Friday 1 April 2016

Data Analytics Outsourcing Market boost operational efficiency & maximize profits across organizations

Data analytics outsourcing services to help in understanding customers’ motivations & brand loyalties thereby enabling strategic policy formulation across companies offering them competitive edge over their rivals


Rise of big data analytics to boost data analytics outsourcing market


Data analytics is fact gaining traction among various industry horizontals. The developments are driven by data explosion, vast proliferation of mobile devices and emergence of big data; this has fundamentally changed the perceptions of consumers and the way companies conduct their business in hyper connected world.

Data analytics outsourcing is the outsourcing of data and statistical research, along with application of various computational models to help in effective decision-making and advanced business analytics solutions to third party vendors. The tools help enterprise to better decisions, cut down costs, boost operational efficiency and able to offer customized services to clients. Several companies prefer use the services to gain a comprehensive analysis into voluminous data through various quantitative and qualitative tools to gain customer insights. These services have enabled companies to understand customers’ motivations and brand loyalties through tracking responses on social media platforms, getting potential preferences and dislikes and getting customer feedback on buying decisions.


Market Prospects


Managements choose to base most of their strategic decisions on qualified data analytics, including marketing analytics, credit risk analysis, fraud analytics and predictive science. Rapid  data generation by organizations in various sectors and low cost involved in storage of data are the factors that have fostered the impending need for making a proactive and successful business decisions on the basis of data analytics tools. As most mid-size and small organizations lack the budgets to use data analytics in-house, outsourcing model is fast emerging as a prominent model in data analytics. The data analytics outsourcing market is considered to be at nascent stage; growing awareness about potential benefits of data analytics in business decision making that boost productivity across verticals are the factors that would offer increased momentum to the market. Several privacy concerns related to confidential data and data security issues may hinder the market growth and would remain key issues warranting attention by key IT & technology players involved in providing security solutions.

Major application segments of the market are sales analytics, marketing analytics, risk & financial analytics and supply chain analytics and are their applications implemented in various business functions including sales, marketing, risk assessment & finance, and others. As per a recent report by Allied Market Research titled “World Data Analytics Outsourcing - Market Opportunities and Forecasts, 2014 – 2020, marketing analytics contributes a major share globally, followed by sales analytics.

Competitive landscape


Over the past decade, the data analytics outsourcing market has witnessed a significant upsurge in the number of third party service providers that offer outsourcing analytics. Prominent market players are Wipro, Infosys, HCL, TCS, HP, Genpact, Evalueserve and JP Morgan which are proactively involved in offering cutting-edge solutions for various business problems through the combination of market research and data analytics. Several other market players such as WNS, Marketics, Annik Systems Arana, CRISIL ValueNotes and AC Nielsen have made foray in the domain led by immense growth opportunities in the market. As per the report, the world data analytics outsourcing market is forecast to reach $5.9 billion by 2020, growing at a CAGR of 29.1% during 2015–2020. The vendors offer a wide spectrum of outsourcing services that help consumers gaining competitive edge over their rivals in formulating effective business decisions and achieve operational efficiency thereby maximizing profits.