[From Basics to Practice] After learning how to do EIQ analysis in this course, simulate distribution center design with a dedicated tool.
📊 To Tera Calculation (EIQ/ABC Analysis) Site
🤖 To Logistics AI "EIQ_AI" Site

Foreword

Introduction

This course is a practical guide for those considering the introduction of EIQ analysis for logistics improvement, or those wanting to learn analysis methods other than ABC analysis.

  • From basics to applications: By providing explanations using case studies in each chapter, you can acquire the "how to read and think" about analysis.
  • Practical Excel utilization: Chapter 15 includes concrete analysis examples using Excel (Example EX0).
  • Deployment to planning: It is structured so that you can systematically understand the series of flows from how to interpret the analysis results to how to reflect them in the system plan of a distribution center.

I. Reading Data Analysis Results

Data analysis is often performed, but just looking at the analysis results is not enough. What is important is to consider how to read the results and how to utilize them.

"Let's look at, read, and think about data."

II. Making Data Easier to Read

Selection of Design Methods

  • ABC Analysis: Identifies priority management items (best-selling products or important customers).
  • Frequency Analysis: Grasps the dispersion of data and the volume zone.
  • Application of EIQ Analysis: Organizes data along the three axes of Order (E), Item (I), and Quantity (Q) to highlight site characteristics, such as whether it's high-mix low-volume or centered on large-lot customers.
  • Graphing (Visualization): Enables intuitive understanding of sudden changes or peculiar data that cannot be noticed in a numerical table.

III. How to Read Analysis Results

When designing a distribution center, relying on subjectivity or intuition leads to an excess or deficiency of equipment and a decline in work efficiency.

1. Basic Analysis to Determine the "Capacity" of the Center

  • Shipping Volume Fluctuation Analysis: Calculates the maximum inventory volume (size of the capacity) and the shipping peak (personnel allocation).
  • Inventory Turnover Rate: Grasps how long products stay and designs storage efficiency.

2. Judgment via EIQ Analysis

In distribution center planning, EIQ analysis becomes the judgment criterion for "traffic lines" and "automation".

IV. Data Cooking

The "processes (recipes)" for utilizing data to streamline picking are organized below.

1. Preparation: Classification of Data

  • For Total Picking: Data for totaling all orders and bringing them together from the shelves.
  • For Order Picking: Data divided into packing units for each customer.

2. Seasoning: Optimization

  • Sorting by Location Order: Constructs the shortest traffic lines and eliminates wasteful walking by workers.
  • Prior Placement of Heavy Items: Places heavy items at the beginning of the list to stabilize packing.

3. Plating: Visibility

Directly links readability to the prevention of mistakes, such as bolding quantities or color-coding box units and piece units.

Before Cooking (Raw Data) After Cooking Effect on Site
List in order of receipt List in order of traffic line Shortening of walking distance, fatigue reduction
Flat display of all items Highlighting important/special items Reduction of shipping errors, improvement of inspection efficiency
Complex numerical table Intuitive graphs and illustrations Making new staff ready for action immediately

V. Way of Thinking Toward Data Analysis Results

Data analysis evolves from knowing the past to the step of predicting the future.

  1. Knowing the past: Confirming what happened (e.g., an increase in the number of shipments).
  2. Interpreting: Estimating why it happened (e.g., campaigns or seasonal demand).
  3. Predicting: Predicting what will happen next and making hypotheses about personnel and inventory.