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Asia Pacific Operational Intelligence Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

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  • 122 Pages
  • August 2022
  • Region: Asia Pacific
  • Mordor Intelligence
  • ID: 5552634
The Asia Pacific Operational Intelligence Market is expected to register a CAGR of 12.5% over the forecast period 2022-2027.

Key Highlights

  • Asia Pacific market for Operational Intelligence is estimated to grow at a rapid pace because of the effectiveness of the technology. Operational Intelligence helps to increase operational efficiency. It helps organizations with intelligence about the key drivers in their supply chain and to get the maximum out of it. It applies the benefits of real-time analytics, alerts, and actions to a broad spectrum of use cases across and beyond the enterprise. It correlates the data and events in real-time with the historical data, the companies gain real-time visibility of information. It gives the information at their fingertips so that the companies can make smarter decisions and maximize profits.
  • Operational Intelligence is one of the key levers for uplifting operational efficiency. It equips organizations with actionable insights into their key drivers across the entire value chain. Operational Intelligence places complete information at one's fingertips, enabling one to make smarter decisions in time to maximize impact. By correlating a wide variety of events and data from both streaming feeds and historical data silos, OI helps organizations gain real-time visibility of information, in context, through advanced dashboards, real-time insight into business performance, health, and status so that immediate action based on business policies and processes can be taken.
  • Operational Intelligence applies the benefits of real-time analytics, alerts, and actions to a broad spectrum of use cases across and beyond the enterprise. The collection, sharing, analysis, and application of Operational Intelligence via web-based technology gives decision-makers at all levels in a commercial organization an exceptional means to maximize the use of their resources. OI tells them precisely what is going on in the precise domain or geographical location of their operation that concerns them. Operational Intelligence is an evolutionary and technological leap beyond Business Intelligence and Management Information systems that presented a retrospective, static, and at best generic Intelligence about an organization's performance. These unique advantages of OI over conventional tools will drive the market ahead in the coming years as companies that enable their management to respond in a timely manner to operational variances and market volatility are better placed to minimize the adverse impacts caused by uncertain operational procedures and disturbances in the market.
  • Cisco Systems estimates that around 42% of all data generated by 2020 is likely to be from the machines, which include sensors, networks, security systems, servers, storage, and applications. Real-time data analytics can influence the IoT and Big Data capabilities to enhance business operations.
  • COVID-19's spread has hastened the implementation of operational intelligence techniques. It is critical for businesses to use digitally enabled solutions to improve the efficiency of operations when working remotely. The Asia Pacific energy industry is accelerating its adoption of the 4th Industrial Revolution digital toolbox and embedding better operational efficiencies as a result of the economic demand devastation caused by the COVID-19 epidemic. In addition, as the pandemic takes a toll on the energy sector, worldwide investment in the sector is likely to drop 20% this year, or over USD 400 billion, compared to last year, according to International Energy Agency.

Key Market Trends

Growing Need for Real Time Data Analytics will drive the market

  • Real-time big data analytics is a big data innovation. While big data analysis converted the database after the raw files were created, real-time big data analysis converts the raw files as they are created. Just other words, the hazy raw data is turned into useful data in milliseconds after it is created. The responses come in a timely manner.
  • Businesses lose money due to delays in decision-making and operations. Real-time analytics overcomes this problem by allowing company leaders to make decisions based on rapid and actionable data insights. This means that businesses can avoid costly delays, seize opportunities, and anticipate issues.
  • Real-time data analytics can be used for a variety of purposes in almost any sort of business (and even on an individual basis). When it comes to running a firm and keeping a finance team going at full capacity, real-time data analytics is practically a prerequisite. Finance teams can use real-time data analytics for a variety of purposes, including determining how everyday operations are working (identify bottlenecks), implementing process improvements (analyze KPIs), and monitoring a company's financial position (reporting), to mention a few.
  • SAP HANA is a single database that combines powerful data processing, application services, and flexible data integration capabilities into a single database. HANA makes use of in-memory database software, which allows users to query data that is kept in the system's memory (RAM) rather than on physical drives. Customers may now process data in a variety of different ways, much faster, and create a series of what-if scenarios to help them capitalize on opportunities or prevent pitfalls. Other established technology suppliers, such as IBM and Oracle, have also used new technology to enable real-time operations in their platforms.
  • Real-time data analytics has some drawbacks, despite being attentive in dealing with massive amounts of data. Real-time data analytics must be accessible not only to manage enormous amounts of data but also to respond quickly to requests. This implies that real-time big data analytics should be capable of dealing with market and business elements to make effective and efficient real-time judgments.

Increasing Adoption of Big Data Analytics and the Internet-of-Things (IoT) will drive the market

  • The market is being driven by end-user adoption of Big Data Analytics and the Internet of Things (IoT). Operational intelligence (OI) and analytics solutions have earned a significant market share in the last decade, thanks to the rise of Big Data and the growing need to make key business decisions in a short amount of time. According to IBM, 62% of merchants believe that using data (Big Data and analytics) gives their businesses a competitive advantage. This number compares to 63% of responses from all industries.
  • Furthermore, the Internet of Things (IoT) is a digital connectivity extension to gadgets and sensors in homes, workplaces, automobiles, and possibly practically anyplace. As a result of this breakthrough, nearly any device may now collect and communicate data on its activities, which can then be analyzed to aid monitoring and a variety of automatic functions. IoT requires operational intelligence to complete these duties (OI). PTC Inc, for example, uses IIoT-delivered operational efficiency insights to evaluate real-time production performance and anticipate problems before they occur.
  • During the pandemic, digital transformation in healthcare, manufacturing, retail, and other industries is likely to increase data creation. Automation in the manufacturing business is driven by the industrial internet of things (IIoT) and artificial intelligence (AI). Inventory management, asset management and predictive maintenance, real-time alerts, network manufacturing, and other technologies are being introduced to help the manufacturing industry prosper in uncertain business situations.

Competitive Landscape

The Asia Pacific market for operational intelligence is fragmented and competitive, with small and big vendors providing visibility and insight into the business operations, allowing companies to make data-driven decisions. Key players are Vitria Technology Inc., Splunk Inc., etc. Recent developments in the market are:
  • January 2021 - Dun & Bradstreet acquired Bisnode, a European data & analytics business headquartered in Sweden. This acquisition benefited its clients by offering critical business intelligence help to them achieve their growth goals.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

This product will be delivered within 2 business days.

Table of Contents

1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Forces Analysis
4.2.1 Threat of New Entrants
4.2.2 Bargaining Power of Buyers
4.2.3 Bargaining Power of Suppliers
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
5.1 Market Drivers
5.1.1 Growing Need for Real Time Data Analytics
5.1.2 Increasing Adoption of Big Data Analytics and the Internet-of-Things (IoT)
5.2 Market Restraint
5.2.1 Combining Data from Multiple Data Sources
6.1 By Deployment Type
6.1.1 Cloud
6.1.2 On-premise
6.2 By End-user Vertical
6.2.1 Retail
6.2.2 Manufacturing
6.2.3 BFSI
6.2.4 Government
6.2.5 IT and Telecommunication
6.2.6 Military and Defense
6.2.7 Transportation and Logistics
6.2.8 Healthcare
6.2.9 Energy and Power
7.1 Company Profiles
7.1.1 Vitria Technology Inc.
7.1.2 Splunk Inc.
7.1.3 SAP SE
7.1.4 Inside Analysis (The Bloor Group)
7.1.5 Software AG
7.1.6 Schneider Electric SE
7.1.7 Rolta India Limited
7.1.8 SolutionsPT Ltd
7.1.9 IBENOX Pty Ltd
7.1.10 Turnberry Corporation
7.1.11 HP Inc.
7.1.12 OpenText Corporation

Companies Mentioned

A selection of companies mentioned in this report includes:

  • Vitria Technology Inc.
  • Splunk Inc.
  • SAP SE
  • Inside Analysis (The Bloor Group)
  • Software AG
  • Schneider Electric SE
  • Rolta India Limited
  • SolutionsPT Ltd
  • IBENOX Pty Ltd
  • Turnberry Corporation
  • HP Inc.
  • OpenText Corporation