Analytics India Magazine caught up with Sudhanshu Singh, senior vice president, Analytics and Research, at Genpact, who shared how the company, a pioneer in the analytics industry, has expanded its capabilities in digital technology with investment in machine learning and AI to drive more predictive insights for clients and help them speed up their digital transformation. In the freewheeling chat, Singh also talked about the company’s strong focus to build talent and industry ready talent pool.
Analytics India Magazine: Genpact has considerable thought leadership in the advanced analytics and is very agile in delivering impact to clients. Can you give us specific examples of driving transformation by bringing in the next generation of AI/ML models, digital tools or platform expertise?
Sudhanshu Singh: Genpact’s ongoing strategy is to drive digital-led innovation and digitally-enabled intelligent operations, and analytics has always been a core part of that. In the last several years, we’ve expanded our capabilities in digital technology, including investing in machine learning, artificial intelligence, and other areas that build our analytics strength to drive more predictive insights for our clients and help them speed up their digital transformation. Our business has grown over the past 20 years and ranked as leaders in the market by numerous prominent analysts.
We created a real-time lithology prediction for a large oil and gas exploration company by creating a single source of truth using data from sensors, spatial and GPS coordinates, weather services, seismic data, and various measuring devices; and then used artificial neural networks to extract complex predictive rules using historical data. ANNs were used to convert the inferencing by the geoscientist expert into a completely automated intelligent reasoning system. We have also worked for a large consumer electronics company and developed analytics solutions that generated $180 million in extra revenue for the client by doing two-stage market mix modelling and MILP optimisation with all marketing drivers.
Besides, we also carried out large-scale transformation for an airline major by collecting all in-flight and ground data; and then doing predictive and cognitive models. We helped them reduce their engine downtime reduction by 20%, resulting in $50 million of cost saving in three years. In the insurance sector, we helped an insurance client achieve 40% in additional revenue (in terms of premium) for the same number of underwriting resources by creating a machine learning-based solution to prioritise the numerous submissions they receive on daily basis. This solution also increased Bind Ratio (conversation) by 2.5 times, decreasing effort wasted from 70% to 25%.
AIM: While you have spoken about some real impactful stories, would you like to share an example where you have driven large-scale transformation for a client that has brought significant value?
Sudhanshu Singh: Quite a few examples. The first that comes to my mind is that of the engagement with an Aviation OEM. I was personally involved in this transformation journey, which spanned over 12+ years. This industry has unique business dynamics – they sell the product at cost or marginal profit and make money through aftermarket services. Genpact manages the client’s end-to-end aftermarket processes, including long-term deal pricing, failure forecasting, managing their remote monitoring and diagnosis centre, risk underwriting of the contract portfolio, warranty forecasting and management, pricing analytics, cost analytics, identification of cost reduction opportunities and margin analytics. Delivered as an Analytics Centre of Excellence, this engagement consists of 150+ analytics resources who help manage the profitability of this client’s aftermarket business and ensure the safety of the aircraft engines flying across the globe. Our analysis results in an average of $500 million to $750 million of business impact year over year.
Genpact provides commercial operations and analytics support to one of the largest market research companies in the consumer packaged goods and retail space. This engagement drives impact for the client across a wide cross-section of business-critical capability areas, with a major focus on data management, reporting, charting, insights generation, and analytics. The end-to-end data processing operational model is powered by various digital-based technologies like robotic process automation and machine learning.
Genpact led one of the biggest supply chain transformation projects for a CPG client. The objective was to redesign and then execute a new operating model with the process and digital transformation being the pivot that would enable 50% planning efficiency, increasing service levels and bringing in $200+ million worth of cost savings. This engagement covered 20+ geographies and involved 300+ distinct process types and 100+ technologies.
Genpact provides end-to-end commercial operations and analytics support to one of the top five pharmaceutical companies through the “office-of-the-future” concept. This unique engagement drives impact for the client across a wide cross-section of business-critical capability areas through end-to-end analytics services – reporting and visualisation, data analytics, advanced analytics, market research, and survey support. The operating model is managed by Genpact through a centralised PMO and an advanced workflow system. It is one of the largest engagements in the industry that operates under a ‘pay by use” based commercial model. This engagement has delivered a total impact of $120 million through cost reduction and released senior executive capacity over the last 10+ years through an “on-demand” COE model.
AIM: Can you tell us how Genpact is focussing on expanding the talent pool and contributing to curriculum development with university tie-ups across global talent locations?
Sudhanshu Singh: Being one of the pioneers in the analytics industry, Genpact recognised this challenge more than a decade back and incubated an ecosystem to identify, develop, and nurture analytics talent. If you look at the analytics leadership in the country, you would realise that most of them have been part of Genpact at some point in their careers. As we all know this industry is extremely dynamic. The landscape keeps evolving very frequently and so do we. We constantly re-look and evolve our talent strategy to address the need of this dynamic industry. We firmly believe that such a talent may not only come from the acquisition of new personnel for specific jobs but also from upskilling our existing workforce.
To this effect, we have a strong focus to build talent for a sustainable and scalable industry-ready talent pool. While we provide targeted interventions to enhance performance and/or link learning with career aspirations for our existing employees, we strongly believe in creating a strong talent pool through university on-campus programs and certifications as well.
Some of the notable programs currently running at Genpact are:
- Talent development and training is a key tenet of Genpact’s growth and is deeply embedded in our business model and culture. We are investing heavily in digital-focused training to significantly raise the “Digital Quotient” across our global employee base with a vision to build market relevant capabilities in the highly advanced analytical techniques and advisory space. This provides Genpacters with a glimpse into innovative digital technologies, applications of machine learning, artificial intelligence, and other key methodologies to solve business problems. It empowers all employees to drive competitive advantage for our clients.
- Analytics Academy: Under this initiative, we are keen on building Industry-Academia collaboration in the field of advanced analytics across industries. We have existing tie-ups with leading academic institutions in India and globally. Rutgers University, New Jersey, Institute of Management Technology, Ghaziabad, University of Calcutta, Jadavpur University, ICFAI Business School, Hyderabad are a few names with whom we have collaborated with for an on-campus program and research collaborations. In addition, we have partnerships with leading industry associations such as Global Association of Risk Professionals (GARP), Association of International Wealth Management of India (AIWMI) and Institute for Certification of Computing Professionals (ICCP) for certification programs.
In the academy initiatives, we collaborate with a few more academic institutes like BITS Pilani, Manipal Global, Amrita University, and Udacity to build generalised analytics/data science on-campus talent.
So far, we have trained 5,000+ students on campus, with 50+ guest lectures, internship opportunities to 200+ and job placements to 250+; Repeat deployments in 20+ clients through these Academy graduates in the past few years
- We build both domain and technical expertise in the required domain (90% of the current talent programs in the industry focus only on technical expertise). This ability for talent to understand both domain and analytics is challenging to cultivate, but a bilingual capability we have worked hard to build. This is important to our delivering results for our clients.
AIM: Let’s continue our discussion on the recruitment of your knowledge workers, typical selection methodology and what are the skill sets you look at?
Sudhanshu Singh: Given the globalisation of analytics services, and war for talent, we run robust programs to retain our highest performing talent and are ahead of the industry in terms of retention. We have constant touch points throughout the employee life cycle to nurture talent to retain employees and save cost. Some of the examples of the channels we use to attract analytics talent are:
- Participation in industry related seminars and conferences
- Technical workshops on partnered university campuses to familiarise students with the latest Analytical tools
- Annual internship programs for students to experience Analytics through real-time client problems
- Education@Work programs offering our employees the opportunities to learn while they earn
- Orchestrating customised skill development and reskilling initiatives in the area of AI through our Artificial Intelligence Development Program (AIDP).
AIM: Can you tell us which sector today is the biggest revenue contributor for service providers these days?
Sudhanshu Singh: The BFSI sector, one of the earliest adopters of analytics, has been seeing the highest growth overall. Some of the key growth drivers are — changing customer preferences, focusing on customer journeys, gathering data from the various touchpoints and channels, and ensuring the customer gets the best possible experience. Having said that, we see a lot of traction in other verticals, too. In fact, most of our clients come to us with the expectation that we will move them up the maturity curve to either keep up with competition or be the first in the industry to move there.
For example, in FMCG & Retail, we have seen a lot of traction for critical decision-making around pricing strategies, product promotion, sales and demand, digital marketing and marketing analytics. We have been providing advanced analytics solutions in the Sales and Marketing space for global Consumer Goods Manufacturers and Retailers. In Life Sciences, social media and digital marketing have been the big areas of focus. The increasing regulatory focus and challenges on profitability due to increasing R&D costs are causing companies to come to us to provide regulatory compliance reporting and marketing and sales support. Similarly, in the Manufacturing world, we have seen IoT analytics gain a lot of traction. It has been a sector which has had a lot of data coming in for a long period of time so the volume of historical data is huge and it is now that clients want to look at the effectiveness of the data and the insights it can deliver. The importance of predicting customer behaviour in the media and entertainment industry cannot be overstated.
The convergence of digital and analytics solutions in this space is what is driving a lot of growth.
AIM: Last year Genpact launched Genpact Cora its AI platform which integrates analytics and automation and AI engine? Can you share how it will be a differentiator for Genpact clients?
Sudhanshu Singh: Genpact Cora is a modular, AI-based platform that accelerates digital transformation at scale. The platform has capabilities in natural language understanding, conversational AI, computer vision, deep learning, big data, data science, data engineering, machine learning, RPA, ambient computing, dynamic workflow, and software-as-a-service. Genpact Cora allows companies to easily integrate advanced technologies, all delivered through a mature application program interface (API) and open, flexible architecture.
AIM: Tell us why sustained investment and leadership involvement is important for a faster analytics adoption
Sudhanshu Singh: While BI tools remain important, there is a far greater need for predictive and prescriptive analytics. Companies with large, detailed historical data, will need to enrich it with data from new sources such as smartphones, connected devices, sensors, etc. Enter technologies, such as data analytics, IOT, cloud and AI. In fact, by next year, we believe that 40% of data will be generated using search, natural-language query or voice, or will be auto-generated. This is a new area of investment for companies – to capture this data securely, ingest it within their system, integrate with legacy systems already in place, then get insights out of it and deliver it as queried. This is not a one-time expenditure, as you will have to keep pace with the increasing data sources. You will have to keep updating algorithms to ensure that there is no costly unlearning that must be done, due to data pollution.
An example of this in Genpact is, having algorithms cleansing data, spotting patterns in the background and in the foreground which is the user interface, you can have users ask questions using natural language. There are only a handful of companies, high on the analytics maturity curve, that are proactively using data to tease out insights and act upon it. The clear majority are still using analytics as a reactive measure, if at all. This is where a leader’s vision and focus come in. Analytics requires driving a data-focused culture within the enterprise and that can be done only when there is a leader who believes in the worth of analytics, focused on moving the organisation higher up the analytics maturity curve and is able to convince the rest of the organisation about its importance.
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