Analytics-first Approach for Business Intelligence

Analytics-first Approach for Business Intelligence

“ML and AI, with all its cognitive and intuitive brilliance, are shaking up the business landscape. The integration of ML, AI and data analytics ups the ante in customer experience, allowing these ML-enabled systems to draw on vast volumes of structured and unstructured data to elevate customer engagement,” says Keshav Murugesh, Group CEO, WNS, in an exclusive interview with EnterpriseTalk.

 ET Bureau: How does an analytics-first approach enable clients to address tangible business problems?

Keshav Murugesh: Enterprises are facing a “data deluge,” where an exorbitant amount of internal (for example, CRM, ERP and machines) and external (such as social, public data, geospatial and smart meters) interactions with customers and other businesses are bringing in thousands, if not millions, of records daily. This immense amount of data is also extremely complex, with various structured, unstructured and semi-structured forms the metrics can take on.

Harnessing this vast amount of data is still a massive undertaking, but data analytics enables this access at scale – through various technologies and methodologies. Identifying and capturing the right data, storing and hosting it profitably and securely, and analyzing as well as disseminating insights, are all possible through analytical techniques. This essentially leads to businesses having insights about their key performance metrics at an increased speed. Elevated customer expectations across the board also mean that enterprises do not have the bandwidth to wait for months to serve their customers more effectively or mitigate any risks they foresee.

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An “analytics-first” approach ensures that organizations can leverage existing and continuously emerging data to generate the needed intelligence which can be actionable across business processes. Such a strategy helps any enterprise to avoid “guessing” the questions that need to be asked, and instead focus on what indeed needs to be improved (customer experience for instance), reduced (costs) and optimized (supply chains). An analytics-first strategy also affords enterprises a chance to simulate transformations without commensurate investments from the get-go.

For instance, when a manufacturing company faces Christmas-level sales that are 20 percent higher than the normal demand due to stockpiling, acquiring insights into customer preferences and pre-dominant trends using curated social media behavior along with other predictors can give it a head start in forecasting demand.

ET Bureau: What is the advantage of advanced analytics being powered by machine learning and AI, and how does this translate to BPM solutions?

Keshav Murugesh: Imagine a customer calling a support center for car insurance policies. An automated response answers the phone, but instead of the automated system saying “press a button” or “repeat,” the voice at the other end completely understands the customer’s request. The automated system interprets questions precisely as well as the emotional tone of the caller.

It processes the natural language command, provides meaningful answers, and to top it off, the automated system gives relevant, valuable suggestions. Despite being a computer, it’s able to intuitively understand the complexity of a customer’s request and end the conversation with a satisfied caller.

ML and AI, with all its cognitive and intuitive brilliance, are shaking up the business landscape. The integration of ML, AI and data analytics ups the ante in customer experience, allowing these ML-enabled systems to draw on vast volumes of structured and unstructured data to elevate customer engagement.

Also Read interview: Capitalizing on AI Talent Marketplace for Future-proofing the Workforce

Beyond enhancing customer experience directly, analytics is also supporting back and mid-office business processes, in their bid to become more “intelligent.” It is being applied extensively in the form of audit and recovery analytics (to prevent leakages in payables), forensic analytics (to enhance compliance), cash flow forecasting (for liquidity planning), working capital analysis (to unlock cash flows), and for effective real-time monitoring. Likewise, it finds its applications in HR analytics towards voice of the employee analysis, and for analyzing retention policies; as well as operational analytics such as analyzing device data (supporting multiple use cases across industries such as utilities, insurance and manufacturing).

A system being able to insightfully predict actions, and offer tangible insights, is extremely valuable for a business managing millions of customers and metrics all at once. Data can be processed across all channels and analyzed for in-depth insights—at unprecedented speeds and volumes. ML tools personalize marketing initiatives better for new products and services. The intelligent cognitive front office agent delivers outstanding customer experiences with ‘always-on’ and real-time collaboration between all enterprise systems.

ML and AI streamline a massive undertaking that enterprises are faced with in keeping up with consumer demand. Through ML and AI, a business can bring their Business Process Management (BPM) capabilities to its fullest without having to sacrifice valuable manpower and larger business priorities.

 ET Bureau: In what ways does data provide business intelligence insights, and how is WNS helping guide its clients through these metrics?

Keshav Murugesh: As mentioned earlier, data and the analysis of data are at the core of effectively doing business. How could an enterprise with hundreds of employees, and millions of customers, be able to manage every granular detail without insightful, fully analyzed metrics? Data and business intelligence go hand-in-hand and without data business intelligence is far more difficult to manage at enterprise scale.

Having access to the right business intelligence is key in managing a business’ performance. Derived from historical and forecasted data, business intelligence helps to manage exceptions, establish causation, manage alerts, foresee problems and enables access to the right leading and lagging indicators for any business.

From banks to healthcare providers to insurance companies, WNS’ unified analytics solution builds intelligence into processes via end-to-end data-to-decision services, built through a Center of Excellence (CoE) model based on client needs. Resulting in faster data management, analytics modeling and visualization, our unified analytics solution has driven transformational benefits to our clients by providing timely and accurate business intelligence as needed.

For a leading consulting and investment advisory firm, the solution enabled the company to quickly answer customers through the immediate review of data, bringing down contact center cost of ownership by 40 percent. For a leading US bank, WNS charted a comprehensive fraud detection strategy – this solution saved USD two million in revenue loss, with 40 percent reduction in true name fraud cases in a year.

WNS’ unified analytics provides companies with tools and methodologies that inform business intelligence, giving a guide to metrics that offer an in-depth, granular look into processes. From finding correlations in data insights to detailed dashboards with all the necessary details, it offers insights that otherwise would be lost given the massive amounts of data companies receive daily.

While enterprises face the challenges of rapid digitization, especially during 2020, insightful data analysis can offer critical business intelligence that could potentially otherwise be lost. It’s crucial that enterprise businesses have access to data insights in order to succeed in today’s digitized world.

Keshav Murugesh serves as Group Chief Executive Officer and Member of the Board of Directors of WNS. He is a member of The Wall Street Journal (WSJ) CEO Council and has been the Chairman of Nasscom* for 2019-2020. He was also the Chairman of the Nasscom Consumer Interest Protection Task Force. Keshav is a Member on the Board of WNS Cares Foundation that focuses on community-related projects, especially education for lesser-privileged children in WNS locations globally. Prior to WNS, he has held several leadership positions in global companies, including President and CEO, Syntel Inc. and ITC Ltd. (an affiliate of BAT Plc.

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