Smart Warehousing Market

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

Report Code: TC 7993 Sep, 2023, by marketsandmarkets.com

[260 Pages Report] 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. Due to various business drivers, the smart warehousing market is expected to grow significantly during the forecast period. The market is experiencing significant growth due to the increasing incidents of phishing emails and ransomware, and need to ensure consistent adherence to security policies and facilitates audit trails.    The rising cybersecurity threats and complexity, growing ability to detect and respond to security incidents in real-time is also responsible for driving the market’s growth.

Smart Warehousing Market

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Smart Warehousing Market

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Market Dynamics

Driver: Rising focus on green initiatives and sustainability to minimize waste 

The rising emphasis on green initiatives and sustainability, aimed at minimizing waste and reducing environmental impact, serves as a compelling driving force for the adoption of smart warehousing solutions in the market. These solutions employ advanced technologies like IoT sensors and automation to optimize resource utilization, energy efficiency, and waste reduction within warehouses, aligning with eco-friendly practices. Smart warehousing solutions promote energy efficiency through technologies like LED lighting and real-time data analytics, optimize transportation to reduce fuel consumption and emissions, and minimize waste through improved inventory management. They also contribute to resource optimization, support recycling and circular economy efforts, aid in regulatory compliance, and align with consumer preferences for environmentally responsible practices. Furthermore, by reducing operational costs and enhancing efficiency, smart warehousing solutions offer ecological and economic benefits, making them a vital component of modern, sustainable supply chain management.

Restraints: Data security privacy concerns

Enterprises adopting smart warehousing solutions face security and privacy issues. They possess confidential data, which needs to be protected to avoid data breaches and thefts, as it may affect the reputation of enterprises. The enterprises’ data may leak over the internet and can be accessed by unauthorized users, which is a growing concern. Cloud technology is a growing trend in the warehouse industry. IoT and automated material handling equipment have digitized warehouse operations, and the adoption of cloud technology has further transformed the warehousing and supply chain industry. The use of cloud technology has given rise to certain cybersecurity threats, including data privacy and security concerns, which arise with the rising complexity of smart warehousing solutions.

Opportunity: Advent of AR and VR technologies to streamline warehouse operations

Leveraging AR and VR technologies for warehouse management activities like order allocation, inventory control management, order picking, and material handling can simplify and improve complex warehouse operations, thereby enhancing supply chain processes. Moreover, AR and VR technologies are utilized to enhance worker training, improve operational efficiency, and provide real-time guidance. AR headsets or mobile devices overlay digital information onto the physical environment, assisting workers in locating items, navigating the warehouse, and performing tasks more effectively. VR simulations create immersive training environments for workers to practice skills, emergency response procedures, and equipment operation. For instance, DHL has successfully tested and implemented AR warehouse operations to improve its productivity. Using AR smart glasses, the company was able to use vision picking, which relies on remotely handling an order by picking the correct item and recording information about it without physically touching it. Furthermore, BMW uses AR and VR technologies to improve its production system and warehouse operations. The company’s employees use smart monitors to display information about the piece they’re working on, share it with other employees, and interact with the management by delivering the information that appears in the worker’s field of vision. Adopting AR and VR technologies in smart warehousing improves efficiency, reduces operational costs, minimizes errors, enhances safety, and provides a more agile and responsive supply chain. Thus, it creates significant opportunities in smart warehousing market as companies seek innovative solutions to remain competitive in an increasingly digital and automated world.

Challenge: Slow adoption of smart warehousing solutions due to high capital investment

The digitalization of warehouse operations requires high capital investments that involve the installation of automation equipment, software, and solutions, which incur heavy expenses. The replacement of existing processes is very costly. Another factor hindering the growth of the smart warehousing market is the slow adoption due to the integration complexities of multiple IoT platforms, numerous protocols, and a large number of APIs. The adoption of smart warehousing solutions is not picking up pace, due to the reluctance of organizations to shift from manual practices to the digitalized process involving high capital re-investment. Most enterprises have a laid-back attitude toward new digital technologies and use their intuition rather than adopting digital technologies to make informed business decisions. Hence, companies with limited financial resources are unable to opt for automation warehouse systems, thereby acting as a restraint to the growth of the smart warehousing market.

Smart Warehousing Market Ecosystem

Smart Warehousing Market

By software by deployment mode, on-premises software segment to account for a larger market size during forecast period

The on-premises deployment of smart warehousing hardware, solutions, and services is a more commonly used practice that offers enterprises the power to manage risks, business processes, and industry policies and enable compliance management. Security and compliance are major concerns for businesses to manage the ever-increasing demand for managing complex warehouse operations. The adoption of on-premises smart warehousing solutions reduces the security risk of handling a huge amount of logistic data.

By technology, IoT registers the highest CAGR during the forecast period

IoT technology has revolutionized the smart warehousing market by providing real-time visibility and control over inventory and operations. The growth of IoT in this sector is primarily driven by its ability to enhance supply chain efficiency, reduce operational costs, and improve inventory management. IoT sensors and devices enable continuous monitoring of warehouse conditions, such as temperature, humidity, and security, ensuring that goods are stored in optimal conditions and reducing the risk of spoilage or theft.

By region, North America holds the largest market size during the forecast period

North America will lead the smart warehousing market in 2023. North America, comprising the United States and Canada, is known for its advanced technology infrastructure and innovative industries, making it a hub for adopting smart warehousing technologies. The region's strong technology ecosystem and continuous innovation make it a key player in driving the development and adoption of these solutions globally.

Smart Warehousing Market Size, and Share

Key Market Players

The smart warehousing solution and service providers have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgrades, partnerships, and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. Some 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).

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Scope of the Report

Report Metrics

Details

Market size available for years

2017–2028

Base year considered

2022

Forecast period

2023–2028

Forecast units

USD (Billion)

Segments covered

Offering, Technology, Application, Warehouse Size, Vertical, and Region

Geographies covered

North America, Asia Pacific, Europe, Middle East & Africa, and Latin America

Companies covered

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).

This research report categorizes the smart warehousing market based on offering, technology, application, warehouse size, vertical, and region.

By Offering:
  • Hardware
    • Radio Frequency Identification Systems (RFID)
      • Passive
      • Active
    • Sensor Networks
      • Environmental Sensors
      • Motion Sensors
      • Proximity Sensors
    • Real-Time Location Systems (RTLS)
      • Indorr RTLS
      • Outdoor RTLS
      • Ultra-Wideband (UWB) RTLS
    • Automated Guided Vehicles (AGVs)
      • AGVs for Material Handling
      • AGVs for Picking
      • AGVs for Sorting
    • Autonomous Mobile Robots (AMRS)
      • AMRS for Inventory Scanning
      • AMRS for Order Fulfillment
      • AMRS for Material Handling
    • Conveyor Systems
      • Belt Conveyors
      • Roller Conveyors
      • Slat Conveyors
    • Other Hardware
  • Software
    • Warehouse management System (WMS) Software
    • Inventory Management Software
    • Collaboration and Communication Tools
    • Simulation and Modeling Software
    • Labor Management Software
    • Warehouse Control System (WCS)
    • Other Software
  • Software by Deployment Mode
    • Cloud
    • On-premises
  • Services
    • Professional Services
      • Training & Consulting
      • System Integration & Implementation
      • Support & Maintenance
    • Managed Services
By Technology:
  • IoT
  • Robotics and Automation
  • AI and Analytics
  • Networking and Communication
  • AR and VR
  • Other Technologies
By Application:
  • Inventory Management
    • Real-Time Inventory Tracking
      • Barcode Scanning
      • RFID based Tracking
      • GPS based Tracking
    • Inventory Optimization
      • Dynamic Reordering
      • Safety Stock Management
      • Demand Sensing
  • Order Fulfillment
    • Picking-and-Packing Automation
      • Robotic Pickers
      • Goods-to-Person Systems
      • Collaboration Robots (Cobots)
    • Order Routing and Optimization
      • Route Planning Algorithms
      • Multi-channel Order Management
      • Dynamic Slotting
  • Asset Tracking
    • Equipemnt and Vehicle Tracking
      • GPS Tracking
      • Telematics Systems
      • Condition Monitoring
    • Product and Package Tracking
      • RFID Tagging
      • Smart Packaging
      • Blockchain-based Tracking
  • Predictive Analytics
    • Demand Forecasting Models
      • Machine Learning based Forecasting
      • Time Series Analysis
      • Bayesian Forecasting
    • Predictive Maintenance
      • Sensor-based Predictive Maintenance
      • AI-Driven Predictive Maintenance
      • Failure-mode and Effects Analysis (FMEA)
  • Other Applications
By Warehouse Size:
  • Small
  • Medium
  • Large
By Vertical:
  • Transportation and Logistics
  • Manufacturing
  • Healthcare & Life Sciences
  • Retail & eCommerce
  • Food and Beverages
  • Energy & Utilities
  • Agriculture
  • Other Verticals
By Region:
  • North America
    • US
    • Canada
  • Europe
    • UK
    • Germany
    • France
    • Italy
    • Spain
    • Rest of Europe
  • Asia Pacific
    • China
    • India
    • Japan
    • Australia and New Zealand (ANZ)
    • South Korea
    • ASEAN Countries
    • Rest of Asia Pacific
  • Middle East & Africa
    • UAE
    • Saudi Arabia
    • South Africa
    • Israel
    • Rest of the Middle East & Africa
  • Latin America
    • Brazil
    • Mexico
    • Argentina
    • Rest of Latin America

Recent Developments:

  • In August 2023, Manhattan Associates announced PacSun, a leading specialty retailer of emerging youth brands and trending fashion, has selected Manhattan Active Point of Sale to enhance its omnichannel sales strategy and deliver a seamless, unified customer shopping experience.
  • In August 2023, Infor announced that Zofri will implement Infor WMS warehouse management system to improve customer service, one of the most important performance indicators in the supply chain. The Infor WMS solution will be deployed in the cloud, which is powered by AWS (Amazon Web Services), and will be implemented by Cerca Technology, Infor's partner in Latin America. 
  • In May 2023, Manhattan Associates announced its re-imagined Manhattan Active Yard Management solution to expand the company’s vision of a unified supply chain. By redesigning yard management to work seamlessly with its industry leading warehouse and transportation management solutions on a single cloud native platform, Manhattan is completing the digital unification of distribution and logistics where they come together in the physical world.
  • In March 2023, Raymour & Flanigan, the largest furniture and mattress retailer in the Northeast and seventh largest in the US, partners with Körber to respond more effectively to today’s consumer challenges through warehouse improvements pushing for greater order accuracy, speed, and customer fulfilment. This enables Raymour & Flanigan to build upon their long-standing legacy of bringing thoughtfully selected pieces of furniture to the places their customers serve, work and live while enhancing the customer shopping experience.
  • In January 2023, Tecsys announced its warehouse-in-a-warehouse e-commerce fulfillment solution enabling retailers and brands to execute e-commerce fulfillment flawlessly while leaving existing wholesale and distribution models and legacy systems largely intact.
  • In December 2022, Tecsys and SVT Robotics have partnered to develop and launch an out-of-the-box integrated connection between the Tecsys’ Elite supply chain platform and SVT's SOFTBOT Platform. The integration will provide Tecsys Elite customers faster deployment and lower complexity without the need for lengthy custom code development often involved in multi-system automation and robotics deployments.
  • In March 2022, Marks & Spencer Reliance India Pvt Ltd (M&S India), a British retailer, and IBM are collaborating to modernize the supply chain, promote connectivity among online and in-store operations, and enhance customer experience. With IBM Sterling Supply Chain Solutions, M&S is expanding its multichannel potential in India.

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TABLE OF CONTENTS
 
1 INTRODUCTION 
    1.1 OBJECTIVES OF THE STUDY 
    1.2 MARKET DEFINITION 
           1.2.1 INCLUSIONS AND EXCLUSIONS
    1.3 MARKET SCOPE 
           1.3.1 MARKET SEGMENTATION
           1.3.2 REGIONS COVERED
           1.3.3 YEARS CONSIDERED FOR THE STUDY
    1.4 CURRENCY CONSIDERED 
    1.5 STAKEHOLDERS 
    1.6 SUMMARY OF CHANGES  
           1.6.1 IMPACT OF RECESSION IN THE SMART WAREHOUSING MARKET 
 
2 RESEARCH METHODOLOGY 
    2.1 RESEARCH DATA 
           2.1.1 SECONDARY DATA
           2.1.2 PRIMARY DATA
                    2.1.2.1 BREAKUP OF PRIMARY PROFILES
                    2.1.2.2 KEY INDUSTRY INSIGHTS
    2.2 MARKET BREAKUP AND DATA TRIANGULATION 
    2.3 MARKET SIZE ESTIMATION 
           2.3.1 TOP-DOWN APPROACH
           2.3.2 BOTTOM-UP APPROACH
    2.4 MARKET FORECAST 
    2.5 COMPETITIVE EVALUATION MATRIX METHODOLOGY 
    2.6 STARTUP/SME EVALUATION MATRIX METHODOLOGY 
    2.7 ASSUMPTIONS FOR THE STUDY 
    2.8 LIMITATIONS OF THE STUDY 
    2.9 IMPLICATIONS OF RECESSION ON THE SMART WAREHOUSING MARKET  
 
3 EXECUTIVE SUMMARY 
 
4 PREMIUM INSIGHTS 
    4.1 ATTRACTIVE OPPORTUNITIES FOR COMPANIES IN THE SMART WAREHOUSING MARKET 
    4.2 SMART WAREHOUSING MARKET, BY OFFERING, 2023 VS. 2028 
    4.3 SMART WAREHOUSING MARKET, BY TECHNOLOGY, 2023 VS. 2028 
    4.4 SMART WAREHOUSING MARKET, BY WAREHOUSE TYPE, 2023 VS. 2028 
    4.5 SMART WAREHOUSING MARKET, BY APPLICATION, 2023–2028 
    4.6 SMART WAREHOUSING MARKET, BY VERTICAL, 2023–2028 
    4.7 SMART WAREHOUSING MARKET, BY REGION 2023 
 
5 MARKET OVERVIEW AND INDUSTRY TRENDS  
    5.1 MARKET DYNAMICS 
           5.1.1 DRIVERS
           5.1.2 RESTRAINTS
           5.1.3 OPPORTUNITIES
           5.1.4 CHALLENGES
    5.2 MARKET EVOLUTION / BRIEF HISTORY OF THE SMART WAREHOUSING MARKET  
    5.3 INDUSTRY TRENDS 
           5.3.1 VALUE/ SUPPLY CHAIN ANALYSIS
           5.3.2 ECOSYSTEM/ MARKET MAP 
           5.3.3 PRICING ANALYSIS
                    5.3.3.1 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY OFFERING
                    5.3.3.2  INDICATIVE PRICING ANALYSIS, BY OFFERING 
           5.3.4 PORTER FIVE FORCES MODEL/ ANALYSIS
           5.3.5 TRENDS/DISRUPTIONS IMPACTING BUYERS/CLIENTS IN THE SMART WAREHOUSING MARKET 
           5.3.6 TECHNOLOGY ANALYSIS
                    5.3.6.1 KEY TECHNOLOGY  
                    5.3.6.2 ADJACENT TECHNOLOGY  
           5.3.7 CASE STUDY ANALYSIS
           5.3.8 PATENT ANALYSIS
           5.3.9 KEY CONFERENCES & EVENTS, 2023-2024
           5.3.10 TARIFF AND REGULATORY LANDSCAPE 
                    5.3.10.1 TARIFF RELATED TO SMART WAREHOUSING  
                    5.3.10.2 REGULATORY REGULATORY BODIES, GOVERNMENT AGENCIES AND OTHER ORGANIZATIONS 
                               5.3.10.2.1 NORTH AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES AND OTHER ORGANIZATIONS 
                               5.3.10.2.2 EUROPE: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES AND OTHER ORGANIZATIONS
                                             5.3.10.2.3  ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES AND OTHER ORGANIZATIONS
                                             5.3.10.2.4  MIDDLE EAST & AFRICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES AND OTHER ORGANIZATIONS
                               5.3.10.2.5 LATIN AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES AND OTHER ORGANIZATIONS
           5.3.11 TECHNOLOGY ROADMAP FOR SMART WAREHOUSING MARKET UNTIL 2030
                    5.3.11.1 SHORT-TERM ROADMAP (2023-2025)  
                               5.3.11.2   MID-TERM ROADMAP (2026-2028)
                    5.3.11.3 LONG-TERM ROADMAP (2029-2030)  
           5.3.12 BUSINESS MODEL ANALYSIS: SMART WAREHOUSING MARKET
           5.3.13 KEY STAKEHOLDERS AND BUYING CRITERIA
                               5.3.13.1  KEY STAKEHOLDERS IN THE BUYING PROCESS  
                    5.3.13.2 BUYING CRITERIA  
           5.3.14 SMART WAREHOUSING ENTERPRISE BENEFITS 
           5.3.15 HS CODES 
                    5.3.15.1 EXPORT SCENARIO  
                    5.3.15.2  IMPORT SCENARIO  
 
6 SMART WAREHOUSING MARKET, BY OFFERING 
    6.1 INTRODUCTION 
    6.2 OFFERINGS: SMART WAREHOUSING MARKET DRIVERS  
    6.3 HARDWARE  
           6.3.1 RFID (RADIO-FREQUENCY IDENTIFICATION) SYSTEMS
                    6.3.1.1 PASSIVE
                    6.3.1.2 ACTIVE
           6.3.2 SENSOR NETWORKS
                    6.3.2.1 ENVIRONMENTAL SENSORS
                    6.3.2.2 MOTION SENSORS 
                    6.3.2.3 PROXIMITY SENSORS 
           6.3.3 REAL-TIME LOCATION SYSTEMS (RTLS)
                    6.3.3.1 INDOOR RTLS
                    6.3.3.2 OUTDOOR RTLS
                    6.3.3.3 ULTRA-WIDEBAND (UWB) RTLS
           6.3.4 AUTOMATED GUIDED VEHICLES (AGVS)
                    6.3.4.1 AGVS FOR MATERIAL HANDLING
                    6.3.4.2 AGVS FOR PICKING
                    6.3.4.3 AGVS FOR SORTING
           6.3.5 AUTONOMOUS MOBILE ROBOTS (AMRS)
                    6.3.5.1 AMRS FOR INVENTORY SCANNING
                    6.3.5.2 AMRS FOR ORDER FULFILLMENT
                    6.3.5.3 AMRS FOR MATERIAL HANDLING
           6.3.6 CONVEYOR SYSTEMS
                    6.3.6.1 BELT CONVEYORS
                    6.3.6.2 ROLLER CONVEYORS
                    6.3.6.3 SLAT CONVEYORS
           6.3.7 OTHER HARDWARE (ROUTERS, SWITCHES, ACCESS POINTS, AND BARCODE SCANNERS)
    6.4 SOFTWARE  
           6.4.1 WAREHOUSE MANAGEMENT SYSTEM (WMS) SOFTWARE
           6.4.2 INVENTORY MANAGEMENT SOFTWARE
           6.4.3 COLLABORATION AND COMMUNICATIONS TOOLS
           6.4.4 SIMULATION AND MODELING SOFTWARE
           6.4.5 LABOR MANAGEMENT SOFTWARE (LMS)
           6.4.6 WAREHOUSE CONTROL SYSTEM (WCS)
           6.4.7 OTHERS (DATA/ WAREHOUSE ANALYTICS AND REPORTING SOFTWARE, DEMAND FORECAST AND PLANNING SOFTWARE, ROUTE OPTIMIZATION SOFTWARE, AND SECURITY AND COMPLIANCE SOFTWARE)
    6.5 SOFTWARE BY DEPLOYMENT MODE  
           6.5.1 CLOUD 
           6.5.2 ON-PREMISES
    6.6 SERVICES 
           6.6.1 PROFESSIONAL SERVICES 
                    6.6.1.1 TRAINING & CONSULTING SERVICES
                    6.6.1.2 SYSTEM INTEGRATION & IMPLEMENTATION SERVICES
                    6.6.1.3 SUPPORT & MAINTENANCE SERVICES
           6.6.2 MANAGED SERVICES
 
6 SMART WAREHOUSING MARKET, BY TECHNOLOGY 
    6.1 INTRODUCTION 
    6.2 TECHNOLOGY: SMART WAREHOUSING MARKET DRIVERS 
    6.3 IOT  
    6.4 ROBOTICS AND AUTOMATION  
    6.5 AI AND ANALYTICS 
    6.6 NETWORKING AND COMMUNICATION  
    6.7 AR AND VR   
    6.8 OTHER TECHNOLOGIES (BLOCKCHAIN, CLOUD COMPUTING, AND DRONES) 
 
8 SMART WAREHOUSING MARKET, BY APPLICATION 
    8.1 INTRODUCTION 
    8.2 APPLICATION: SMART WAREHOUSING MARKET DRIVERS 
    8.3 INVENTORY MANAGEMENT   
           8.3.1 REAL-TIME INVENTORY TRACKING
                    8.3.1.1 BARCODE SCANNING
                    8.3.1.2 RFID-BASED TRACKING
                    8.3.1.3 GPS-BASED TRACKING
           8.3.2 INVENTORY OPTIMIZATION
                    8.3.2.1 DYNAMIC REORDERING
                    8.3.2.2 SAFETY STOCK MANAGEMENT
                    8.3.2.3 DEMAND SENSING
    8.4 ORDER FULFILLMENT 
           8.4.1 PICKING AND PACKING AUTOMATION
                    8.4.1.1 ROBOTIC PICKERS
                    8.4.1.2 GOODS-TO-PERSON SYSTEMS
                    8.4.1.3 COLLABORATIVE ROBOTS (COBOTS)
           8.4.2 ORDER ROUTING AND OPTIMIZATION
                    8.4.2.1 ROUTE PLANNING ALGORITHMS
                    8.4.2.2 MULTI-CHANNEL ORDER MANAGEMENT
                    8.4.2.3 DYNAMIC SLOTTING
    8.5 ASSET TRACKING 
           8.5.1 EQUIPMENT AND VEHICLE TRACKING
                    8.5.1.1 GPS TRACKING
                    8.5.1.2 TELEMATICS SYSTEMS
                    8.5.1.3 CONDITION MONITORING
           8.5.2 PRODUCT AND PACKAGE TRACKING
                    8.5.2.1 RFID TAGGING
                    8.5.2.2 SMART PACKAGING
                    8.5.2.3 BLOCKCHAIN-BASED TRACKING
    8.6 PREDICTIVE ANALYTICS 
           8.6.1 DEMAND FORECASTING MODELS
                    8.6.1.1 MACHINE LEARNING-BASED FORECASTING
                    8.6.1.2 TIME SERIES ANALYSIS
                    8.6.1.3 BAYESIAN FORECASTING
           8.6.2 PREDICTIVE MAINTENANCE
                    8.6.2.1 SENSOR-BASED PREDICTIVE MAINTENANCE
                    8.6.2.2 AI-DRIVEN PREDICTIVE MAINTENANCE
                    8.6.2.3 FAILURE MODE AND EFFECTS ANALYSIS (FMEA)
    8.6 OTHER APPLICATIONS (FLEET MANAGEMENT, PROCESS MONITORING) 
 
9 SMART WAREHOUSING MARKET, SOFTWARE BY WAREHOUSE SIZE  
    9.1 INTRODUCTION 
    9.2 WAREHOUSE SIZE: SMART WAREHOUSINGMARKET DRIVERS 
    9.3 SMALL 
           9.3.1 MICRO WAREHOUSES
           9.3.2 SMALL-SCALE DISTRIBUTION CENTERS
    9.4 MEDIUM  
           9.4.1 REGIONAL WAREHOUSES
           9.4.2 CROSS-DOCKING FACILITIES
    9.5 LARGE  
           9.5.1 NATIONAL DISTRIBUTION CENTERS
           9.5.2 MEGA WAREHOUSES
 
10 SMART WAREHOUSING MARKET, BY VERTICAL 
     10.1 INTRODUCTION 
     10.2 VERTICAL: SMART WAREHOUSING MARKET DRIVERS  
     10.3 TRANSPORTATION AND LOGISTICS  
             10.3.1 THIRD-PARTY LOGISTICS (3PL) COMPANIES
             10.3.2 FREIGHT FORWARDERS
             10.3.3 LAST-MILE DELIVERY PROVIDERS
     10.4 HEALTHCARE AND LIFE SCIENCES    
             10.4.1 PHARMACEUTICAL WAREHOUSING
             10.4.2 MEDICAL DEVICE WAREHOUSING
             10.4.3 HOSPITAL SUPPLY CHAIN MANAGEMENT
     10.5 MANUFACTURING 
             10.5.1 DISCRETE 
             10.5.2 PROCESS 
     10.6 FOOD AND BEVERAGES  
             10.6.1 COLD CHAIN LOGISTICS
             10.6.2 NON-PERISHABLE GOODS
     10.7 RETAIL AND E-COMMERCE   
             10.7.1 BRICK-AND-MORTAR RETAIL
             10.7.2 E-COMMERCE RETAIL
                       10.7.2.1 ONLINE MARKETPLACES 
                       10.7.2.2 DIRECT-TO-CONSUMER (DTC) BRANDS
     10.8 ENERGY AND UTILITIES  
             10.8.1 OIL AND GAS 
             10.8.2 RENEWABLE ENERGY (SOLAR, WIND, HYDRO)
             10.8.3 UTILITIES (ELECTRICITY, WATER, GAS)
             10.8.4 MINING AND RESOURCES
     10.9 AGRICULTURE 
             10.9.1 GRAIN INVENTORY MANAGEMENT
             10.9.2 AUTOMATED HARVESTING AND SORTING
             10.9.3 QUALITY CONTROL AND GRADING
     10.10 OTHER VERTICALS (EDUCATION, AND TRAVEL AND HOSPITALITY) 
 
11 SMART WAREHOUSING MARKET BY REGION 
     11.1 INTRODUCTION 
     11.2 NORTH AMERICA 
             11.2.1 NORTH AMERICA: SMART WAREHOUSING MARKET DRIVERS
             11.2.2 NORTH AMERICA: IMPACT OF THE RECESSION
             11.2.3 UNITED STATES
             11.2.4 CANADA
     11.3 EUROPE 
             11.3.1 EUROPE: SMART WAREHOUSING MARKET DRIVERS
             11.3.2 EUROPE: IMPACT OF THE RECESSION
             11.3.3 UNITED KINGDOM
             11.3.4 GERMANY
             11.3.5 FRANCE
             11.3.6 SPAIN
             11.3.6 ITALY
             11.3.6 REST OF EUROPE ( THE NETHERLANDS, SWITZERLAND, DENMARK, SWEDEN, AND OTHERS)
     11.4 ASIA PACIFIC 
             11.4.1 ASIA PACIFIC: SMART WAREHOUSING MARKET DRIVERS
             11.4.2 ASIA PACIFIC: IMPACT OF THE RECESSION
             11.4.3 CHINA 
             11.4.4 JAPAN
             11.4.5 INDIA
             11.4.6 SOUTH KOREA
             11.4.6 ANZ
             11.4.6 ASEAN COUNTRIES 
             11.4.8 REST OF ASIA PACIFIC (NEPAL, BHUTAN, BANGLADESH, AND OTHERS)
     11.5 MIDDLE EAST AND AFRICA 
             11.5.1 MIDDLE EAST AND AFRICA: SMART WAREHOUSING MARKET DRIVERS
             11.5.2 MIDDLE EAST AND AFRICA: IMPACT OF THE RECESSION
             11.5.3 UAE
             11.5.4 SAUDI ARABIA
             11.5.5 SOUTH AFRICA
             11.5.6 ISRAEL
             11.5.6 REST OF MIDDLE EAST AND AFRICA (QATAR, EGYPT, KUWAIT, AND OTHERS)
     11.6 LATIN AMERICA 
             11.6.1 LATIN AMERICA: SMART WAREHOUSING MARKET DRIVERS
             11.6.2 LATIN AMERICA: IMPACT OF THE RECESSION
             11.6.3 BRAZIL
             11.6.4 MEXICO
             11.6.5 ARGENTINA
             11.6.6 REST OF LATIN AMERICA (CHILE, COLOMBIA, PERU, AND OTHERS)
 
12 COMPETITIVE LANDSCAPE 
     12.1 INTRODUCTION 
     12.2 MARKET EVALUATION FRAMEWORK 
     12.3 KEY PLAYER STRATEGIES/RIGHT TO WIN 
             12.3.1 OVERVIEW OF STRATEGIES DEPLOYED BY KEY SMART WAREHOUSINGVENDORS
     12.4 BUSINESS SEGMENT REVENUE ANALYSIS  
     12.5 MARKET SHARE ANALYSIS 
     12.6 BRAND/ PRODUCT COMPARATIVE ANALYSIS  
     12.6 COMPANY EVALUATION MATRIX, 2022 
             12.6.1 STARS
             12.6.2 EMERGING LEADERS
             12.6.3 PERVASIVE PLAYERS 
             12.6.4 PARTICIPANTS
             12.6.5 COMPANY FOOTPRINT
     12.8 STARTUP/SME EVALUATION MATRIX, 2022 
             12.8.1 PROGRESSIVE COMPANIES
             12.8.2 RESPONSIVE COMPANIES
             12.8.3 DYNAMIC COMPANIES
             12.8.4 STARTING BLOCKS
             12.8.5 COMPETITIVE BENCHMARKING
     12.9 VALUATION AND FINANCIAL METRICS  
 
13 COMPANY PROFILES 
     13.1 INTRODUCTION 
     13.2 ORACLE 
               13.2.1  BUSINESS OVERVIEW
               13.2.2  PRODUCTS/SOLUTIONS/SERVICES OFFERED
               13.2.3  RECENT DEVELOPMENTS
             13.2.4 MNM VIEW
     13.3 SAP 
               13.3.1  BUSINESS OVERVIEW
               13.3.2  PRODUCTS/ SOLUTIONS/ SERVICES OFFERED
               13.3.3  RECENT DEVELOPMENTS
               13.3.4  MNM VIEW
     13.4 MANHATTAN ASSOCIATES  
               13.4.1  BUSINESS OVERVIEW
               13.4.2  PRODUCTS/ SOLUTIONS/ SERVICES OFFERED
               13.4.3  RECENT DEVELOPMENTS
               13.4.4  MNM VIEW
     13.5 PSI LOGISTICS  
               13.5.1  BUSINESS OVERVIEW
               13.5.2  PRODUCTS/ SOLUTIONS/ SERVICES OFFERED
               13.5.3  RECENT DEVELOPMENTS
               13.5.4  MNM VIEW
     13.6 TECSYS 
               13.6.1  BUSINESS OVERVIEW
               13.6.2  PRODUCTS/ SOLUTIONS/ SERVICES OFFERED
               13.6.3  RECENT DEVELOPMENTS
               13.6.54 MNM VIEW
     13.6 IBM 
               13.6.1  BUSINESS OVERVIEW
               13.6.2  PRODUCTS/ SOLUTIONS/ SERVICES OFFERED
               13.6.3  RECENT DEVELOPMENTS
     13.6 REPLY   
     13.9 INFOR   
     13.10 KORBER  
     13.11 BLUE YONDER  
     13.12 GENERIX GROUP  
     13.13 MICROLISTICS  
     13.14 MICROSOFT  
     13.15 EPICOR  
     13.16 MADE4NET  
     13.16 MANTIS 
     13.18 SOFTEON   
     13.19 SYNERGY  
     13.20 E2OPEN  
     13.21 VINCULUM  
     13.22 SSI SCHAEFER 
     13.23 FISHBOWL INVENTORY  
     13.24 ABB  
     13.25 STARTUP/SME COMPANY PROFILES 
               13.25.1 WAREIQ
               13.25.2 FOYSONIS
               13.25.3 LOGIWA
               13.25.4 LOCUS ROBOTICS
               13.25.5 SHIPHERO
               13.25.6 CIN7
               13.25.6 EASYECOM
               13.25.8 UNICOMMERCE
               13.25.9 I AM ROBOTICS
               13.25.10 INCREFF
 
14 ADJACENT MARKET  
     14.1 INTRODUCTION 
     14.2 MARKET DEFINITION 
     14.3 SUPPLY CHAIN ANALYTICS MARKET  
     14.4 LOGISTICS AUTOMATION MARKET 
 
15 APPENDIX 
     15.1 DISCUSSION GUIDE 
     15.2 KNOWLEDGE STORE: MARKETSANDMARKETS’  SUBSCRIPTION PORTAL 
     15.3 AVAILABLE CUSTOMIZATIONS 
     15.4 RELATED REPORTS 
     15.5 AUTHOR DETAILS 

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.

Secondary Research

In the secondary research process, various sources were referred to, for identifying and collecting information for this study. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers, journals, and certified publications; and articles from recognized authors, directories, and databases. The data was also collected from other secondary sources, such as journals, government websites, blogs, and vendors websites. Additionally, smart warehousing spending of various countries was extracted from the respective sources. Secondary research was mainly used to obtain key information related to the industry’s value chain and supply chain to identify key players based on hardware, software, services, market classification, and segmentation according to offerings of major players, industry trends related to hardware, software, services, deployment modes, technology, application, warehouse size, verticals, and regions, and key developments from both market- and technology-oriented perspectives.

Primary Research

In the primary research process, various primary sources from both supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, including Chief Experience Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and smart warehousing expertise; related key executives from smart warehousing solution vendors, SIs, professional service providers, and industry associations; and key opinion leaders.

Primary interviews were conducted to gather insights, such as market statistics, revenue data collected from solutions and services, market breakups, market size estimations, market forecasts, and data triangulation. Primary research also helped understand various trends related to technologies, applications, deployments, and regions. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Strategy Officers (CSOs), and end users using smart warehousing solutions, were interviewed to understand the buyer’s perspective on suppliers, products, service providers, and their current usage of smart warehousing solutions and services, which would impact the overall smart warehousing market.

The breakup of Primary Research:

Smart Warehousing Market Size, and Share

To know about the assumptions considered for the study, download the pdf brochure

COMPANY NAME

DESIGNATION

PSI Logistics

Head of Marketing

Increff

Co-Founder 

ShipHero

VP of Product - SaaS

Market Size Estimation

In the bottom-up approach, the adoption rate of smart warehousing solutions and services among different end users in key countries with respect to their regions contributing the most to the market share was identified. For cross-validation, the adoption of smart warehousing solutions and services among industries, along with different use cases with respect to their regions, was identified and extrapolated. Weightage was given to use cases identified in different regions for the market size calculation.

Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the smart warehousing market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socio-economic analysis of each country, strategic vendor analysis of major smart warehousing providers, and organic and inorganic business development activities of regional and global players were estimated. With the data triangulation procedure and data validation through primaries, the exact values of the overall smart warehousing market size and segments’ size were determined and confirmed using the study.

Global Smart Warehousing Market Size: Bottom-Up and Top-Down Approach:

Smart Warehousing Market Size, and Share

To know about the assumptions considered for the study, Request for Free Sample Report

Data Triangulation

Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the smart warehousing market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socio-economic analysis of each country, strategic vendor analysis of major smart warehousing providers, and organic and inorganic business development activities of regional and global players were estimated. With the data triangulation procedure and data validation through primaries, the exact values of the overall smart warehousing market size and segments’ size were determined and confirmed using the study.

Market Definition

Smart Warehouses, akin to smart factories, leverage data and automation to optimize their operations. These facilities automate a multitude of tasks, from order recognition and product receipt to storage, sorting, and dispatch. The integration of various automation technologies and interconnected equipment creates a technologically advanced environment where materials and shipments can be efficiently received, organized, identified, and prepared for delivery or dispatch with minimal human intervention.

Stakeholders

  • Smart warehousing vendors
  • Smart warehousing service vendors
  • Managed service providers
  • Support and maintenance service providers
  • System Integrators (SIs)/migration service providers
  • Value-Added Resellers (VARs) and distributors
  • Distributors and Value-added Resellers (VARs)
  • System Integrators (SIs)
  • Independent Software Vendors (ISV)
  • Third-party providers
  • Technology providers

Report Objectives

  • To define, describe, and predict the smart warehousing market by offering (hardware, software and services), technology, application, warehouse size, verticals, and region
  • To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
  • To analyze the micro markets with respect to individual growth trends, prospects, and their contribution to the total market
  • To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the smart warehousing market
  • To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
  • To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
  • To profile key players and comprehensively analyze their market rankings and core competencies.
  • To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the smart warehousing market
  • To analyze the impact of recession across all the regions across the smart warehousing market

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per your company’s specific needs. The following customization options are available for the report:

Product Analysis

  • Product quadrant, which gives a detailed comparison of the product portfolio of each company.

Geographic Analysis

  • Further breakup of the North American smart warehousing market
  • Further breakup of the European smart warehousing market
  • Further breakup of the Asia Pacific smart warehousing market
  • Further breakup of the Middle Eastern & African smart warehousing market
  • Further breakup of the Latin America smart warehousing market

Company Information

  • Detailed analysis and profiling of additional market players (up to five)
Custom Market Research Services

We will customize the research for you, in case the report listed above does not meet with your exact requirements. Our custom research will comprehensively cover the business information you require to help you arrive at strategic and profitable business decisions.

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Report Code
TC 7993
Published ON
Sep, 2023
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