Report Thumbnail
Product Code MM0913421467XS
Published Date 2023/9/26
MarketsandMarkets
English327 PagesGlobal

Smart Warehousing Market by Offering (Hardware, Software, Services), Technology (AI & Analytics, Robotics & Automation), Application (Inventory Management, Predictive Analytics), Warehouse Size, Vertical and Region - Global Forecast to 2028 ‐ Telecom_Media_ICT_Digital Market


Report Thumbnail
Product Code MM0913421467XS◆The Sep 2025 edition is also likely available. We will check with the publisher immediately.
Published Date 2023/9/26
MarketsandMarkets
English 327 PagesGlobal

Smart Warehousing Market by Offering (Hardware, Software, Services), Technology (AI & Analytics, Robotics & Automation), Application (Inventory Management, Predictive Analytics), Warehouse Size, Vertical and Region - Global Forecast to 2028 ‐ Telecom_Media_ICT_Digital Market


Abstract

Summary

The smart warehousing market is projected to grow from USD 20.4 billion in 2023 to USD 40.5 billion by 2028, at a compound annual growth rate (CAGR) of 14.6% during the forecast period. The market is anticipated to grow due to the emergence of multi-channel distribution networks, and the rising focus on green initiatives and sustainability to minimize waste. By offering hardware segment to register for largest market size during forecast period The hardware segment includes radio frequency identification systems, sensor networks, real-time location systems, automated guided vehicles, autonomous mobile robots, conveyor systems, and other hardware (routers, switches, access points). A rise in the demand for IoT, sensors, and AI technologies among users to optimize warehouse operations has influenced vendors to develop smart warehousing hardware. A smart warehouse solution helps warehouse managers to monitor and track goods in real time based on their types and usage. By vertical, healthcare & life sciences segment to register fastest growing CAGR during the forecast period In the healthcare distribution ecosystem, continuous sharing of information and visibility of every process are the determinants for efficient warehouse management. Smart warehousing enables clear visibility of logistic activities in the healthcare industry, enabling proper tracking of medicines and medical devices. Further, small batch sizes, the short shelf life of medicines, and the need for clean storage and controlled environmental conditions are the key factors driving the growth of automated warehouses in the healthcare industry. Leading healthcare and life sciences companies are using smart warehousing solutions to carry out their critical warehousing operations, such as quality control, safety precautions, and tracking of expiration dates of drugs. Large warehouses to witness the largest market size during the forecast period The smart warehousing market for large warehouses is experiencing significant growth, driven by several compelling factors. Large warehouses, often serving as distribution centers for major retailers and e-commerce giants, require sophisticated software solutions to manage vast inventories and streamline complex logistics operations. One of the primary growth drivers is the increasing emphasis on automation and scalability to meet the ever-growing demand for fast and accurate order fulfillment. Breakdown of primaries In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the smart warehousing market.  By Company: Tier I: 38%, Tier II: 50%, and Tier III: 12%  By Designation: C-Level Executives: 35%, D-Level Executives: 40%, and Managers: 25%  By Region: North America: 40%, Europe: 30%, Asia Pacific: 20%, and Middle East and Africa- 5%, Latin America-5% The report includes the study of key players offering smart warehousing solutions. It profiles major vendors in the smart warehousing market. The major players in the smart warehousing market include Manhattan Associates (US), Korber (Germany), Oracle (US), SAP (Germany), Tecsys (Canada), PSI Logistics (Germany), PTC (US), Reply (Italy), Infor (US), IBM (US), Blue Yonder (US), Generix Group (France), Microlistics (Australia), ABB (Switzerland), Microsoft (US), Epicor (US), Made4net (US), Mantis (US), Softeon (US), Synergy Logistics (US), E2open (US), Vinculum (India), Mecalux (Spain), SSI Schaefer (US), WareIQ (India), Foysonis (India), Increff (India), Locus Robotics (US), ShipHero (US), Cin7 (US), EasyEcom (India), Unicommerce (India), and IAM Robotics (US). Research coverage The smart warehousing market research study involved extensive secondary sources, directories, journals, and paid databases. Primary sources were mainly industry experts from the core and related industries, preferred smart warehousing providers, third-party service providers, consulting service providers, end users, and other commercial enterprises. In-depth interviews were conducted with various primary respondents, including key industry participants and subject matter experts, to obtain and verify critical qualitative and quantitative information, and assess the market’s prospects. Key Benefits of Buying the Report The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall smart warehousing market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities. The report provides insights on the following pointers: • Analysis of key drivers (proliferation of smartphones for faster and more efficient management of goods, emergence of multi-channel distribution networks, dynamic nature and globalization of supply chain networks, and the rising focus on green initiatives and sustainability to minimize waste), restraints (lack of uniform governance standards in the fragmented supply chain and logistics industry, data security and privacy concerns), opportunities ( advent of AR and VR technologies to streamline warehouse operations, focus on Warehouse 4.0 for a more efficient and safer warehouse, advancements in self-driving vehicles and robotics for warehouse automation), and challenges (lack of awareness about benefits of smart warehousing among small-scale industries, slow adoption of smart warehousing solutions due to high capital investment, high implementation and maintenance costs for SMEs). • Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the smart warehousing market • Market Development: Comprehensive information about lucrative markets – the report analyses the smart warehousing market across varied regions • Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the smart warehousing market • Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players like include Manhattan Associates (US), Korber (Germany), Oracle (US), SAP (Germany), Tecsys (Canada), PSI Logistics (Germany), PTC (US), Reply (Italy), Infor (US), IBM (US), Blue Yonder (US) among others in the smart warehousing market strategies. The report also helps stakeholders understand the pulse of the smart warehousing market and provides them with information on key market drivers, restraints, challenges, and opportunities.

Table of Contents

  • 1 INTRODUCTION 47

    • 1.1 STUDY OBJECTIVES 47
    • 1.2 MARKET DEFINITION 47
      • 1.2.1 INCLUSIONS AND EXCLUSIONS 48
    • 1.3 MARKET SCOPE 49
      • 1.3.1 MARKET SEGMENTATION 49
      • 1.3.2 REGIONS COVERED 50
      • 1.3.3 YEARS CONSIDERED 50
    • 1.4 CURRENCY CONSIDERED 50
    • 1.5 STAKEHOLDERS 51
    • 1.6 SUMMARY OF CHANGES 51
      • 1.6.1 IMPACT OF RECESSION 51

  • 2 RESEARCH METHODOLOGY 52

    • 2.1 RESEARCH DATA 52
      • 2.1.1 SECONDARY DATA 53
      • 2.1.2 PRIMARY DATA 53
        • 2.1.2.1 Breakup of primary profiles 54
        • 2.1.2.2 Key industry insights 54
    • 2.2 MARKET BREAKUP AND DATA TRIANGULATION 55
    • 2.3 MARKET SIZE ESTIMATION 56
      • 2.3.1 TOP-DOWN APPROACH 56
      • 2.3.2 BOTTOM-UP APPROACH 57
    • 2.4 MARKET FORECAST 60
    • 2.5 RESEARCH ASSUMPTIONS 61
    • 2.6 LIMITATIONS 63
    • 2.7 IMPLICATIONS OF RECESSION ON SMART WAREHOUSING MARKET 63

  • 3 EXECUTIVE SUMMARY 65

  • 4 PREMIUM INSIGHTS 72

    • 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN SMART WAREHOUSING MARKET 72
    • 4.2 OVERVIEW OF RECESSION IMPACT ON GLOBAL SMART WAREHOUSING MARKET 73
    • 4.3 SMART WAREHOUSING MARKET: TOP THREE APPLICATIONS 73
    • 4.4 NORTH AMERICA: SMART WAREHOUSING MARKET, BY OFFERING AND TOP THREE VERTICALS 74
    • 4.5 SMART WAREHOUSING MARKET: BY REGION 74

  • 5 MARKET OVERVIEW AND INDUSTRY TRENDS 75

    • 5.1 INTRODUCTION 75
    • 5.2 MARKET DYNAMICS 76
      • 5.2.1 DRIVERS 76
        • 5.2.1.1 Rising focus on green initiatives and sustainability to minimize waste 76
        • 5.2.1.2 Proliferation of smartphones for faster and efficient management of goods 77
        • 5.2.1.3 Emergence of multi-channel distribution networks 77
        • 5.2.1.4 Dynamic nature and globalization of supply chain networks 78
      • 5.2.2 RESTRAINTS 78
        • 5.2.2.1 Lack of uniform governance standards in fragmented logistics industry 78
        • 5.2.2.2 Data security and privacy concerns 78
      • 5.2.3 OPPORTUNITIES 79
        • 5.2.3.1 Adoption of AR and VR technologies to streamline warehouse operations 79
        • 5.2.3.2 Rising focus on Warehouse 4.0 to reduce operating costs 79
        • 5.2.3.3 Advancements in self-driving vehicles and robotics 79
      • 5.2.4 CHALLENGES 80
        • 5.2.4.1 Lack of awareness among small-scale industries 80
        • 5.2.4.2 High implementation and maintenance costs for SMEs 80
    • 5.3 BRIEF HISTORY OF SMART WAREHOUSING 81
    • 5.4 ARCHITECTURE: SMART WAREHOUSING MARKET 82
    • 5.5 CASE STUDY ANALYSIS 84
      • 5.5.1 TRANSPORTATION & LOGISTICS 84
        • 5.5.1.1 Americold deploys Blue Yonder WMS to modernize warehouse environment 84
        • 5.5.1.2 Automated warehouse solutions from Körber help Pharmalog deal with high order volume 84
        • 5.5.1.3 Locus assists BigBasket to achieve 99.5% on-time delivery for 10 million customers 85
        • 5.5.1.4 FM Logistic Russia chooses Generix SaaS-based WMS to improve operational efficiency 85
      • 5.5.2 HEALTHCARE & LIFE SCIENCES 86
        • 5.5.2.1 Sanford Health improves patient care and safety with Tecsys software 86
        • 5.5.2.2 Tecsys WMS solution helps NMHS achieve annual savings of USD 8 million 86
        • 5.5.2.3 Drogaria Araujo opts for Körber’s WMS to increase stock traceability 87
      • 5.5.3 MANUFACTURING 87
        • 5.5.3.1 Etilux Group implements Körber's WMS to streamline inventory 87
        • 5.5.3.2 Epicor Kinetic helps Finnish manufacturer focus on international growth 87
        • 5.5.3.3 SOLOCHAIN streamlines Marucci Sports’ warehouse process 88
      • 5.5.4 FOOD & BEVERAGES 89
        • 5.5.4.1 Generix WMS enables Lactalis Spain to pilot different types of warehouses 89
        • 5.5.4.2 Dutch food company relies on ABB robots to optimize delivery process 89
        • 5.5.4.3 EasyEcom helps Paper Boat improve order processing 89
      • 5.5.5 RETAIL & ECOMMERCE 90
        • 5.5.5.1 Körber WMS helps Adore Beauty keep up with growing sales 90
        • 5.5.5.2 Eventyrsport deploys Tecsys’ Omni WMS to manage growing inventory 91
        • 5.5.5.3 Conforama uses Generix WMS to increase warehouse production capacity 91
      • 5.5.6 ENERGY & UTILITIES 91
        • 5.5.6.1 Körber WMS helps GRTgaz configure personalized strategies 91
        • 5.5.6.2 Puget Sound Energy successfully implements SAP Extended Warehouse Management Application 92
      • 5.5.7 AUTOMOTIVE 92
        • 5.5.7.1 Mitsubishi deploys Körber WMS to address challenges of manual warehouse operations 92
        • 5.5.7.2 Click Reply solution allows Dana Italia to speed up warehouse processes 93
      • 5.5.8 AGRICULTURE 93
        • 5.5.8.1 Thai Agro Exchange Co. opts for Körber solutions to serve wholesale clients better 93
    • 5.6 TARIFF AND REGULATORY LANDSCAPE 94
      • 5.6.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 94
      • 5.6.2 NORTH AMERICA 94
      • 5.6.3 EUROPE 96
      • 5.6.4 ASIA PACIFIC 96
      • 5.6.5 MIDDLE EAST & AFRICA 97
      • 5.6.6 LATIN AMERICA 97
    • 5.7 ECOSYSTEM/MARKET MAP 98
    • 5.8 PATENT ANALYSIS 100
      • 5.8.1 METHODOLOGY 100
      • 5.8.2 PATENTS FILED, BY DOCUMENT TYPE 100
      • 5.8.3 INNOVATION AND PATENT APPLICATIONS 100
        • 5.8.3.1 Top applicants 101
    • 5.9 SUPPLY CHAIN ANALYSIS 105
    • 5.10 FUTURE DIRECTION OF SMART WAREHOUSING MARKET LANDSCAPE 106
    • 5.11 PRICING ANALYSIS 107
      • 5.11.1 AVERAGE SELLING PRICE OF KEY COMPANIES 107
      • 5.11.2 INDICATIVE PRICING ANALYSIS 107
    • 5.12 TRENDS AND DISRUPTIONS IMPACTING BUYERS/CLIENTS’ BUSINESSES 108
    • 5.13 PORTER’S FIVE FORCES ANALYSIS 109
      • 5.13.1 THREAT OF NEW ENTRANTS 110
      • 5.13.2 THREAT OF SUBSTITUTES 110
      • 5.13.3 BARGAINING POWER OF SUPPLIERS 110
      • 5.13.4 BARGAINING POWER OF BUYERS 110
      • 5.13.5 INTENSITY OF COMPETITIVE RIVALRY 110
    • 5.14 KEY CONFERENCES AND EVENTS, 2023-2024 111
    • 5.15 KEY STAKEHOLDERS AND BUYING CRITERIA 112
      • 5.15.1 KEY STAKEHOLDERS IN BUYING PROCESS 112
      • 5.15.2 BUYING CRITERIA 112
    • 5.16 TECHNOLOGY ANALYSIS 113
      • 5.16.1 KEY TECHNOLOGY 113
        • 5.16.1.1 Artificial Intelligence and Machine Learning (AI and ML) 113
        • 5.16.1.2 IoT 114
        • 5.16.1.3 Predictive Analytics 114
      • 5.16.2 ADJACENT TECHNOLOGY 114
        • 5.16.2.1 Blockchain 114
        • 5.16.2.2 Cloud Computing 114
        • 5.16.2.3 AR/VR 115
        • 5.16.2.4 Digital Twins 115
    • 5.17 BUSINESS MODEL ANALYSIS 115
      • 5.17.1 SUPPLY SIDE 115
      • 5.17.2 DEMAND SIDE 116
    • 5.18 HS CODES (ALTERNATIVE TO TRADE ANALYSIS) 117
      • 5.18.1 EXPORT SCENARIO 117
      • 5.18.2 IMPORT SCENARIO 118

  • 6 SMART WAREHOUSING MARKET, BY OFFERING 119

    • 6.1 INTRODUCTION 120
      • 6.1.1 DRIVERS: SMART WAREHOUSING MARKET, BY OFFERING 120
    • 6.2 HARDWARE 121
      • 6.2.1 RADIO FREQUENCY IDENTIFICATION SYSTEMS (RFID) 123
        • 6.2.1.1 Passive RFID 124
          • 6.2.1.1.1 Growing usage due to affordability to drive market 124
        • 6.2.1.2 Active RFID 124
          • 6.2.1.2.1 Increasing adoption of Internet of Things (IoT) to boost demand 124
      • 6.2.2 SENSOR NETWORKS 124
        • 6.2.2.1 Environmental Sensors 125
          • 6.2.2.1.1 Growing focus on sustainability to drive demand 125
        • 6.2.2.2 Motion Sensors 125
          • 6.2.2.2.1 Ability to enhance operational efficiency to boost demand 125
        • 6.2.2.3 Proximity Sensors 126
          • 6.2.2.3.1 Rising adoption to reduce energy consumption to drive market 126
      • 6.2.3 REAL-TIME LOCATION SYSTEMS (RTLS) 126
        • 6.2.3.1 Indoor RTLS 127
          • 6.2.3.1.1 Growing need for precise tracking to fuel market 127
        • 6.2.3.2 Outdoor RTLS 127
          • 6.2.3.2.1 Ability to provide end-to-end visibility to drive demand 127
        • 6.2.3.3 Ultra-Wideband (UWB) RTLS 127
          • 6.2.3.3.1 Need for high precision levels to boost market 127
      • 6.2.4 AUTOMATED GUIDED VEHICLES (AGV) 127
        • 6.2.4.1 AGV for Material Handling 128
          • 6.2.4.1.1 Demand for seamless material handling to fuel market 128
        • 6.2.4.2 AGV for Picking 128
          • 6.2.4.2.1 Need to accelerate order fulfillment to drive market 128
        • 6.2.4.3 AGV for Sorting 129
          • 6.2.4.3.1 Growth of omnichannel retailing to fuel demand 129
      • 6.2.5 AUTONOMOUS MOBILE ROBOTS (AMR) 129
        • 6.2.5.1 AMR for Inventory Scanning 130
          • 6.2.5.1.1 Need for greater efficiency in inventory management to drive market 130
        • 6.2.5.2 AMR for Order Fulfillment 130
          • 6.2.5.2.1 Booming e-commerce industry to propel market growth 130
        • 6.2.5.3 AMR for Material Handling 130
          • 6.2.5.3.1 Demand for faster delivery times to boost market 130
      • 6.2.6 CONVEYOR SYSTEMS 130
        • 6.2.6.1 Belt Conveyors 131
          • 6.2.6.1.1 Demand for quicker material handling to drive market 131
        • 6.2.6.2 Roller Conveyors 131
          • 6.2.6.2.1 High versatility to boost demand 131
        • 6.2.6.3 Slat Conveyors 132
          • 6.2.6.3.1 Suitability to harsh environments to drive demand 132
      • 6.2.7 OTHER HARDWARE 132
    • 6.3 SOFTWARE 133
      • 6.3.1 WAREHOUSE MANAGEMENT SYSTEM (WMS) 135
        • 6.3.1.1 Growth of e-commerce to drive market 135
      • 6.3.2 INVENTORY MANAGEMENT SOFTWARE 136
        • 6.3.2.1 Need to optimize inventory control and reduce operational costs to drive demand 136
      • 6.3.3 COLLABORATION AND COMMUNICATION TOOLS 137
        • 6.3.3.1 Rising demand for seamless coordination to fuel market 137
      • 6.3.4 SIMULATION AND MODELING SOFTWARE 138
        • 6.3.4.1 Availability of cost-effective testing process to boost market 138
      • 6.3.5 LABOR MANAGEMENT SOFTWARE (LMS) 139
        • 6.3.5.1 Need to improve labor performance to drive market 139
      • 6.3.6 WAREHOUSE CONTROL SYSTEM (WCS) 140
        • 6.3.6.1 Growing adoption of advanced technologies to fuel demand 140
      • 6.3.7 OTHER SOFTWARE 141
    • 6.4 SMART WAREHOUSING SOFTWARE MARKET, BY DEPLOYMENT MODE 142
      • 6.4.1 CLOUD 143
        • 6.4.1.1 Easy scalability and cost-effectiveness to boost demand 143
      • 6.4.2 ON-PREMISES 144
        • 6.4.2.1 Reduced security risk to drive adoption 144
    • 6.5 SERVICES 145
      • 6.5.1 PROFESSIONAL SERVICES 147
        • 6.5.1.1 Training & Consulting 149
          • 6.5.1.1.1 Rising need for specialized knowledge to fuel market 149
        • 6.5.1.2 System Integration & Implementation 150
          • 6.5.1.2.1 Need for seamless integration of solutions into IT environment to drive demand 150
        • 6.5.1.3 Support & Maintenance 151
          • 6.5.1.3.1 Requirement for regular maintenance and upgrades to boost market 151
      • 6.5.2 MANAGED SERVICES 151

  • 7 SMART WAREHOUSING MARKET, BY TECHNOLOGY 153

    • 7.1 INTRODUCTION 154
      • 7.1.1 DRIVERS: SMART WAREHOUSING MARKET, BY TECHNOLOGY 154
    • 7.2 IOT 155
      • 7.2.1 RISING NEED FOR IOT-POWERED PREDICTIVE MAINTENANCE TO DRIVE MARKET 155
    • 7.3 ROBOTICS AND AUTOMATION 156
      • 7.3.1 ABILITY TO IMPROVE OPERATIONAL EFFICIENCY TO DRIVE MARKET 156
    • 7.4 AI AND ANALYTICS 157
      • 7.4.1 SIGNIFICANT OPTIMIZATION OF INVENTORY MANAGEMENT TO BOOST DEMAND 157
    • 7.5 NETWORKING AND COMMUNICATION 158
      • 7.5.1 INCREASING DEMAND FOR CONNECTIVITY TO FUEL MARKET 158
    • 7.6 AR AND VR 159
      • 7.6.1 POTENTIAL TO IMPROVE WORKER PRODUCTIVITY TO BOOST DEMAND 159
    • 7.7 OTHER TECHNOLOGIES 160

  • 8 SMART WAREHOUSING MARKET, BY APPLICATION 162

    • 8.1 INTRODUCTION 163
      • 8.1.1 DRIVERS: SMART WAREHOUSING MARKET, BY APPLICATION 163
    • 8.2 INVENTORY MANAGEMENT 164
      • 8.2.1 REAL-TIME INVENTORY TRACKING 165
        • 8.2.1.1 Barcode Scanning 165
          • 8.2.1.1.1 Increasing adoption of real-time scanning to drive market 165
        • 8.2.1.2 RFID-based Tracking 166
          • 8.2.1.2.1 Need for error-free workflows to boost market 166
        • 8.2.1.3 GPS-based Tracking 166
          • 8.2.1.3.1 Growing demand for end-to-end visibility and timely deliveries to fuel market 166
      • 8.2.2 INVENTORY OPTIMIZATION 166
        • 8.2.2.1 Dynamic Reordering 166
          • 8.2.2.1.1 Need for just-in-time replenishment of goods to drive market 166
        • 8.2.2.2 Safety Stock Management 167
          • 8.2.2.2.1 Ability to prevent stockouts and supply chain disruptions to drive demand 167
        • 8.2.2.3 Demand Sensing 167
          • 8.2.2.3.1 Rising demand from retail industry to drive market growth 167
    • 8.3 ORDER FULFILLMENT 167
      • 8.3.1 PICKING AND PACKING AUTOMATION 168
        • 8.3.1.1 Robotic Pickers 168
          • 8.3.1.1.1 Need for faster order fulfillment to boost demand 168
        • 8.3.1.2 Goods-to-Person Systems 168
          • 8.3.1.2.1 Ability to increase storage density within warehouses to fuel demand 168
        • 8.3.1.3 Collaborative Robots (Cobots) 169
          • 8.3.1.3.1 Suitability to repetitive tasks to boost demand 169
      • 8.3.2 ORDER ROUTING AND OPTIMIZATION 169
        • 8.3.2.1 Route Planning Algorithms 169
          • 8.3.2.1.1 Increasing demand for swift deliveries to drive adoption 169
        • 8.3.2.2 Multi-channel Order Management 169
          • 8.3.2.2.1 Rising popularity of omnichannel retailing to push demand 169
        • 8.3.2.3 Dynamic Slotting 170
          • 8.3.2.3.1 Need to adapt to changing product mixes to drive market 170
    • 8.4 ASSET TRACKING 170
      • 8.4.1 EQUIPMENT AND VEHICLE TRACKING 171
        • 8.4.1.1 GPS Tracking 171
          • 8.4.1.1.1 Rising demand for real-time visibility to boost market 171
        • 8.4.1.2 Telematics Systems 171
          • 8.4.1.2.1 Need for insights into vehicle performance and driver behavior to push demand 171
        • 8.4.1.3 Condition Monitoring 171
          • 8.4.1.3.1 Potential for continuous monitoring of equipment to drive market 171
      • 8.4.2 PRODUCT AND PACKAGE TRACKING 172
        • 8.4.2.1 RFID Tagging 172
          • 8.4.2.1.1 Affordability and versatility to boost demand 172
        • 8.4.2.2 Smart Packaging 172
          • 8.4.2.2.1 Growing usage to reduce product spoilage to drive market 172
        • 8.4.2.3 Blockchain-based Tracking 172
          • 8.4.2.3.1 Need for transparency in food and pharmaceutical industries to encourage adoption 172
    • 8.5 PREDICTIVE ANALYTICS 173
      • 8.5.1 DEMAND FORECASTING MODELS 173
        • 8.5.1.1 Machine Learning-based Forecasting 174
          • 8.5.1.1.1 Ability to optimize inventory management to fuel demand 174
        • 8.5.1.2 Time Series Analysis 174
          • 8.5.1.2.1 Potential to facilitate predictive maintenance to encourage adoption 174
        • 8.5.1.3 Bayesian Forecasting 174
          • 8.5.1.3.1 Need for risk management and scenario planning to drive demand 174
      • 8.5.2 PREDICTIVE MAINTENANCE 174
        • 8.5.2.1 Sensor-based Predictive Maintenance 175
          • 8.5.2.1.1 Ability to prevent costly breakdowns to propel demand 175
        • 8.5.2.2 AI-driven Predictive Maintenance 175
          • 8.5.2.2.1 Increasing adoption to predict equipment failures to drive market 175
        • 8.5.2.3 Failure Mode and Effects Analysis (FMEA) 175
          • 8.5.2.3.1 Growing need to address vulnerabilities to push adoption 175
    • 8.6 OTHER APPLICATIONS 175

  • 9 SMART WAREHOUSING MARKET, BY WAREHOUSE SIZE 177

    • 9.1 INTRODUCTION 178
      • 9.1.1 DRIVERS: SMART WAREHOUSING MARKET, BY WAREHOUSE SIZE 178
    • 9.2 SMALL 179
      • 9.2.1 MICRO WAREHOUSES 180
        • 9.2.1.1 Increasing demand for quicker last-mile delivery services to boost market 180
      • 9.2.2 SMALL-SCALE DISTRIBUTION CENTERS 180
        • 9.2.2.1 Potential to streamline logistics operations to drive market 180
    • 9.3 MEDIUM 180
      • 9.3.1 REGIONAL WAREHOUSES 181
        • 9.3.1.1 Increasing demand for same-day deliveries to boost market 181
      • 9.3.2 CROSS-DOCKING FACILITIES 181
        • 9.3.2.1 Rising demand for speedy shipping to drive market growth 181
    • 9.4 LARGE 182
      • 9.4.1 NATIONAL DISTRIBUTION CENTERS 183
        • 9.4.1.1 Demand for faster order fulfillment to fuel market 183
      • 9.4.2 MEGA WAREHOUSES 183
        • 9.4.2.1 Surge in e-commerce to create demand for mega storage spaces 183

  • 10 SMART WAREHOUSING MARKET, BY VERTICAL 184

    • 10.1 INTRODUCTION 185
      • 10.1.1 DRIVERS: SMART WAREHOUSING MARKET, BY VERTICAL 185
    • 10.2 TRANSPORTATION AND LOGISTICS 186
      • 10.2.1 THIRD-PARTY LOGISTICS (3PL) COMPANIES 187
        • 10.2.1.1 Rising demand for e-commerce fulfillment services to spur market growth 187
      • 10.2.2 FREIGHT FORWARDERS 188
        • 10.2.2.1 Focus on sustainability and green logistics to drive market 188
      • 10.2.3 LAST-MILE DELIVERY PROVIDERS 188
        • 10.2.3.1 Rising demand for same-day deliveries to propel demand 188
    • 10.3 MANUFACTURING 188
      • 10.3.1 DISCRETE 189
        • 10.3.1.1 Shift toward cloud-based smart warehousing solutions to drive market 189
      • 10.3.2 PROCESS 190
        • 10.3.2.1 Need to improve operational efficiency and meet regulatory requirements to boost demand 190
    • 10.4 HEALTHCARE AND LIFE SCIENCES 190
      • 10.4.1 PHARMACEUTICAL WAREHOUSING 191
        • 10.4.1.1 Pressure to optimize supply chains to drive demand 191
      • 10.4.2 MEDICAL DEVICE WAREHOUSING 191
        • 10.4.2.1 Demand for agile and responsive supply chains to fuel market 191
      • 10.4.3 HOSPITAL SUPPLY CHAIN MANAGEMENT 191
        • 10.4.3.1 Focus on cost-effective healthcare delivery to boost adoption 191
    • 10.5 FOOD AND BEVERAGES 192
      • 10.5.1 COLD CHAIN LOGISTICS 193
        • 10.5.1.1 Potential to reduce risk of human error to drive demand 193
      • 10.5.2 NON-PERISHABLE LOGISTICS 193
        • 10.5.2.1 E-commerce boom to encourage adoption 193
    • 10.6 RETAIL AND E-COMMERCE 193
      • 10.6.1 BRICK AND MORTAR RETAIL 194
      • 10.6.2 E-COMMERCE RETAIL 194
        • 10.6.2.1 Online Marketplaces 195
          • 10.6.2.1.1 Need for increased efficiency and sustainability to drive market 195
        • 10.6.2.2 Direct-to-Consumer (DTC) Brands 195
          • 10.6.2.2.1 Growing demand for customization to drive market 195
    • 10.7 ENERGY AND UTILITIES 195
      • 10.7.1 OIL AND GAS 196
        • 10.7.1.1 Potential to facilitate predictive maintenance to drive demand 196
      • 10.7.2 RENEWABLE ENERGY 196
        • 10.7.2.1 Need for efficient storage facilities to fuel demand 196
      • 10.7.3 UTILITIES 196
        • 10.7.3.1 Requirement for real-time monitoring to encourage adoption 196
      • 10.7.4 MINING AND RESOURCES 197
        • 10.7.4.1 Ability to monitor environmental conditions and ensure worker safety to drive demand 197
    • 10.8 AGRICULTURE 197
    • 10.9 OTHER VERTICALS 198

  • 11 SMART WAREHOUSING MARKET, BY REGION 199

    • 11.1 INTRODUCTION 200
    • 11.2 NORTH AMERICA 201
      • 11.2.1 NORTH AMERICA: SMART WAREHOUSING MARKET DRIVERS 202
      • 11.2.2 NORTH AMERICA: RECESSION IMPACT 202
      • 11.2.3 US 211
        • 11.2.3.1 Need for faster and more efficient supply chain operations to drive market 211
      • 11.2.4 CANADA 211
        • 11.2.4.1 Booming e-commerce industry to increase demand for smart warehousing 211
    • 11.3 EUROPE 212
      • 11.3.1 EUROPE: SMART WAREHOUSING MARKET DRIVERS 212
      • 11.3.2 EUROPE: RECESSION IMPACT 212
      • 11.3.3 UK 219
        • 11.3.3.1 Increasing need for efficient order fulfillment solutions to drive market 219
      • 11.3.4 GERMANY 220
        • 11.3.4.1 Rising focus on automation in manufacturing and logistics to fuel market 220
      • 11.3.5 FRANCE 220
        • 11.3.5.1 Growing logistics and retail sectors to boost demand 220
      • 11.3.6 SPAIN 220
        • 11.3.6.1 Increasing adoption of AI & ML to boost market 220
      • 11.3.7 ITALY 221
        • 11.3.7.1 Emphasis on digital transformation in logistics sector to drive demand 221
      • 11.3.8 REST OF EUROPE 221
    • 11.4 ASIA PACIFIC 221
      • 11.4.1 ASIA PACIFIC: SMART WAREHOUSING MARKET DRIVERS 222
      • 11.4.2 ASIA PACIFIC: RECESSION IMPACT 222
      • 11.4.3 CHINA 230
        • 11.4.3.1 Rising need for warehouse automation to drive market 230
      • 11.4.4 JAPAN 231
        • 11.4.4.1 Growing e-commerce industry to boost adoption of smart warehousing solutions 231
      • 11.4.5 INDIA 231
        • 11.4.5.1 Increasing need for faster delivery processes to drive market 231
      • 11.4.6 SOUTH KOREA 231
        • 11.4.6.1 Rapid integration of automation and robotics in warehouses to drive market 231
      • 11.4.7 AUSTRALIA & NEW ZEALAND 232
        • 11.4.7.1 Commitment to sustainability to encourage adoption of eco-friendly warehousing solutions 232
      • 11.4.8 ASEAN COUNTRIES 232
        • 11.4.8.1 Surge in adoption of smart warehousing to drive market 232
      • 11.4.9 REST OF ASIA PACIFIC 233
    • 11.5 MIDDLE EAST & AFRICA 233
      • 11.5.1 MIDDLE EAST & AFRICA: SMART WAREHOUSING MARKET DRIVERS 234
      • 11.5.2 MIDDLE EAST & AFRICA: RECESSION IMPACT 234
      • 11.5.3 UAE 242
        • 11.5.3.1 Government initiatives to boost market 242
      • 11.5.4 SAUDI ARABIA 242
        • 11.5.4.1 Investments in logistics infrastructure and digitalization to drive market growth 242
      • 11.5.5 SOUTH AFRICA 242
        • 11.5.5.1 Focus on improving logistics infrastructure to bolster demand 242
      • 11.5.6 ISRAEL 243
        • 11.5.6.1 Increasing use of AI-driven predictive analytics to drive market 243
      • 11.5.7 REST OF MIDDLE EAST & AFRICA 243
    • 11.6 LATIN AMERICA 243
      • 11.6.1 LATIN AMERICA: SMART WAREHOUSING MARKET DRIVERS 244
      • 11.6.2 LATIN AMERICA: RECESSION IMPACT 244
      • 11.6.3 BRAZIL 252
        • 11.6.3.1 Government initiatives to promote digital transformation to drive market 252
      • 11.6.4 MEXICO 252
        • 11.6.4.1 Demand from automotive and electronics sectors to fuel market 252
      • 11.6.5 ARGENTINA 252
        • 11.6.5.1 Need to improve supply chain efficiency to bolster demand 252
      • 11.6.6 REST OF LATIN AMERICA 253

  • 12 COMPETITIVE LANDSCAPE 254

    • 12.1 OVERVIEW 254
    • 12.2 STRATEGIES ADOPTED BY KEY PLAYERS 254
    • 12.3 BUSINESS SEGMENT REVENUE ANALYSIS 256
      • 12.3.1 BUSINESS SEGMENT REVENUE ANALYSIS 257
    • 12.4 MARKET SHARE ANALYSIS 258
    • 12.5 COMPANY EVALUATION MATRIX, 2022 259
      • 12.5.1 STARS 259
      • 12.5.2 EMERGING LEADERS 259
      • 12.5.3 PERVASIVE PLAYERS 259
      • 12.5.4 PARTICIPANTS 259
      • 12.5.5 COMPANY FOOTPRINT 261
    • 12.6 STARTUP/SME EVALUATION MATRIX 263
      • 12.6.1 PROGRESSIVE COMPANIES 263
      • 12.6.2 RESPONSIVE COMPANIES 263
      • 12.6.3 DYNAMIC COMPANIES 263
      • 12.6.4 STARTING BLOCKS 263
      • 12.6.5 COMPETITIVE BENCHMARKING 265
    • 12.7 BRAND/PRODUCT COMPARATIVE ANALYSIS 266
      • 12.7.1 COMPARATIVE ANALYSIS OF SMART WAREHOUSING PRODUCTS 266
    • 12.8 VALUATION AND FINANCIAL METRICS OF KEY SMART WAREHOUSING VENDORS 268
    • 12.9 COMPETITIVE SCENARIO AND TRENDS 269
      • 12.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS 269
      • 12.9.2 DEALS 270

  • 13 COMPANY PROFILES 273

    • 13.1 INTRODUCTION 273
    • 13.2 KEY PLAYERS 273
      • 13.2.1 MANHATTAN ASSOCIATES 273
      • 13.2.2 KÖRBER 277
      • 13.2.3 ORACLE 280
      • 13.2.4 SAP 283
      • 13.2.5 TECSYS 287
      • 13.2.6 PSI LOGISTICS 291
      • 13.2.7 PTC 294
      • 13.2.8 REPLY 297
      • 13.2.9 INFOR 300
      • 13.2.10 IBM 302
      • 13.2.11 BLUE YONDER 305
    • 13.3 OTHER KEY PLAYERS 307
      • 13.3.1 GENERIX GROUP 307
      • 13.3.2 MICROLISTICS 307
      • 13.3.3 ABB 308
      • 13.3.4 MICROSOFT 308
      • 13.3.5 EPICOR 309
      • 13.3.6 MADE4NET 309
      • 13.3.7 MANTIS 310
      • 13.3.8 SOFTEON 310
      • 13.3.9 SYNERGY LOGISTICS 311
      • 13.3.10 E2OPEN 311
      • 13.3.11 VINCULUM 312
      • 13.3.12 MECALUX 312
      • 13.3.13 SSI SCHAEFER 313
    • 13.4 STARTUP/SME PROFILES 313
      • 13.4.1 WAREIQ 313
      • 13.4.2 FOYSONIS 314
      • 13.4.3 INCREFF 314
      • 13.4.4 LOCUS ROBOTICS 315
      • 13.4.5 SHIPHERO 315
      • 13.4.6 CIN7 ORDERHIVE 316
      • 13.4.7 EASYECOM 316
      • 13.4.8 UNICOMMERCE 317
      • 13.4.9 IAM ROBOTICS 317
      • 13.4.10 LOGIWA 318

  • 14 ADJACENT AND RELATED MARKETS 319

    • 14.1 INTRODUCTION 319
    • 14.2 LOGISTICS AUTOMATION MARKET - GLOBAL FORECAST TO 2028 319
      • 14.2.1 MARKET DEFINITION 319
      • 14.2.2 MARKET OVERVIEW 319
        • 14.2.2.1 Logistics automation market, by component 319
        • 14.2.2.2 Logistics automation market, by function 320
        • 14.2.2.3 Logistics automation market, by logistics type 321
        • 14.2.2.4 Logistics automation market, by organization size 321
        • 14.2.2.5 Logistics automation market, by vertical 322
        • 14.2.2.6 Logistics automation market, by software application 323
        • 14.2.2.7 Logistics automation market, by region 324
    • 14.3 SUPPLY CHAIN ANALYTICS MARKET - GLOBAL FORECAST TO 2027 324
      • 14.3.1 MARKET DEFINITION 324
      • 14.3.2 MARKET OVERVIEW 324
        • 14.3.2.1 Supply chain analytics market, by component 325
        • 14.3.2.2 Supply chain analytics market, by service 325
        • 14.3.2.3 Supply chain analytics market, by deployment mode 326
        • 14.3.2.4 Supply chain analytics market, by organization size 327
        • 14.3.2.5 Supply chain analytics market, by vertical 327
        • 14.3.2.6 Supply chain analytics market, by region 328

  • 15 APPENDIX 330

    • 15.1 DISCUSSION GUIDE 330
    • 15.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 336
    • 15.3 CUSTOMIZATION OPTIONS 338
    • 15.4 RELATED REPORTS 338
    • 15.5 AUTHOR DETAILS 339
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