AIM interacted with Rohit Tandon, senior vice president and business leader of Genpact’s Analytics and Research business. With over 25 years of leadership experience across the BPO, analytics, IT, consulting, digital and advertising sectors, he re-joins Genpact after a stint as Global Head of Analytics at HP for six years.
In his current capacity, he is focused on driving continued growth of Analytics business and development of digital and domain-led solutions to help Genpact’s client base harness big data and analytical insights.
Beginning his career as an entrepreneur, Rohit has worked for Accenture, GE and then moved to Genpact. Based in Palo Alto, California, he has a master’s degree in Computer Application (MCA) from the Institute of Management and Technology, Ghaziabad, is a computer science graduate from St. Stephens College, Delhi University and is a Certified Six Sigma Master Black Belt and a Certified Quality Leader in Six Sigma.
In this candid chat, he shares growth of analytics industry, analytics at Genpact, challenges in the industry, trends and much more.
AIMAnalytics India Magazine: How has been the growth of analytics industry in India since its inception? What are the major landmarks that you feel this industry has witnessed?
RTRohit Tandon- The analytics industry in India has seen prolific growth since the late 90s. It started locally with a few consulting firms working on areas like strategic cost reduction and supply chain optimization. The word “analytics” emerged around that time as a collective term to refer to efforts around optimization, forecasting and similar data- intensive pursuits across multiple industries.
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Genpact was one of the pioneers in this space as a third-party analytics provider for GE beginning in 1997. It started with the banking and financial services industry – which at 35% still forms the largest part of the analytics pie in India. It then expanded to the manufacturing space, specifically supply chain. Both industries were prime for analytics and India had by then developed enough resources to be able to setup and subsequently dominate what then got labeled as the “analytics industry.”
The industry got a shot in the arm as Dell, Citibank, and other major global players started their analytics builds out of India. The next explosion happened as key “pure-play” analytics firms like eValueserve, Mu Sigma, and Fractal jumped into the fray and helped further expand the reach as well as the talent build in the country.
We are also witnessing the next wave now where local organizations, like Flipkart, are investing heavily into building analytics as a core pillar for their business. This can only give a further boost to the industry.
AIM: How analytics plays a central role at Genpact? What have been the benefits of adopting analytics at your organization?
RT- Genpact’s focus has always been on solving real-world business problems and providing tangible impact to our clients. This has meant having a relentless focus on making a difference for the end problem of the client. Analytics on the data mined through our intimate knowledge of our customer and as well as various sources of external data has been a cornerstone of all that we do.
Genpact has long believed in measuring for improvement and our Lean Six Sigma heritage has made analytics an integral part of our business. We take pride in the impact we have provided our clients by weaving analytics seamlessly, making data-to-insight-to- action a continuous process. We measure the impact we deliver in terms of additional revenue, increased margins, cash released from operations, compliance, and customer experience enhancement.
In 2016 alone, we provided over $2 billion of measurable business impact to our clients.
AIM: How have analytics and big data transformed the way businesses are conducted today at Genpact?
RT- Analytics and big data have transformed the way our clients conduct their business and as a result, we have tried to proactively help our clients leverage all the great data and tools at their disposal. Through some of the examples highlighted below, we can discuss how Genpact uses analytics with its clients to transform their businesses.
In recent years with the explosion of social media, Internet of Things, and mobility, marketing and supply chain analytics have also started to grow at a tremendous pace.
The usage of advanced analytics for customer service, the wider adoption of IoT and now the rapid development of artificial intelligence (AI) and deep learning are all significant milestones in this journey.
AIM: Would you like to highlight a few use cases where Genpact has contributed significantly in digitization, artificial intelligence and analytics?
RT- At Genpact, we look at analytics as a means to solving business problems – not as an end in and of itself – so a solution for a client will have elements of analytics, digital technology, and process improvement. We always start with the question – what is the business problem we need to solve? For example, one of our clients, a leading airline, wanted to understand how they could reduce aircraft downtime due to parts that need maintenance. We then convert that into an analytics problem – a regular intercontinental aircraft these days produces more than a terabyte of data from the various sensors on the aircraft engine. We analyze the data and predict which of these parts will fail – thus generating an analytical solution. For this we use the latest cutting-edge technologies and analytical methods – but for the sake of using them to be ‘cool’ but constantly looking through the lens of solving the business problem. We then provide a business solution – in this case providing the airline with information on parts they should carry so that they could be replaced quickly in case of a failure – Thus generating business impact for the client.
Another example is that of a global pharmaceutical major that was struggling with an error-prone, manual pharmacovigilance process resulting in an annual processing fee of over $250 million. Through the dynamic capturing of safety data as well as an advanced analytics solution on an automated, AI-embedded pharmacovigilance platform, Genpact created over $23 million of business impact with over 75% improvement in accuracy.
AIM: Would you like to share some of the analytics solutions that you have worked on?
RT- Over time, Genpact has honed in on its strategic areas of focus based on client demands and inherent strengths. In our analytics business, we are continuing to build on our capabilities in key practices including risk management, supply chain analytics, IoT, and marketing and customer analytics. Our data science and governance platform, Intelligent Process Insights Engine (IPIE), forms the foundation of the solutions that we offer across industry verticals and business functions.
Let us take an example of a solution that we developed for a large consumer goods company that was trying to improve its bottom line as it struggled with its order management process.
On a typical day, the company’s order management analysts have to manage a high volume of messages. These could be frustrated buyers tracking shipments, an irate sales person at a new product presentation with a buyer only to have the meeting shortened because a promotional item had been cut from an order, or a third-party logistics company that missed the requested delivery date. There was no way to prioritize these and the order management analysts had to navigate through a maze of people, processes, and tools leading to unpredictable performance. Applying its Lean DigitalSM approach, Genpact employed design thinking to understand how the processes can be reimagined. The final solution used Natural Language Processing (NLP), cognitive analytics, and AI that made the process continuously smarter and error free. The solution provides a new way of working together—one that is smarter, faster, more efficient, and more effective. In addition to a potential direct reduction in order management costs to the tune of $100 million, due to a cut in transactional activities by up to 90%, and an estimated overall reduction in time by a third, the order management team can now focus on value- added activities that are assisted by the intelligent system.
AIM- What are the most significant challenges you face being at the forefront in analytics space?
RT- Some of the key challenges our clients face including increasing share of customer wallet, deriving relevant insights from data, and leveraging leading technology trends remain at the forefront of our strategy and innovation.
As an analytics organization, a key challenge is the availability of analytics talent. Everyone looks for that unique unicorn of a person who has data science skills, technology skills, and relevant industry domain knowledge to intelligently apply the analytics. Such talent is hard to find and therefore Genpact has proactively launched initiatives such as the Risk Academy that works with academic institutions to customize the curriculum and create industry-ready talent.
The Chief Science Office (CSO) at Genpact is a team of senior thought leaders available to our select client partners to engage in dialogue and exchange of ideas. The CSO works with internal and external organizations to drive industry, leading capabilities to accelerate capability maturity of clients. They also mentor the staff by providing them with advanced training in key areas through Genpact University (GenU).
Another key challenge is working with the clients to understand how best to utilize the data and analytics at their disposal to solve for their challenges. This is not just a process challenge, but a cultural and management barrier that we need to work with our clients to solve for.
AIM- What is your roadmap/plans for analytics at your company in the future?
RT- Genpact has probably the largest institutionalized single group of analytics experts in the world today. In line with our culture, we are continuously trying to industrialize this team. We are challenging everything we do for our clients and seeking ways to use machine learning, IT, intelligent platforms and advanced algorithms to eliminate a large part of the manual/human intervention required. This will not only allow us to use the ever-scare resources to focus on the insight-to-action part of the job, but also deliver huge savings and speed to our clients, leading to more market share and ROI for them.
At Genpact our key differentiator remains our deep domain knowledge of our clients’ businesses, so there is a continuous effort to enhance domain knowledge as well as build the next horizon of analytics capabilities.
AIM- How do you think ‘Analytics’ as an industry is evolving today? Could you tell us the most important contemporary trends that you see emerging in the present analytics space across the globe?
RT- Analytics as an industry is has long moved from ‘nice to have’ to an absolute necessity to remain competitive. There are a few key trends that we need to watch out for:
- Prescriptive analytics will grow: There is a need not just to predict trends but prescribe the action that needs to be taken. Gartner predicts that this market will grow to be $1 billion by 2019 with more companies adopting analytics as the basis of strategy development.
- Customization through behavior analytics: The amount companies spend on digital advertisements is expected to grow to as much as $77.37 billion in the U.S. alone next year, and understanding the audience is vital to ensuring that this is money well spent. Companies that are able to personalize are achieving higher conversion and lead acceptance rates. No more carpet bombing but rather a surgical strike on relevant customers.
- Pre-emptive analytics: No longer is analytics a post-mortem exercise with the aim of improving results in the future. Analytics is now done real time or pre-emptively in order to create positive impact.
- Creation of new jobs and roles: From the CEO to the shop floor workers – there will need to be retooling and reskilling to ensure that analytics is used to improve day-to-day operations. Apart from roles such as data scientists, new roles like ‘data engineers’ who are responsible for designing and managing the data architecture will emerge. Expect to see the disappearance of large teams who just spend their time on collating data and reporting the same outcomes.