Connected Services and Big Data Analytics in the Global Farming Industry, Forecast to 2022
Connected Services and Big Data Analytics in the Global Farming Industry, Forecast to 2022
Integration of Big Data Analytics with Connected Farm Equipment Signifies the Next Frontier of Competition
30-Aug-2017
Global
Market Research
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Description
This study aims to research and analyse the development of Big Data Analytics and connected services in the farm equipment industry and to assess the value proposition of these connected services that address the expectations of farmers and transform their business practices. The farm equipment industry is witnessing another wave of industrial change through IT industry. The formation of smart connected products is creating new opportunities and new areas of business models. The farm equipment industry has evolved with new territory of connected services. New functionality, high reliability, and better product utilization are the evaluating parameters for these OEMs. The IoT wave has reshaped competitive factors and expanded industry boundary, from standard products to a system of smart connected products.
These products help integrate operations, and collect and transit real-time data from farm equipment to a farmer’s dashboard. OEMs are now competing not just at the product-feature level but on the level of offering wholly connected, integrated solutions by connecting their products across various systems and various functions.
Research Scope
Market trends are analysed for the study period 2016 to 2022, with 2016 being the base year. Technologies covered in the study are Precision Agriculture, Big Data, IoT, and autonomous systems. Farm equipment, including tractors, harvesters, and sprayers are covered under the product scope of the study. The incorporation of Big Data analytics in farming and precision agriculture, a growing trend, is the key focus area in this study. The precision agriculture ecosystem consists of tractor OEMs, seeds and fertilizer manufacturers, technology companies, and hardware and software companies.
Companies covered in the competitive landscape of this study include John Deere, KUBOTA, Accenture, IBM, Intel, Videophone, Tech Mahindra, Mahindra & Mahindra, Trimble, Cisco, AT&T, CNH Industrial, and others.
The geographic scope of the study is global, which includes: Europe (all 28 European countries), Russia, United States, Brazil, Mexico, Africa (Kenya, Nigeria, Algeria, South Africa, Tanzania, and Uganda), Asia-Pacific (India, China, Japan, Thailand, Indonesia, Vietnam, Cambodia, and Australia).
Key Questions This Study Will Answer
• What are the adoption trends in Big Data solutions and services in the farming sector?
• What are the upcoming technologies involved in the agriculture industries?
• What are the major digital initiatives taken up by the OEMs in the technology front?
• What are the drivers and restraints for digital telematics market in the farming sector?
• What lies ahead for farm equipment manufacturers, Tier I suppliers, and IoT service providers in the Digital Farming landscape?
Table of Contents
Executive Summary—Key Findings
Executive Summary—Global Scenario
Executive Summary—Market Outlook
Recommendations to OEMs
Digitization of Farm Management Supply Chains
Research Scope
Research Aim and Objectives
Key Questions this Study will Answer
Research Methodology
Definitions
Big Data Analytics
Precision Agriculture—Input for Agriculture Big Data
Value Chain of Big Data Analytics
Impact of Big Data Analytics on Farm Equipment Industry
Big Data—Opportunity Analysis
Industry Initiatives—Big Data and Predictive Analytics
Agriculture Industry Value Chain
Connected Services and Big Data Application Trends
Big Data Landscape in Smart Agriculture
Smart Farming Through Predictive Analytics
Enabling Technologies for Big Data in Smart Agriculture
Data Collection and Transmission—Innovator Profile
Data Storage and Analysis—Innovator Profile
Automation Solutions—Innovator Profile
Technologies—Future Outlook
Focus Areas for the Development of Precision Agriculture
Emerging Smart Agriculture Ecosystem
Connected Agriculture Ecosystem
Connected System in Smart Farming
Opportunities for IoT and Specialised Domain Big Data
IoT Solutions in the Farm Management Segment
Participants in Connected Agriculture Ecosystem
Case Study—Monsanto’s Digital Farms
Case Study—Mahindra and Mahindra’s New Business Model
Big Data Information Sharing to New Business Models
Impact of New Business Models
Farmers Business Network (FBN)—Software and Analytics
FarmLogs—Farm Management Software
Orbital Insight—Geospatial Big Data Analytics
Evolution of Tractors to Connected Tractors
Connected Farm Equipment System
Connected Tractors to Pave Way for Autonomous Systems
Connected Tractors Application Segment
Connected Combines Trends
Rising Proliferation of Telematics in Connecting Machines
Farm Equipment Telematics—Developments and Outlook
Key Telematics Features by Equipment Type
Rise of Farm Equipment Telematics
Drivers—Impact and Duration
Drivers Explained
Restraints—Impact and Duration
Drivers Explained
Industry Initiatives—Telematics Solutions
Telematics—Case IH
Telematics—John Deere
Telematics—John Deere (continued)
Telematics—New Holland
Telematics—AGCO
Telematics—CLAAS
Future Roadmap
Connected Services and Big Data Analytics—Global Opportunity
Strategic Imperatives for Success and Growth
Key Conclusions
Legal Disclaimer
List of Acronyms
The Frost & Sullivan Story
Value Proposition—Future of Your Company & Career
Global Perspective
Industry Convergence
360º Research Perspective
Implementation Excellence
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Deliverable Type | Market Research |
---|---|
No Index | No |
Podcast | No |
Author | Anubhav Grover |
Industries | Automotive |
WIP Number | 9AB2-00-7C-00-00 |
Is Prebook | No |