Analytics has often been run as a series of periodic and siloed exercises. However, to respond to their customers in the smartest, fastest, most efficient manner, WNS perceives that organizations increasingly need to run their analytics always-on, in almost real-time, and on an enterprise rather than siloed basis. To do this and become ‘insights-led enterprises’, organizations’ analytics need to be supported by a suitable underlying enterprise data ecosystem, typically cloud-based.

WNS has had a strong Data & Analytics practice for many years. In the past, the scope of WNS’ analytics-led engagements was somewhat limited and frequently priced on an FTE basis. WNS now seeks to significantly broaden the scope, powered by data management, Artificial Intelligence (AI), and cloud, and aggressively incorporate alternative and outcome-based pricing models. WNS has now repositioned to work more upstream on client engagements and participate in larger data lake transformations, rebranding its Data & Analytics practice as WNS Triange.

Repositioning and Expanding Horizons as an ‘End-to-End Industry Analytics’ Player

This repositioning aims to establish WNS with a clear identity as ‘an end-to-end industry analytics player’ delivering outcomes and not just personnel and assisting the practice in targeting transformational activity for functional business heads, CDOs, CTOs, and CDOs outside of WNS BPS engagements. It also assists the Data & Analytics practice in establishing a stronger identity within WNS and attracting talent in a challenging talent market.

WNS is also aiming to change the scope of engagements from running individual use case analytics in silos to assisting organizations with the broader management of their underlying data ecosystems and rolling out analytics on an enterprise basis at scale.

Accordingly, WNS Triange is building data & analytics capability on the cloud, together with data/AI Ops capability to run large-scale data operations and governance at scale. These capabilities are supported by an Analytics CoE that brings together “best practices” on cloud, data, and AI, together with associated governance mechanisms and domain expertise.

Investing in High-End consulting and Hyperscaler-Certified IP

WNS Triange currently has ~4,500 personnel and is being restructured into three components:

• Triange Consult. WNS Triange is placing much greater emphasis on up-front consulting than previously and is increasingly recruiting and locating senior consultants onshore operating from its design labs. WNS has also built framework assets in support of Triange Consult in the past two years, covering areas such as analytics and AI strategy, data strategy, and data quality & governance strategy, together with domain-specific consulting
• Triange NxT. WNS continues to focus on the creation of accelerators. These include SKENSE, Unified Analytics Platform, Insurance Analytics in a BOX, Emerging Brands and Trends, InsighTRAC, and Datazone.ai
• Triange CoE, for analytics project and service implementation.

WNS has invested in platforms to address intelligent cloud data ops as well as in analytics AI models. These Triange NxT platforms assist WNS in delivering speed-to-execution and speed-to-value since these elements are pre-built models with tested connectors to third-party data and are being cloud-certified with the necessary governance and built-in security protocols.

For example, the Triange NXT Insurance Analytics Platform provides pre-trained AI and non-AI based analytics models in support of insurance analytics related to claims, pricing, underwriting, fraud, customer marketing, and service & retention. These models are underpinned by APIs to leading insurance platforms, connectors with workflow systems, ML Ops, and what-if analyses. WNS also incorporates platforms from partnerships with start-ups and specialized data providers as part of its prepackaged solutions.

Key WNS platforms within Triange NxT include Skense for data extraction and contextualization, Insurance Analytics Platform, InsighTRAC for procurement insights, and SocioSEER, a social media analytics platform. WNS is currently finalizing the certification of each platform on AWS and Azure and making them available in cloud marketplaces.

SKENSE platform based solutions have been built to address a range of use cases across finance & accounting, customer interaction services, legal services and procurement, as well as banking & financial services, shipping & logistics, healthcare, and insurance.

Increasing Use of Co-Innovation and Non-FTE Pricing Models

WNS Triange revenues have grown ~25% over the past year, and WNS is increasing its use of co-innovation and non-FTE pricing models.

For example, WNS has deployed its AI/ML platform to capture the quality control data from the various plants of an FMCG company, create summaries, change the data into a suitable format for generating insights, and return the summary notes and insights to the FMCG company’s data lake.

This resulted in an 82% reduction in processing cost per document compared to what had previously been a very manual process.

WNS undertook the development of this IP largely at its own expense and now owns it, with the client paying some elements of the development fee and a licensing fee. In addition, WNS will pay the initial client a percentage of the revenue if this IP is sold to other CPG companies.

WNS helped an Insurance client automate the process of identifying subrogation opportunities in the Claims processing workflow. WNS used MLOps frameworks to identify recovery opportunities based on historical data and predict opportunities in the current transactional data with higher chances of recovery. This helped the client in improving the recovery rates by multiple percentage points.

Elsewhere, WNS is working with a media client to transform the enterprise into a digital media agency and reinvent its traditional approach to processes such as media planning and customer segmentation. Here, WNS is assisting the company with multiple data & analytics initiatives. In some cases, this involves the Triange Consult practice, in others provision of platforms, and in others, the application of the Triange CoE approach.

For example, WNS Triange Consult is helping the company establish an appropriate cloud architecture and organize its data appropriately, establish how to run machine learning ops, and identify the appropriate design for a complete reporting center.

The company’s data has traditionally been paper-based, so WNS NxT is using platforms to digitize its data and provide insights for real-time decision-making. WNS is also helping the company set up its training infrastructure for data & analytics.

This repositioning is underlined by systemic structural changes that will enable WNS to adopt a more consultative and enterprise-scale approach to analytics. While many organizations will still address analytics on a siloed case-by-case basis, and these use cases remain important, WNS now has the structure to go beyond individual use cases, further augmenting its traditional strengths in domain-based analytics and assisting organizations in adopting more systematic approaches to establishing and scaling their enterprise analytics infrastructures end-to-end with enterprise-level data, analytics, and AI.