rank I, I-Rank E
Generation Event Generated when clicking "条件抽出_計算Bt"

2. Shared 5-Tier Ranking System

🎖️ 5-Stage Segmentation (A1, A2, B, C, D)

Both methodologies segment cumulative distribution ratios into an identical 5-stage ranking scale.

Rank Cumulative % Segment Share % Operational Focus
A1 0 - 50% ~5% Highest-density tier accounting for 50% of volume
A2 50 - 70% ~15% High-volume tier accounting for 20% of volume
B 70 - 85% ~30% Medium-volume tier accounting for 15% of volume
C 85 - 95% ~30% Low-volume tier accounting for 10% of volume
D 95 - 100% ~20% Ultra-low-volume tier accounting for 5% of volume

3. Common Physical Metrics

📦 Evaluated Logistics Units
  • Order Lines: Total number of pick line records (pick trips).
  • Piece Units: Quantity in loose individual pieces.
  • Case Units: Converted full case quantities.
  • Pallet Units: Converted full pallet loads.
  • Volume (m³): Total cubic meters.
  • Weight (kg): Total weight in kilograms.

📊 EIQ Matrix Analysis (In-Depth)

Analytical Features

🔍 Two-Dimensional Matrix Perspective
  • Core Focus: Analyzes the direct correlation between Entry (Customers) and Item (SKUs).
  • Structure: 5 × 5 Matrix Grid (25 cell intersections).
  • Rank Axes:
    • Horizontal Axis (I-Rank): Item SKU Ranks (I-A1 through I-D).
    • Vertical Axis (E-Rank): Customer Order Ranks (E-A1 through E-D).
  • Display Modes: Absolute Values, Row Cumulative Ratio A (I-direction), and Column Cumulative Ratio B (E-direction).

Sample EIQ Matrix Grid Layout

E-Rank
↓		 I-Rank (Item SKU) → Row Sum
I-A1 I-A2 I-B I-C I-D
E-A1 500 300 200 100 50 1,150
E-A2 200 150 100 80 30 560
E-B 100 80 60 40 20 300
E-C 50 40 30 20 10 150
E-D 20 15 10 8 5 58
Column Sum 870 585 400 248 115 2,218

📈 Traditional Calculation (In-Depth)

Analytical Features

🔍 Single-Axis Distribution Profile
  • Core Focus: Evaluates volume distribution aggregated along a single axis at a time.
  • Two Separate Axes:
    • By Item SKU: Categorizes items into CI/BI ranks based on volume.
    • By Customer: Categorizes customers into CE/BE ranks based on volume.
  • Structure: 1D summary table showing item count, order lines, and unit quantities per rank.

⚖️ Method Comparison

EIQ Matrix Analysis

  • Dimensionality: 2D (I-Rank × E-Rank)
  • Grid Size: 5 × 5 Matrix (25 Cell Intersections)
  • Primary Focus: SKU vs Customer Interaction Density
  • Engineering Use: Slotting, Pick Face Zoning, Conveyor Routing
  • Target Audience: Industrial Engineers, Warehouse Designers

Traditional Calculation

  • Dimensionality: 1D (Item Rank OR Customer Rank)
  • Grid Size: 5-Row Summary Table
  • Primary Focus: Macro Volume Concentration (Pareto Distribution)
  • Engineering Use: Storage Footprint, Vehicle Sizing, High-Level Resource Allocation
  • Target Audience: Executives, Operations Management

🔗 Data Correspondence Principles

📐 Mathematical Equivalences Between Tables
✅ Key Equality Rules:
  • Row Sum of EIQ Matrix Row (E-A1) = Total Line Count of Traditional Customer Rank CE-A1.
  • Column Sum of EIQ Matrix Column (I-A1) = Total Line Count of Traditional Item Rank CI-A1.
  • Grand Total of EIQ Matrix = Grand Total of Traditional Item or Customer Tables.

🔄 Recommended Engineering Workflow

  1. Step 1 (Macro Profiling): Open "Traditional Analysis" tab to evaluate overall SKU and customer volume distributions.
  2. Step 2 (Micro Intersections): Open "EIQ Data Analysis" tab to locate high-density matrix cells (e.g., E-A1 × I-A1).
  3. Step 3 (Validation): Confirm that column sums match CI-rank line totals and row sums match CE-rank line totals.
  4. Step 4 (Implementation): Assign high-density matrix cells to optimal pick zones and automated storage systems.