Data Analytics Most Instrumental in Enhancing Customer Experience and Lowering Risk for Organizations

• Innovating new business models and maximizing revenue and profits are the next set of priorities for data analytics  

• Finance and accounting, marketing and operations are key functions that leverage analytics extensively  

• When combined with data analytics; allied technologies like AI, IoT & Cloud perceived to be the most effective in delivering better business outcomes. Data Analytics Most Instrumental in Enhancing Customer Experience and Lowering Risk for Organizations : Infosys Research  

Bangalore, December 4, 2018 : Infosys, a global leader in next-generation digital services and consulting, today published a global research on data analytics from the Infosys Knowledge Institute. The survey titled, ‘Endless possibilities with data: Navigate from now to your next’, reveals that a majority of organizations are deploying analytics to enhance customer experiences and mitigate risk.

This research tries to understand how data analytics is becoming core to driving digital transformation for enterprises and makes an assessment of enterprise expectations in a world of endless possibilities with data. It also explores a range of challenges, opportunities, and the role of new technologies in the analytics world.

Highlights of the survey :  

  • 31% of respondents identified the use of analytics with experience enhancement. This includes using intelligence generated by listening to internal and external stakeholders to drive extreme personalization and high quality customer service
  • 28% respondents were interested in leveraging analytics for risk mitigation – predicting risk to enable better decision making, and detecting anomalies that could disrupt business effectiveness
  • Developing new business models by unearthing the latent needs of customers and offering innovative products and services was seen as the primary analytics requirement of 23% of respondents.
  • Revenue and profit maximization through increasing channel effectiveness and thereby enhancing profitability across processes, channels and stakeholder ecosystems was the analytics priority for the remaining 18%.
  • The majority of respondents in the U.S. (32%) and Europe (34%) stated they would like to use analytics for experience enhancement whereas in ANZ about 31% respondents consider it for risk mitigation

Functions across organization are benefiting from the possibilities of data. Finance and accounting was found to use analytics the most at 32%, followed by marketing and operations at 20% and 17% respectively. In terms of emerging technologies, Artificial intelligence was perceived to deliver increased outcomes when combined with analytics at 37% followed by IoT and Cloud Technologies at 19% and 16% respectively.

The survey found that enterprises in every industry encountered several challenges that prevented them from implementing their analytics initiatives fully. The biggest challenges stemmed from a lack of expertise in integrating multiple datasets (44% of respondents) and failure of understanding in deploying the right analysis techniques (43%). This is where enterprises are looking up to their partners to help industrialize their analytics capabilities by creating an analytics strategy, build an operational framework, and define a process for executing and governing analytics initiatives.

Satish H.C., EVP and Head, Data Analytics, Infosys, said, “In the world of endless possibilities that data provides, being data native is core for enterprises to being digital. As enterprises work with limitations of siloed systems, data integration issues, resources and skills, harnessing the possibilities with data will be essential to navigating their next. We believe that the findings of this survey will help our clients to fast-track their journey into a data-native enterprise by industrializing their analytics capabilities and ultimately monetize data.”

For a full copy of the report, visit at :  http://www.infosys.com/endless-possibilities-with-data

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