|Base Year Market Size
|USD XX Billion
|Forecast Year Market Size
|USD XX Billion
|Fastest Growing Market
The global data analytics outsourcing market size was valued at USD 7,79 billion in 2021, growing at a CAGR of 34.2% and expected to reach USD 81.98 billion during the forecast period.
Data analytics is the process of analyzing data sets, which consists of identifying and examining patterns and making inferences based on the information those data sets hold. Data analysis is increasingly carried out with specialized computer systems and software. Many different kinds of IT and business functions, including pretty strategic ones, are outsourced by companies to service providers. This increasingly includes data analytics, one of the areas of the technology spectrum that offers a significant advantage in terms of competitiveness.
With data analytics outsourcing, businesses hire service providers to analyze the information they provide to the outsourcing company. According to industry research, service demand is on the rise. Most businesses today recognize the benefits and profitability of outsourcing data analytics services. Sometimes, lacking skilled personnel and knowledge compels businesses to outsource data analytics. Outsourcing data analytics encourages businesses to gain market share and customer ideas and make strategic business decisions based on the data analytics report. One of the foremost factors driving the data analytics outsourcing market growth is the escalating volume and complexity of digital information. But even so, data privacy and security issues are having the most significant effect on the data analytics outsourcing market share. In addition, the increased focus on managing data from social media platforms and the rapid expandability of outsourcing data analytics models are anticipated to create a lucrative market opportunity.
The era of digitization has resulted in a global explosion of digital data production. The increased prevalence of digital devices, like computers and mobile devices, in the daily lives of ordinary consumers is one of the prime reasons driving this increase in digital data output. In addition, the increasing popularity of the Internet of Things (IoT) and the data produced by various IoT devices have contributed to this data explosion. It has been difficult for data analysts to process and interpret vast amounts of digital data outputs. In-house solutions can be costly and involve a substantial initial investment, making outsourcing data analytics solutions even more critical for businesses. In addition to knowing data analytics skills, outsourcing services can aid businesses in speedily establishing an analytics framework, which may not be simple or even possible for them to do internally. These factors lay the groundwork for the future market expansion for data analytics outsourcing.
Companies like Amazon have utilized data analytics for over a decade. With the aid of its in-house data scientists and analysts, Amazon has developed algorithms centered on the everyday needs of its customers. The algorithm uses all of the information Amazon collects on its customers to target customers with specific products, increasing the probability of a sale. As in-house solutions are costly, smaller businesses may not access these resources and may need to rely on third-party solutions for their data analysis needs. In addition, third-party solutions offer a wealth of expertise from various industries and related businesses/projects, which can directly contribute to the company's goals and needs. Therefore, businesses employ data analytics outsourcing solutions to gain access to experienced experts at a fraction of the cost, resulting in market expansion.
When outsourcing, there is always the threat of losing control of the data or a data breach. Data protection and privacy must be ensured. For these threats to be mitigated, companies that outsource their data analytics solutions may have significant concerns about how and where their data is stored and whether or not that location is the best fit for their organization. A third-party solution may choose the option that is either the cheapest or the most convenient for them (or both), putting their security policy and data protection at risk. Consequently, a loss of control over a company's sensitive data due to outsourcing could reduce the need for data analytics outsourcing.
In addition to the opportunity to learn data analytics skills, outsourcing services can also help organizations speedily create an analytics framework that would otherwise be difficult since it gets expensive for a small or medium-sized business to achieve with its internal resources. According to Close, utilizing the outsourcing company's resources and technology to improve the operational efficiency of data analysis methods and technologies, whether by introducing an advanced data center, implementing robotic process automation, or deploying cloud-based software, can be a significant benefit. A company that outsources its data analytics to a third entity may also be able to implement technologies it had not previously considered. Small and medium businesses may not even be able to employ such capabilities in-house. Consequently, outsourcing analytic data requirements may only be viable for many organizations, which bodes well for the future market for data analytics outsourcing.
The region-wise segmentation of the global data analytics outsourcing market includes North America, Europe, Asia-Pacific, and LAMEA.
Asia-Pacific is anticipated to grow at the highest CAGR of 37.4% and hold the largest share during the forecast period. The market dominance of the Asia-Pacific region may be attributable to the rise of digitalization and e-commerce services in India and China for various business purposes. In the Asia-Pacific region, the availability of a labor force, low labor costs, and an evolving IT infrastructure are also expected to contribute to the growth of the target market. By speedily adopting outsourcing of data analytics with Big Data analytics, existing data is discovered, and connections are made between data points and sets based on forecasts of future activity, trends, and customer behavior. India has been a leader in generating revenue in the data analytics outsourcing market, with TCS analytics services generating USD 2 billion. In addition, approximately 47% of India's analytics revenue came from exports to the United States, while the United Kingdom generated 9.6 % of USD 27 billion in outsourcing revenue. Such factors and contributions from the region's nations are most likely to propel Asia-Pacific's data analytics outsourcing market growth.
North America will hold the second-largest market share of USD 35,271 million, growing at a CAGR of 32%. Regarding innovation and technological advancement, North America is among the regions with the most rapid growth. In the past five years, the region has implemented technologies like Big Data, IoT, artificial intelligence, cognitive learning, machine learning, and driven solutions in an effective manner. These technologies are highly data-intensive and responsible for the daily generation of vast quantities of data that are stored, processed, and analyzed as often as required. The region's expansion can be attributed to the growing usage of sophisticated technologies by the field's data-generating end users. In addition, rising data volumes from departments such as production, procurement, sales, marketing, and human resources are predicted to boost the demand for data analytics outsourcing in the region.
|By Industry Vertical
|Fractal Analytics Ltd Opera TYPEs LLC ZS Associates, Inc. Tata Consultancy Services Ltd. Wipro Ltd. Genpact Ltd. Accenture Capgemini IBM Corporation Mu Sigma, Inc.
|U.K. Germany France Spain Italy Russia Nordic Benelux Rest of Europe
|China Korea Japan India Australia Taiwan South East Asia Rest of Asia-Pacific
|Middle East and Africa
|UAE Turkey Saudi Arabia South Africa Egypt Nigeria Rest of MEA
|Brazil Mexico Argentina Chile Colombia Rest of LATAM
|Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends
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The global data analytics outsourcing market is classified based on type, application, industry vertical, and region.
The fragments include descriptive, predictive, and prescriptive analytics based on type.
Predictive analytics will likely hold most of the data analytics outsourcing market share, growing at a CAGR of 33.7% during the forecast period. Predictive analysis is poised to revolutionize how businesses operate in the current century. Organizations that provide significant services to end-users will benefit from a thorough understanding of customer requirements and corresponding preparation. With technological advancements in business sectors like manufacturing and logistics, the requirement for predictive analytics solutions is anticipated to increase significantly over the next few years. Consequently, the expansion of the global predictive segment is presumed to accelerate. Other factors contributing to the segment's rapid expansion are the greater use of Big Data and the cloud by businesses, the introduction of product differentiation, and the rising need to adopt new technologies.
Descriptive analytics will have the second-largest market share. Descriptive analytics is the assessment of historical data to better comprehend business changes. It describes the comparison of a variety of historical data sets. Data aggregation and data mining are the primary data collection techniques for descriptive analysis. The descriptive analysis employs a vast array of data to accurately depict what has occurred in a company and how it varies from other comparable periods.
Based on application, the fragments include sales analytics, marketing analytics, risk & financial analytics, supply chain analytics, and others.
Sales analytics is expected to hold the largest market share during the forecast period growing at a CAGR of 32.3%. Using their data, sales analytics tools enable organizations to gain insight into sales pipelines, products, and staff performance assessments. With these learnings, one is better equipped to comprehend, manage, and produce more precise sales forecasts. Sales process analysis can differentiate between efficiency and productivity. Using data insights to identify the most promising opportunities aids the sales team in responding to the most promising sales leads. These factors drive the segment of sales analytics. In addition, the growing demand for an enterprise sales team to develop a strategy, execute and evaluate campaigns across multiple platforms, and make better decisions is anticipated to create more market opportunities.
Marketing analytics will hold the second-largest share. The global marketing analytics segment is driven by factors such as the growing use of social media channels for advertising, the increasing investment in advertising products, and the need to comprehend customer behavior. The global marketing analytics market is benefiting from the unprecedented advantages of marketing analytics, which marketers use to assess the effectiveness of their efforts.
Based on industry vertical, the fragments include BFSI, telecom, retail, healthcare, media & entertainment, and others.
BFSI segment is most likely to hold the largest market share during the forecast period growing at a CAGR of 32.1%. BFSI includes:
The impact of big data analytics on banks' back-office operations and customer-facing processes is substantial. This is an essential aspect of risk management tasks, such as assessing the likelihood that a transaction is fraudulent or presents a credit risk.
Data analytics systems can analyze thousands of parameters for each transaction, such as the lending history of applicants, past payments associated with their credit card, and specific items in their credit history. It provides bank employees with informed predictions regarding risk factors of interaction. These factors drive the BFSI market segment.
The Telecom sector will hold the second-largest share. Data analytics services for the telecommunication sector enable organizations to maximize consumer engagement, increase customer loyalty & retention, personalize cross-sell-up sales efforts, optimize value and offers, strengthen collection and recovery, maximize profitability by decreasing customer churn through default rates, and boost customer engagement. In addition, the popularity of social media has generated enormous amounts of data and reduced the cost of data storage, driving the expansion of the market for data analytics outsourcing.