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

RELEASE DATE
30-Aug-2017
REGION
Global
Research Code: 9AB2-00-7C-00-00
SKU: AU01530-GL-MR_20631
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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

Our Blue Ocean Strategy

Related Research
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 s
More Information
No Index No
Podcast No
Author Anubhav Grover
Industries Automotive
WIP Number 9AB2-00-7C-00-00
Is Prebook No