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INNOVATION PROJECT

Warehouse Layout
Optimization

Data-Driven Picking Efficiency & Smart Inventory Placement

TEAM MG Warehouse Operations
DEPARTMENT Supply Chain & Logistics
SLIDE 02

Problem Statement

The Core Challenge: Reduce picking time with data-driven approach & organized layout setup

Root Cause: Unorganized layout optimization for high-demand parts

Scattered Inventory

Fast-moving parts mapped across multiple locations, causing excessive search times and picking delays

LAYOUT ISSUE

High MHE Dependency

Over-reliance on Material Handling Equipment slows processes, increases operational cost & safety risks

COST DRIVER

Extended Picking Times

Inefficient routing & parts placement result in extended picking cycle times, impacting order fulfillment speed

EFFICIENCY GAP

No Data-Driven Placement

Parts mapping doesn't reflect market demand. High-dispatch items stored in upper locations causing operator fatigue

DATA GAP
SLIDE 03

Proposed Solution

Defining the picking affecting factors & preparing countermeasure goals

PRIMARY GOALS

Transform the MG warehouse into a data-driven, high-efficiency operation

Reduce Average Picking Time
Optimize Floor Space Utilization
Align Material Placement as per Market Demand
01
FACTOR 1

Seasonal Demand Analysis

Summer high-demand part positioning on floor — filters, radiators, coolants & solvents

Air & Oil Filters Radiators & Coolers Coolants & Solvents
02
FACTOR 2

Top Dealers Profiling

Top 10 dealers' most ordered parts moved to ground locations for faster picking process

MG Majestor MG CyberStar MG MIFA-9 MG Astor MG Hector MG ZSEV
03
FACTOR 3

Product Lifecycle Management

Phase-out model parts moved UP, NPI fast-moving model parts moved DOWN on locations

NPI MODEL ↓ PHASE OUT ↑
SLIDE 04

Seasonal Demand Mapping

Summer season demand surge for filters, radiators, coolers & coolants — creating dedicated hot zones

Seasonal Demand Index — Parts Category
Air Filters
Oil Filters
Radiators
Coolers
Coolants
Solvents
Warehouse Zone Layout — After Optimization
🔧
FILTER ZONE
All fast-moving filter parts mapped on floor
GROUND LEVEL
💧
SHELF LINE ZONE
All liquid, coolants & solvent parts on floor
GROUND LEVEL
🏗️
MHE REDUCTION
Significant reduction in MHE movement after zone creation
KEY OUTCOME
SLIDE 05

Impact: Seasonal Demand Mapping

Measurable improvements from filter & coolant zone creation

BEFORE
MHE fatigue — multiple movements throughout whole day
High lead time — multiple locations & height locations
Scattered parts picking increases operational fatigue
12 min avg. pick time per order
ZONE
CREATION
AFTER
Reduced average picking time by –40%
Optimized workflow — less dependency on MHE
Simple movement — reduced operator fatigue
8 min avg. pick time per order
–33% Picking Time
(1224→816 mins/day)
–56% MHE Distance
(9180→4080 mtrs/day)
–5 km Daily Trip Distance
Saved
–1 hr MHE Operating Time
Saved Daily
SLIDE 06

Product Lifecycle Management

Relocation Tactics: Data analysis & mapping strategy for phase-out vs NPI models

Phase-Out Classification Criteria
📉
Sales Velocity Decline
Threshold: <5 units/month
Parts showing >80% sales decline over 18 months
📋
Manufacturer Notice
Immediate Action
Official discontinued model EOL announced
📦
Inventory Aging
Age: >18+ months
Part in stock >18 months with minimal movement
📊
Market Demand Drop
Model Years: 5+ Years
Reduced market demand for specific model
Models Identification & Relocation Strategy
NPI MODEL ↓ GROUND
MG MajestorMG CyberStarMG MIFA-9
PHASE OUT ↑ UPPER
MG AstorMG HectorMG ZSEV
139 Ground locations freed from non-moving items
→
79 Upper locations with regular fast-moving visits
→
218 Total locations optimized via interchange
SLIDE 07

Dead Stock Liquification

Storage zone-wise dead stock (>1 Year) classification & optimization

MDR
3,832Locations
3.52LQty
₹3.44CrValue
HDR
1,231Locations
36.7KQty
₹13.75CrValue
SDR
96Locations
2.14KQty
₹1.71CrValue
Lock & Key
95Locations
2.16KQty
₹0.24CrValue
BEFORE LIQUIFICATION
Total Dead Stock SKU 5,254 SKU
Locked Capital ₹19.15 Crores
Area Occupied 6,200 Sq.ft
Monthly Holding Cost ₹1,09,585/mo
LIQUIFIED
AFTER LIQUIFICATION
Locations Utilized 5,254 Locations
Capital Liquidified ₹19.15 Crores
Space Evacuated 6,200 Sq.ft
Monthly Cost Saved ₹1,09,585/mo
SLIDE 08

Implementation Roadmap

Four-phase execution plan from data extraction to performance optimization

01
PHASE: IDENTIFICATION

Data Extraction & Analysis

  • Data extracted for parts with >18 months dispatch records
  • Analysis for dealer-centralized fast-moving items
  • Analysis for NPI models fast-moving parts
02
PHASE: PLANNING

Classification & Slotting

  • Identified floor locations occupied by non-moving items
  • Identified upper zone locations with fast-moving items
  • Relocation roadmap prepared for part interchange
  • Non-moving UP, fast-moving/NPI parts DOWN
03
PHASE: EXECUTION

Physical Relocation

  • Location-wise target set in 3 phases with immediate effect
  • Radiator parts moved to ground zone in storage bins
  • Filter Zone created for faster picking process
  • SP01 area defined on floor; Back Order Area created
04
PHASE: OPTIMIZATION

Performance Monitoring

  • Daily monitoring of hand-pick rate
  • Daily monitoring of filter & coolant dispatch records
  • Daily tracking report for hot zones picking rate
  • Dashboard preparation for real-time visibility
SLIDE 09

Impacts & Benefits

Quantified results across picking time, MHE movement & space optimization

⏱
–33%
Picking Time Reduction
Before:102 × 12 = 1,224 mins/day
After:102 × 8 = 816 mins/day
Saved:408 mins/day
67% efficiency retained → 33% time saved
🏗
–56%
MHE Movement Reduction
Before:102 × 90 = 9,180 mtrs/day
After:102 × 40 = 4,080 mtrs/day
Saved:5,100 mtrs (5 km)/day
44% distance retained → 56% MHE reduction
📦
27.82%
Space Optimization
Optimized:6,096 locations
Total:21,910 locations
Formula:6096/21910 = 27.82%
27.82% of total locations optimized
Location Optimization Breakdown
139Ground non-moving
+
79Upper fast-moving
+
624Filter zone
+
1,231Coolant/Radiator
+
3,832Dead stock
+
96+95SDR/Lock&Key
=
6,096Total Optimized
MGIC INNOVATION PROJECT

Thank You

Warehouse Layout Optimization & Data-Driven Picking Efficiency

–33% Picking Time
–56% MHE Movement
27.82% Space Optimized
₹19.15Cr Capital Freed