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In an eco-system that demands more out in less time, it is becoming more important than ever to make the processes simplified and transparent. However, without having the right system in place, it is next to impossible to achieve such lofty goals, particularly when the operational procedures are all interdependent and data intensive. Therefore, to transcend the conventional barriers businesses are largely depending on business process management services. WNS Global Services applies deep industry knowledge to derive insightful analytics to help companies upscale their business with their unique data-driven Business Process Management (BPM) services. Analytics Insight has engaged in an exclusive interview with Akhilesh Ayer Head, Research & Analytics Business Unit, WNS Global Services.
The data and analytics technology landscape is evolving rapidly in line with the evolution in computing power, storage, and analytical techniques. When it comes to data and analytics maturity, enterprises fall in the spectrum between beginners to mature adopters of data and analytics. The last few years have seen the rise of 'Unicorn' startups that are pioneering the use of data and analytics in their day-to-day business. Today, almost 100 percent of e-commerce startups, private banks, retail & consumer companies, and FinTechs are utilizing analytics in multiple ways to improve business growth and optimize costs. They have leveraged the benefits of evolving technology trends such as cloud, AI, and data-driven decision-making to deliver differentiated customer experience in real time. Traditional organizations such as public sector banks and other government enterprises are in the early stages of adoption. They are getting their data strategy in place to embark on their journey towards becoming a data-driven organization.
The COVID-19 pandemic has accelerated the pace of digital transformation. Today, organizations are looking to stay connected with their customers in real time. Therefore, embedding customer-centricity in every function across the company is crucial. This also requires organizations to be 'always present' across all physical and digital channels, enabling them to proactively adapt to and fulfill the rapidly evolving customer expectations. The ramification is that data needs to be available, insightful, and analytical, and AI needs to enable decision making almost real-time.
Further, to keep pace with supply chain disruptions and customer demands, organizations are increasingly building intelligent operations fueled by analytics through an accelerated test, learn and scale approach to new capabilities. They are also moving up the maturity curve in adopting AI by operationalizing AI in their enterprise-wide decision-making and automation. This results in a demand for transparent and explainable implementation of AI and ML algorithms.
All organizations broadly fall into three categories in terms of the maturity of their adoption of data and analytics — beginner, intermediate and advanced. Our experience suggests that the challenges faced in adopting data and analytics are different across the beginner to advanced maturity spectrum. The recently commissioned global survey conducted by Forrester Consulting on behalf of WNS validates our observations. The hurdles for beginners are mostly in defining and articulating a data strategy or what must be the Key Performance Indicators (KPIs) to measure success. Those at the intermediate stage find it hard to constantly refine their organizational structure, expertise, and analytics processes. Advanced organizations often centralize their data and insights talent at the corporate level, with limited ability to support the specific needs of different lines of business.
It's critical to get all the five pieces of the puzzle in place to become a mature data-driven organization — strategy, people, practices (methodologies and frameworks), data, and cloud platforms. So, in essence, customers must first invest in their ability to process vast amounts of data with the right data management, governance, and security capabilities, besides having the right talent and strategy.
WNS Triange is the data and analytics practice of the company. At WNS Triange, we provide a broad spectrum of data and analytics services to 100+ global clients across industries. We co-create 'Intelligent Enterprises' for our clients by helping them manage intelligence as an asset and transform those assets into insights across the value chain using domain expertise. We enable them to share those insights throughout the enterprise more effectively for enhanced overall performance.
•Triange Consult, the consulting arm, sets the right foundation for organizations' data, analytics, and AI needs. From the initial gap analysis and change management to governing standards and processes leading to an implementation roadmap, it helps companies define their journey to an insight-driven enterprise
•Triange NxT, the industry analytics-led platform suite, provides readily deployable assets and solutions by combining intelligent cloud-enabled data, analytics, and AI capabilities along with our partnerships with all major cloud providers and niche start-ups
•Triange CoE, the Center of Excellence, drives the end-to-end execution of industry-specific analytics programs powered by domain expertise, global delivery capabilities, functional knowledge, and technology best practices.
•WNS partnered with a leading U.K.-based global insurance major to transform its legacy data and analytics processes. This was done through a data-driven transformation journey by breaking silos in the processes, improving efficiency in decision-making, effective usage of data and building trust within the organization to adopt data-driven decision-making
•WNS helped a leading European retailer transform their retail media inventory utilization and engaged with the client to grow the revenue by co-creating transformational initiatives
•WNS enabled a leading North American regional bank in their data modernization journey by streamlining their master data management practices. This made wealth data platform in the cloud possible resulting in a 360-degree view of customers to drive cross-sell /up-sell and customer satisfaction KPIs
•WNS helped an APAC-based global Insurer with geographically disparate entities to set up a global data and analytics CoE to drive reusability, governance, and speed-to-market by leveraging best practices across the various entities.
There are five levers that businesses should use to extract total value from data. First, embrace change management – an important aspect many organizations miss, including culture change. Data analytics programs must be sponsored at the C-level, with the drive coming right from the CEO. Only then will there be a mindset change that accepts the use of data-led insights to efficiently drive decision-making across the organization.
Second, identify the right data monetization opportunities. Start with easy wins that will inspire confidence and form the base for launching bigger, more complex, and enterprise-wide initiatives. For instance, an insurance company wants to transform the claims process using analytical models. Pick one area with maximum potential for quick results, such as a loss severity model or a claims litigation model, instead of transforming the entire process. Insurance companies can realize immediate benefits by identifying missed recovery opportunities and predicting recovery opportunities proactively for new claims entering the system. Deploying the recovery models at FNOL helps in controlling the recovery leakages and with improved recovery rates as well as reduced cycle times due to early identification of such cases. This will help to establish credibility better and generate business buy-in.
Third, know what problems you want to solve with data. Start with the business problem and collect data to feed your model that will find answers, rather than just collecting data without any stated purpose and then wondering what to do with it. A leading fitness product company wanted to improve its customer activation. We executed a data modernization strategy involving migration and integration of the existing unified CRM data warehouse to the enterprise cloud. The project involved through data profiling and cleaning, ETL automation, data reconciliation, ensuring robust data security through encryption, especially for PII data, addressing incompatibility issues between databases, and so on. All of this was encompassed by data audit and governance to ensure data integrity. The modernization move enabled the client to achieve higher customer activations, better visibility into customer lifecycle behaviors, and faster time-to-market.
Fourth, fast-track technology maturity. Organizations must invest in advanced data management solutions hosted on the cloud, without which the downstream ability to process big data and act on it quickly will be lost.
Fifth, work with experts who have experience working with multiple use cases in your industry, so you do not have to reinvent the wheel and face the uphill task on your own.
Enterprises are having to continuously adapt to the changing landscape of business and technology. As per the Forrester survey commissioned by WNS, 73 percent of organizations have cited 'accelerating response to business and market changes as the top business priority and investment area for analytics. The industry is facing dramatic shifts today, with a need to have continuous intelligence to enable decision-making based on the latest data.
Continuous intelligence is enabled by real-time connectedness, intelligent operations, and cloud-based platforms. Real-time connectedness and decision-making help organizations to be reactive as well as proactive in responding to rapidly changing customer expectations and needs. Intelligent operations help businesses to rapidly test, learn and scale capabilities to adapt to the changing demands. Cloud-based platforms allow rapid deployments of capabilities and effectively are 'always-present' to enable decision-making in real-time.
We know that the move toward digital is an irreversible trend and data is an irreplaceable asset. The COVID-19 pandemic has enriched our data sources and presented us with an opportunity to better understand customer behavior and prepare ourselves for regulatory changes, geopolitical tensions, and black swan events. With the external environment expected to remain volatile, the need for data-driven insights for businesses will further intensify.
Organizations that want to remain adaptive will start embedding analytics in every business function — from improving the customer experience to eliminating operational inefficiencies and reducing risks.
The WNS-Forrester survey shows that 63 percent of decision-makers recognize that data and analytics are strategic enablers and 68 percent expect an increase in organizational spending on data and analytics in the next 12 months. They also see a more significant role for third-party service providers in the near term.
