Data Analytics Outsourcing Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

Data Analytics Outsourcing Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

The data analytics outsourcing market was valued at USD 3.04 billion in 2020, and it is expected to reach USD 9.46 billion by 2026 at a CAGR of 21.5% during the forecast period from 2021 to 2026. Artificial Intelligence (AI)/Machine Learning technology has replaced humans in many aspects of data analytics, thus, requiring less input from human manual work. The nature of data analytics outsourcing, therefore, skews toward how humans can effectively create and train a machine learning model rather than how businesses could manage an offshore team.

Key Highlights

• Over 90% of the world's data was created in the last two years, as per IBM. And the shortage of the right talent has led to the growth of analytics solutions, as the acceptance is stemming from several industries BFSI, retail, to name a few. The FMCG manufacturers, for instance, are observed suffering from unstable sales performance lacking the capability to diagnostic analytics, to identify what triggers poor performance or make accurate sales forecasts. At such a moment, the manufacturer has required time and budget to grow an in-house data analytics team. Therefore, they turn to analytics outsourcing in the hope of fast insight.
• Many businesses were in the process of outsourcing their data operations even before the COVID-19 pandemic, and the current situation even more speed up this process. Firms are also shifting a large percentage of their IT spending dollars into cybersecurity projects. According to DataScience blog, a recent survey found that 37% of business leaders said they were already going to cut their IT department budgets. The same study found that 28% of businesses are going to move at least some part of their data analytics programs abroad.
• The generation of huge amounts of data has led the companies to seek insights, such as customers' segmentation, understanding of the preferences under each segment, staying updated with changes in behavior, and personalization of services. Additionally, due to the rise in the usage of the internet, there is an enormous amount of structured and unstructured data available to organizations. Such benefits have led multinational and large companies to get their Big Data analyzed for actionable insights.
• Cloud migration has also boosted adoption as inherent cloud characteristics, such as scalability, agility, cost-effective storage options, and access to vast processing power, complement the ability to harvest Big Data. Besides, cloud computing technology has become mainstream, and the seamless connectivity provided by the cloud is making it accessible and leading to the generation of Big Data and applications. According to the Right Scale's annual State of the Cloud Report 2021, 19% of businesses use public cloud, 2% use private cloud, and 78% use hybrid cloud. Hence, the advent of cloud technology is also boosting the growth of the market studied.

Key Market TrendsBFSI is Expected to Hold Major Share

• Data analytics has many purposes in the banking industry, ranging from improving cybersecurity to reducing customer churn. Banks can even harness external regulatory, trading, and social media engagement data, all of which can be processed and analyzed to benefit their operations. For example, Santa Rosa, California-based Redwood Credit Union, found that social data was particularly important when offering auto loans. It initially extended preapproval for such loans every two years based solely on members' credit scores and vehicle purchase histories. It soon discovered that there was a much more reliable indicator and updated its preapproval frequency accordingly.
• Big Data significantly affects banks' back-of-house operations as well as their customer-facing processes. It is key to risk management functions, which entail assessing the likelihood that any given transaction could be fraudulent or present a credit risk. Data analytics systems can analyze thousands of variables for each transaction, including applicants' lending histories, past transactions associated with their credit cards, or individual items in their credit histories. This gives bank staff educated predictions regarding interactions' risk factors. Bank of America's Corporate Investment Group (CIG) used a data analytics system to calculate the default probability of approximately 9.5 million mortgages, reducing the calculation time from 96 hours to just 4 hours.
• In January 2020, The Financial Conduct Authority (FCA) and the Bank of England (Bank) outlined their plans to develop their data and analytics capabilities. Both authorities depend on access to high-quality data to fulfill their respective missions of maintaining monetary and financial stability, market integrity, effective competition, and consumer protection. FCA's refreshed Data Strategy sets out a transformation plan to become a highly data-driven regulator. The strategy outlines the organization's increased focus on the use of advanced analytics and automation techniques to deepen its understanding of how markets function and allow the FCA to efficiently predict, monitor and respond to firm and demand issues.
• During the 2020 ABA Conference for Community Bankers, KlariVis, a unique and proprietary data analytics software platform developed by bankers for bankers, announced that it had been selected by three community banks: Select Bank & Trust; the Bank of Botetourt, and the Farmers Bank of Appomattox. KlariVis helps community financial institutions to make more strategic and better-informed decisions by uncovering and providing access to their transformative data. KlariVis compiles and aggregates actionable data in an automated fashion providing banks like Select Bank & Trust improved and timely insight into factors such as deposit, loan, and revenue growth. Community banks can make data-driven decisions across their entire organization, gaining a significant competitive advantage in today's market.

Asia Pacific Region is Expected to Witness Fastest Growth

• With Big Data analytics used in finding existing insights and creating connections between data points and sets and cleaning the data, the rapid adoption of outsourcing of data analytics is making projections about future activity, trends, and customer behaviors. According to the China Academy of Information and Communications Technology (CAICT), the Big Data Market size in China is expected to reach CNY 57.8 billion by 2020 from CNY 32.7 billion in 2018. Being augmented by AI/ML with analytical models, major IT firms, and analytics firms in the region are building an ML practice and developing vertical-specific AI solutions.
• The data from increasing social penetration contains hidden patterns that traditional analytics tools are unable to find, and require increased adoption of analytics. According to We Are Social, as of January 2021, the active social network penetration in China and the United States accounted for 64.6% and 72.3%, respectively, indicating again the presence of the massive amount of data generation requiring analytics. ​This is acting as a catalyst for businesses in the country to opt for data analytics outsourcing.
• India has been leading revenue generation in the analytics market, with TCS generating USD 2 billion from analytics services. Additionally, companies, like India Inc. led by TCS, Genpact, Wipro, are investing heavily in such domain, thereby increasing the range of services being offered, as per 2019 study Analytics India Magazine and Praxis Business School. Also, almost 47% of analytics revenues in India have risen from exports to the United States, while the United Kingdom, in the second position, is recording 9.6% of revenues of overall USD 27 billion generations from outsourcing.
• In China, high-tech and big data analysis have been widely used to support government policy decisions, continuing in the fight against COVID-19. Based on the data platform, advanced data analytics created a path map for people flow, especially for those who came from and passed through Hubei Province or other outbreak areas. These maps tracked the flow of people who had tested positive for the coronavirus in the past 14 days, to find out who these people had come into close contact with. These results helped the local government and communities to implement defensive measures.

Competitive Landscape

The Data Analytics Outsourcing Market is fragmented, with various vendors proving business process solutions for big companies and SMEs. As the amount of big data generated by enterprises increases, more vendors are being contacted to manage enterprise data and provide data intelligence services. Technological advancements in the market are also bringing sustainable competitive advantage to the companies, and the market is also witnessing multiple partnerships and mergers.

• January 2021 - Genpact has acquired Enquero, a firm that offers data engineering and data-led digital transformation services. Enquero will increase the scale and depth of Genpact's data and analytics teams and further enhances its capabilities to accelerate the digital transformation journeys of its clients,
• June 2020 - Accenture entered into an agreement to acquire Sentelis, an independent data consulting and engineering company, headquartered in France, that specializes in designing and scaling data and artificial intelligence (AI) capabilities. Sentelis would join Accenture Applied Intelligence and complement its focus on helping clients build the right data strategy and foundation to industrialize AI across their businesses.
• February 2020 - Capgemini announced the signing of an agreement to acquire Advectas, one of the leading business intelligence and data science company in Scandinavia. By joining Capgemini’s Insights & Data global business line, the 200+ strong Advectas team will help to meet further growing client demand for Capgemini’s business intelligence and data analytics services across the region.
• Feburary 2020 - SEBI shortlisted IBM India and other data service provider companies to implement a data analytics project through which the regulator wants to track possible market manipulations, such as insider trading and front running. The move is part of SEBI's efforts to address and handle challenges arising out of technological advancements in the markets.

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• The market estimate (ME) sheet in Excel format
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