3 questions for leaders using tech to make the world a better place

A new framework will enable companies to use tech to create better … use new technologies to deliver broader societal impact, including reaching our …

The guiding framework, when adopted, embeds a responsible technology approach across an enterprise – from strategy, operating model and supply chain, to governance and people – in order to scale action and bring it into the mainstream. To make the framework more tangible we have developed a set of guiding questions. These are the types of questions C-suite, and business function leaders, should be asking themselves, and addressing, as they seek to embed and integrate new technologies across their businesses and value chains to drive holistic commercial, environmental and social impact.

Artificial Intelligence In Construction Market Drives Future Change | IBM, Microsoft, Oracle, SAP

Oracle; SAP; Alice Technologies; Aurora Computer Services; Autodesk; Coins Global; Beyond Limits; Plangrid; Renoworks Software; Bentley Systems.

Sep 17, 2020 6:21 AM ET

iCrowd Newswire – Sep 17, 2020

Global Artificial Intelligence In Construction Market Size Study, By Application (Project Management, Field Management, Risk Management, Schedule Management, Supply-Chain Management, Others), By Industry (Residential, Institutional Commercial, Heavy Construction, Others), By Component (Solutions, Services), By Stage Of Construction (Pre-Construction, Construction Stage, Post-Construction), By Technology (Machine Learning & Deep Learning, Natural Language Processing), By Deployment (Cloud, On-Premises) And Regional Forecasts Covid 19 Outbreak Impact research report added by Report Ocean, is an in-depth analysis of combination of factors, including COVID-19 containment situation, end-use market recovery & Recovery Timeline of 2020/ 2021, the latest developments, market size, status, upcoming technologies, industry drivers, challenges, regulatory policies, with key company profiles and strategies of players. The research study provides market overview, Artificial Intelligence In Construction market definition, regional market opportunity, sales and revenue by region, manufacturing cost analysis, Industrial Chain, market effect factors analysis, Artificial Intelligence In Construction market size forecast, market data & Graphs and Statistics, Tables, Bar &Pie Charts, and many more for business intelligence. Getreportto understand the structure of the complete fine points (Including Full TOC, List of Tables & Figures, Chart). – In-depth Analysis Pre & Post COVID-19 Market Estimates

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Global Artificial Intelligence in Construction Market to reach USD XX billion by 2025.

Global Artificial Intelligence in Construction Market valued approximately USD XX billion in 2017 is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2018-2025. The major driving factor of global artificial intelligence in construction market are growing demand across end user industries, technological advancements have encouraged the organizations especially construction and engineering sector and the increasing digital data. In addition, a rapid surge in the growth of the digital data has been witnessed owing to the growing adoption of Building Information Systems (BIM), security sensors, drones, and machine telematics. This is encouraging construction companies to adopt advanced analytics solutions to take the full advantage of the huge amount of digital data and extract actionable insights.

The major restraining factor of global artificial intelligence in construction market are unstructured construction environment and lack of skilled workforce. Moreover, adoption of the drones, robots, and autonomous vehicles in the construction sector is also backing the growth of the artificial intelligence in construction market. Artificial Intelligence in Construction Management is the core of artificial intelligence. With data collected at various cycles of the construction project across many different projects in construction firms, this provides valuable learning information for artificial intelligence applications. Artificial intelligence serves as a helpful tool for every phase of the construction project. The major key benefits of artificial intelligence are By using Construction Language Analysis, from tools such as Autodesk BIM 360 software, algorithms are able to understand complex data and predict potential problems, by using AI technology in the construction industry and scanning software, they can track the body movement of bricklayers to analyses their form in order to reduce the amount of injuries on-site and artificial intelligence in construction can be used to measure a project’s parameters which is then fed into a computer which understands the data and requirements of their physical location.

The regional analysis of Global Artificial Intelligence in Construction Market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America and Rest of the World. North-America has accounted the dominant share in the global Artificial Intelligence in Construction market due to high investments by construction companies. Additionally, Asia Pacific is also expected to register a considerable growth rate in the market over the forecasted period 2018-2025. China, Japan, South Korea, and India are the leading countries in this region. The market growth is due to increase in demand by the economies to develop smart city projects which require better amenities that boost the real estate sector.

The leading market player are:

  • IBM
  • Microsoft
  • Oracle
  • SAP
  • Alice Technologies
  • Aurora Computer Services
  • Autodesk
  • Coins Global
  • Beyond Limits
  • Plangrid
  • Renoworks Software
  • Bentley Systems

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Application:

Project Management

Field Management

Risk Management

Schedule Management

Supply-Chain Management

Others

By Industry:

Residential

Institutional Commercial

Heavy construction

Others

By Component:

Solutions

Services

By Stage of Construction:

Pre-Construction

Construction Stage

Post-Construction

By Technology:

Machine Learning & Deep Learning

Natural Language Processing

By Deployment:

Cloud

On-Premises

Target Audience of the Global Artificial Intelligence in Construction Market in Market Study:

Key Consulting Companies & Advisors

Large, medium-sized, and small enterprises

Venture capitalists

Value-Added Resellers (VARs)

Third-party knowledge providers

Investment bankers

Investors

Geographical Breakdown: Regional level analysis of the market, currently covering North America, Europe, China & Japan

North America (United States, Canada & Mexico)

Asia-Pacific (Japan, China, India, Australia etc)

Europe (Germany, UK, France etc)

Central & South America (Brazil, Argentina etc)

Middle East & Africa (UAE, Saudi Arabia, South Africa etc)

In-Depth Qualitative COVID 19 Outbreak Impact Analysis Include Identification And Investigation Of The Following Aspects: Market Structure, Growth Drivers, Restraints and Challenges, Emerging Product Trends & Market Opportunities, Porter’s Fiver Forces. The report also inspects the financial standing of the leading companies, which includes gross profit, revenue generation, sales volume, sales revenue, manufacturing cost, individual growth rate, and other financial ratios. The report basically gives information about the Market trends, growth factors, limitations, opportunities, challenges, future forecasts, and details about all the key market players.

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Changing Forecasts in a Time of Crisis: explores key issues, including:

  • Future changes in consumer behavior
  • High-frequency economic data
  • Mapping Out a Potential Recovery
  • Business Strategies During COVID-19
  • Near & Long Term Risk Outlook, Risk Assessment and Opportunities

Key questions answered: The Study Explore COVID 19 Outbreak Impact Analysis

  • Market size and growth rate during forecast period.
  • Key factors driving the Market.
  • Key market trends cracking up the growth of the Market.
  • Challenges to market growth.
  • Key vendors of Market.
  • Detailed SWOT analysis.
  • Opportunities and threats faces by the existing vendors in Global Market.
  • Trending factors influencing the market in the geographical regions.
  • Strategic initiatives focusing the leading vendors.
  • PEST analysis of the market in the five major regions.
  • What should be entry strategies, countermeasures to economic impact, and marketing channels?
  • What are market dynamics?
  • What are challenges and opportunities?
  • What is economic impact on market?
  • What is market chain analysis by upstream raw materials and downstream industry?
  • What is industry considering capacity, production and production value? What will be the estimation of cost and profit? What will be market share, supply and consumption? What about import and export?
  • What is current market status? What’s market competition in this industry, both company, and country wise? What’s market analysis by taking applications and types in consideration?
  • What were capacity, production value, cost and profit?
  • Who are the global key players in this industry? What are their company profile, their product information, and contact information?
  • Which manufacturing technology is used, what are their company profile, their product information, and contact information?

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Key Points Covered in Artificial Intelligence In ConstructionMarket Report:

Chapter 1. Executive Summary

1.1. Market Snapshot

1.2. Key Trends

1.3. Global & Segmental Market Estimates & Forecasts, 2015-2025 (USD Billion)

1.3.1. Artificial Intelligence in Construction, by Application, 2015-2025 (USD Billion)

1.3.2. Artificial Intelligence in Construction, by Industry, 2015-2025 (USD Billion)

1.3.3. Artificial Intelligence in Construction, by Component, 2015-2025 (USD Billion)

1.3.4. Artificial Intelligence in Construction, by Stage of construction, 2015-2025 (USD Billion)

1.3.5. Artificial Intelligence in Construction, by Technology, 2015-2025 (USD Billion)

1.3.6. Artificial Intelligence in Construction, by Deployment, 2015-2025 (USD Billion)

1.3.7. Artificial Intelligence in Construction, by Region, 2015-2025 (USD Billion)

1.4. Estimation Methodology

1.5. Research Assumption

Chapter 2. Definition and Scope

2.1. Objective of the Study

2.2. Market Definition & Scope

2.2.1. Industry Evolution

2.2.2. Scope of the Study

2.3. Years Considered for the Study

2.4. Currency Conversion Rates

Chapter 3. Artificial Intelligence in Construction Dynamics

3.1. See Saw Analysis

3.1.1. Market Drivers

3.1.2. Market Challenges

3.1.3. Market Opportunities

Chapter 4. Artificial Intelligence in Construction Industry Analysis

4.1. Porter’s 5 Force Model

4.1.1. Bargaining Power of Buyers

4.1.2. Bargaining Power of Suppliers

4.1.3. Threat of New Entrants

4.1.4. Threat of Substitutes

4.1.5. Competitive Rivalry

4.1.6. Futuristic Approach to Porter’s 5 Force Model

4.2. PEST Analysis

4.2.1. Political Scenario

4.2.2. Economic Scenario

4.2.3. Social Scenario

4.2.4. Technological Scenario

4.3. Value Chain Analysis

4.3.1. Supplier

4.3.2. Manufacturers/Service Provider

4.3.3. Distributors

4.3.4. End-Users

4.4. Key Buying Criteria

4.5. Regulatory Framework

4.6. Cost Structure Analysis

4.6.1. Raw Material Cost Analysis

4.6.2. Manufacturing Cost Analysis

4.6.3. Labour Cost Analysis

4.7. Investment Vs Adoption Scenario

4.8. Analyst Recommendation & Conclusion

Chapter 5. Artificial Intelligence in Construction, by Application

5.1. Market Snapshot

5.2. Market Performance – Potential Model

5.3. Key Market Players

5.4. Artificial Intelligence in Construction, Sub Segment Analysis

5.4.1. Project Management

5.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.4.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

5.4.2. Field Management

5.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.4.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

5.4.3. Risk Management

5.4.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.4.3.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

5.4.4. Schedule Management

5.4.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.4.4.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

5.4.5. Supply-Chain Management

5.4.5.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.4.5.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

5.4.6. Others

5.4.6.1. Market estimates & forecasts, 2015-2025 (USD Billion)

5.4.6.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 6. Artificial Intelligence in Construction, by Industry

6.1. Market Snapshot

6.2. Market Performance – Potential Model

6.3. Key Market Players

6.4. Artificial Intelligence in Construction, Sub Segment Analysis

6.4.1. Residential

6.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

6.4.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

6.4.2. Institutional Commercial

6.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

6.4.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

6.4.3. Heavy Construction

6.4.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

6.4.3.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

6.4.4. Others

6.4.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)

6.4.4.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 7. Artificial Intelligence in Construction, by Component

7.1. Market Snapshot

7.2. Market Performance – Potential Model

7.3. Key Market Players

7.4. Artificial Intelligence in Construction, Sub Segment Analysis

7.4.1. Solutions

7.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

7.4.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

7.4.2. Services

7.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

7.4.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 8. Artificial Intelligence in Construction, by Stage of Construction

8.1. Market Snapshot

8.2. Market Performance – Potential Model

8.3. Key Market Players

8.4. Artificial Intelligence in Construction, Sub Segment Analysis

8.4.1. Pre-Construction

8.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

8.4.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

8.4.2. Construction Stage

8.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

8.4.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

8.4.3. Post-Construction

8.4.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

8.4.3.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 9. Artificial Intelligence in Construction, by Technology

9.1. Market Snapshot

9.2. Market Performance – Potential Model

9.3. Key Market Players

9.4. Artificial Intelligence in Construction, Sub Segment Analysis

9.4.1. Machine Learning & Deep Learning

9.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.4.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

9.4.2. Natural Language Processing

9.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

9.4.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 10. Artificial Intelligence in Construction, by Deployment

10.1. Market Snapshot

10.2. Market Performance – Potential Model

10.3. Key Market Players

10.4. Artificial Intelligence in Construction, Sub Segment Analysis

10.4.1. Cloud

10.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

10.4.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

10.4.2. On-Premises

10.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

10.4.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 11. Artificial Intelligence in Construction, by Regional Analysis

11.1. Artificial Intelligence in Construction, Regional Market Snapshot (2015-2025)

11.2. North America Artificial Intelligence in Construction Snapshot

11.2.1. U.S.

11.2.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.2.1.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.2.1.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.2.1.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.2.2. Canada

11.2.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.2.2.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.2.2.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.2.2.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3. Europe Artificial Intelligence in Construction Snapshot

11.3.1. U.K.

11.3.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.3.1.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.1.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.1.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.2. Germany

11.3.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.3.2.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.2.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.2.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.3. France

11.3.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.3.3.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.3.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.3.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.4. Rest of Europe

11.3.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.3.4.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.4.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.3.4.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4. Asia Artificial Intelligence in Construction Snapshot

11.4.1. China

11.4.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.4.1.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.1.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.1.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.2. India

11.4.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.4.2.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.2.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.2.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.3. Japan

11.4.3.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.4.3.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.3.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.3.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.4. Rest of Asia Pacific

11.4.4.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.4.4.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.4.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.4.4.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.5. Latin America Artificial Intelligence in Construction Snapshot

11.5.1. Brazil

11.5.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.5.1.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.5.1.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.5.1.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.5.2. Mexico

11.5.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.5.2.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.5.2.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.5.2.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.6. Rest of The World

11.6.1. South America

11.6.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.6.1.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.6.1.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.6.1.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.6.2. Middle East and Africa

11.6.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)

11.6.2.2. Components breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.6.2.3. Applications breakdown estimates & forecasts, 2015-2025 (USD Billion)

11.6.2.4. End user breakdown estimates & forecasts, 2015-2025 (USD Billion)

Chapter 12. Competitive Intelligence

12.1. Company Market Share (Subject to Data Availability)

12.2. Top Market Strategies

12.3. Company Profiles

12.3.1. IBM

12.3.1.1. Overview

12.3.1.2. Financial (Subject to Data Availability)

12.3.1.3. Product Summary

12.3.1.4. Recent Developments

12.3.2. Microsoft

12.3.3. Oracle

12.3.4. SAP

12.3.5. Alice Technologies

12.3.6. Aurora Computer Services

12.3.7. Autodesk

12.3.8. Coins Global

12.3.9. Beyond Limits

12.3.10. Plangrid

12.3.11. Renoworks Software

12.3.12. Bentley Systems

Chapter 13. Research Process

13.1. Research Process

13.1.1. Data Mining

13.1.2. Analysis

13.1.3. Market Estimation

13.1.4. Validation

13.1.5. Publishing

13.1.6. Research Assumption

Continued….

……..and view more in complete table of Contents

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iCrowdNewswire

Keywords: Artificial Intelligence In Construction Market, Artificial Intelligence In Construction Market Analysis, Artificial Intelligence In Construction Market Growth, Artificial Intelligence In Construction Market Scope, Artificial Intelligence In Construction Market Share, Artificial Intelligence In Construction Market Trend, Artificial Intelligence In Construction Market Development, Artificial Intelligence In Construction Market Sales, Artificial Intelligence In Construction Market Forecast, Artificial Intelligence In Construction Market Opportunities, Artificial Intelligence In Construction Market Size

Blockchain in Retail Market Next Big Thing | Major Giants Microsoft, SAP, AWS

… Oracle, Bitfury, Cegeka, Auxesis Group, Blockpoint, Coinbase, Loyyal, Abra, Bitpay, Blockverify, BTL Group, Modultrade, Recordskeeper, Guardtime, …

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1. External Factor Analysis

An external analysis looks at the wider business environment that affects the business. This industry assessment covers all the factors that are outside the control. It includes both the micro and macro environmental factors.

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MICRO ENVIRONMENT: Factors highlighting the rivalry of the competition.

2. Growth & Margins

Players that are having stellar growth track record is a must see view in the study that Analyst have covered. From 2014 to 2019, some of the company have shown enormous sales figures, with net income going doubled in that period with operating as well as gross margins constantly expanding. The rise of gross margins over past few years directs strong pricing power of the competitive companies in the industry for its products or offering, over and above the increase in the cost of goods sold.

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3. Ambitious growth plans & rising competition?

Industry players are planning to introduce new products launch into various markets around the globe considering applications / end use such as Small and Medium-Sized Enterprises & Large Enterprises. Examining some latest innovative products that are vital and may be introduced in EMEA markets in last quarter 2019 and 2020. Considering all round development activities of IBM, Microsoft, SAP, AWS, Oracle, Bitfury, Cegeka, Auxesis Group, Blockpoint, Coinbase, Loyyal, Abra, Bitpay, Blockverify, BTL Group, Modultrade, Recordskeeper, Guardtime, Blockchain Foundry, Bigchaindb, Sofocle Technologies, OGY Docs, Reply, Project Provenance & Warranteer Digital, some players profiles are worth attention seeking.

4. Where the Blockchain in Retail Industry is today

Though latest year might not be that encouraging as market segments especially , Compliance Management, Identity Management, Loyalty and Rewards Management, Payments, Smart Contracts, Supply Chain Management & Others have shown modest gains, growth scenario could have been changed if IBM, Microsoft, SAP, AWS, Oracle, Bitfury, Cegeka, Auxesis Group, Blockpoint, Coinbase, Loyyal, Abra, Bitpay, Blockverify, BTL Group, Modultrade, Recordskeeper, Guardtime, Blockchain Foundry, Bigchaindb, Sofocle Technologies, OGY Docs, Reply, Project Provenance & Warranteer Digital would have plan ambitious move earlier. Unlike past, but decent valuation and emerging investment cycle to progress in the United States, Europe, China, Japan, Southeast Asia, India & Central & South America., many growth opportunities ahead for the companies in 2020, it looks descent today but stronger returns would be expected beyond.

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• Market Share & Sales Revenue by Key Players & Local Emerging Regional Players. [Some of the players covered in the study are IBM, Microsoft, SAP, AWS, Oracle, Bitfury, Cegeka, Auxesis Group, Blockpoint, Coinbase, Loyyal, Abra, Bitpay, Blockverify, BTL Group, Modultrade, Recordskeeper, Guardtime, Blockchain Foundry, Bigchaindb, Sofocle Technologies, OGY Docs, Reply, Project Provenance & Warranteer Digital]

• A separate section on Entropy to gain useful insights on leaders aggressiveness towards market [Merger & Acquisition / Recent Investment and Key Development Activity Including seed funding]

• Competitive Analysis: Company profile of listed players with separate SWOT Analysis, Overview, Product/Services Specification, Headquarter, Downstream Buyers and Upstream Suppliers.

• Gap Analysis by Region. Country break-up will help you dig out Trends and opportunity lying in specific territory of your business interest.

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Adapting Omnichannel Fulfillment for a Post-COVID-19 World

Blockchain, however, offers a viable way to bridge the gap, connecting transactional data from across the supply chain on a distributed ledger.

Around the world, countries are taking gradual steps toward a return to normalcy amidst efforts to flatten the curve of COVID-19. One of those key steps is the easing of restrictions on retailers. This follows months of store closures, which made e-commerce the primary sales channel for many businesses practically overnight.

Looking ahead, we can expect these precautionary measures to have a lasting impact on consumer purchasing behavior long after case numbers reach favorable lows. Namely, consumers will likely remain cautious even as stores reopen, choosing to continue shopping online. More will also gravitate towards retailers that offer curbside pickup as a safe fulfillment option.

To adapt accordingly, companies will need to tighten their omnichannel capabilities and develop an integrated ecosystem between their online and offline experiences. Lessons learned during the pandemic along with supporting technologies will prove vital to successful execution.

Below are three strategies to consider:

1. Create a free-flowing inventory ecosystem.

Big-box stores have done well during the pandemic thanks to previous investments in inventory visibility, enabling online shoppers to see available stock and pick up orders from nearby stores. It was naturally easier for these companies to shift to curbside pickup.

Other retailers — such as those in the mid-market — haven’t fared as well due to fewer resources and a lack of connectivity and segregation of inventory between their online order management and in-store inventory management systems. Blockchain, however, offers a viable way to bridge the gap, connecting transactional data from across the supply chain on a distributed ledger. This level of connectivity enables accurate insight into in-store inventory (for companies and consumers alike) and the seamless execution of online orders, from desktop or mobile to curbside.

Blockchain doesn’t have to be an expensive investment, either. There are blockchain-as-a-service (BaaS) solutions that use low-cost, subscription-based models that can fit any budget. BaaS also makes deployments quick and scalable, as users only need an internet browser to share and access permissioned data.

2. Leverage sales data to optimize fulfillment operations.

Initial store closures drove spikes in online traffic that few retailers were prepared for. Coupled with the fact that many were and still are operating with reduced workforces to enable safe distancing between team members, it’s led to fulfillment delays and other inefficiencies in customer service.

To avoid additional operational challenges, retailers need better foresight so they can anticipate demand fluctuations and adjust their operations as needed. This is another area where blockchain can help by making downstream sales data available to support decisions at all levels of the business.

The data flows in real time, allowing decision makers to proactively understand the following:

  • How much will demand rise?
  • What’s driving demand?
  • Where is that demand coming from?

They can thereby prepare distribution centers, fulfillment partners, stores, etc., well in advance.

3. Generate regular fulfillment forecasts with AI.

In connection with the previous strategy, organizations don’t have to calculate demand forecasts on their own anymore. There are artificial intelligence (AI) models that can produce accurate projections, taking into account multidimensional factors. All they require is a solid data foundation from which to develop algorithms. Notably, holistic supply chain data logged on blockchain can provide that ideal foundation.

Instead of digging into data then, retailers can use AI-generated insights to stay ahead of the curve, appropriately staffing their warehouses, planning shipping routes, and working to ensure timely fulfillment across all channels.

Ultimately, these strategies boil down to transparency, connectivity and agility. When companies make upstream decisions based on real-time downstream data, it’s a benefit to not only omnichannel fulfillment and meeting consumers expectations today, but also building adaptability and resilience for the future.

Pratik Soni is the founder and CEO of Omnichain™, a supply chain technology startup that uses blockchain to help brands and retailers drive business growth at scale.

Digital Coin Market to Witness Unprecedented Growth in Coming Years 2024 | Bitcoin, Ethereum …

Key Companies Covered : Bitcoin, Ethereum, Ripple, Litecoin, Dogecoin, Dash. You get the detailed analysis of the current market scenario for Digital …

The Digital Coin Market research Report is a valuable supply of perceptive information for business strategists. This Premium Tyres Market study provides comprehensive data which enhances the understanding, scope and application of this report.

The key market segments along with its subtypes are provided in the report. This report especially focuses on the dynamic view of the market, which can help to manage the outline of the industries. Several analysis tools and standard procedures help to demonstrate the role of different domains in market. The study estimates the factors that are boosting the development of Digital Coin companies.

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Key Companies Covered : Bitcoin, Ethereum, Ripple, Litecoin, Dogecoin, Dash

You get the detailed analysis of the current market scenario for Digital Coin and a market forecast till 2024 with this report. The forecast is also supported with the elements affecting the market dynamics for the forecast period. This report also details the information related to geographic trends, competitive scenarios and opportunities in the Digital Coin market. The report is also equipped with SWOT analysis and value chain for the companies which are profiled in this report.

Most Important Types : P2P Coins, Type II

Most Important Application : Online transaction, Application 2

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Global Digital Coin Market Size, Status and Forecast 2019 – 2024

1 Market Overview

2 Manufacturers Profiles

3 Global Digital Coin Sales, Revenue, Market Share and Competition by Manufacturer

4 Global Digital Coin Market Analysis by Regions

5 North America Digital Coin by Countries

6 Europe Digital Coin by Countries

7 Asia-Pacific Digital Coin by Countries

8 South America Digital Coin by Countries

9 Middle East and Africa Digital Coin by Countries

10 Global Digital Coin Market Segment by Type

11 Global Digital Coin Market Segment by Application

12 Digital Coin Market Forecast

13 Sales Channel, Distributors, Traders and Dealers

14 Research Findings and Conclusion

15 Appendixes

Reasons for Buying this Report:

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  5. Provides pin-point analysis of inconstant competition dynamics and keeps you ahead of competitors.

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