Today, the Indian enterprises is looking for experts to understand the power of data in order to solve the numerous business challenges. With Covid-19, disruptions have emerged in many ways across the various industry segments around the globe. Enterprises have also had to rapidly adapt and change.
Satish HC, EVP – Head Global Services – Data and Analytics, Infosys for Data and Analytics, tells us more. Excerpts from an interview.
DQ: What are the challenges faced by organizations in implementing a data analytics strategy?
Satish HC: Modernization, industrialization, building agility,democratization of data/AI, data quality, and access to talent are some of the key challenges that enterprises face. Organizations also struggle to “frame the right problem to solve”. They need experts who understand the power of data to solve the business problems and drive data led transformation for the enterprise.
Infosys is solving these challenges and accelerating the time-to-market for such solutions through deep investment in service R&D, frameworks, assets, and an ecosystem of partners like enterprise ISVs, startups, and academia, unlocking collective capability.
Alongside the definition of strategy, that is in line with the organization’s core, driving effective change management, cultural change is critical, and Infosys brings about a structured mechanism and frameworks to implementation.
DQ: How have data and analytics apps revolutionized industries during pandemic?
Satish HC: Covid-19 brought disruptions in unprecedented ways around the globe and across all industry segments.
Enterprises have realized their inability to respond in real time to mitigate losses arising out of demand, supply disruptions, preserve working capital, provide high-quality service to clients,and monetize new opportunities to grow.
Enterprises have had to develop the ability to rapidly change or adapt in response to changes in the market.
A sound data and analytics strategy can help address thesechallenges faced by enterprises during the pandemic crisis in real-time, ensure enterprise agility to adapt and respond to changes in the market, de-risk business models, draw enterpriseand sector level intelligence to drive data-led decisions thus enabling resilience for the enterprise and economy.
Organizational Agility can help the enterprise react before-time/in-time to crisis, to emergence of new competitors, to evolving new industry-changing technologies, or sudden shifts in overall market conditions.
Here are some examples of how Infosys helped clients to adapt to the new normal:
DQ: What is the power of the confluence of technologies such as cloud, IoT, AI?
Satish HC: We are witnessing a new era of digital acceleration powered by the confluence of Cloud, AI, IoT, 5G, Edge computing, AR/VR and stimulated by the need for resilience during pandemic. This is providing the unprecedented opportunities for business innovation across all core business functions – customer experience, efficient operations, newer revenue opportunities, automated risk management, etc.
Enterprises are striving to become digital and data natives, and are therefore, transitioning to data economy that enables them to explore newer revenue opportunities connecting the data value chain across their competitors, suppliers, adjacent industries.
The pivot for managing these developments will be cloud, data and AI. They are complementary and interlinked – AI is most effective with cloud computing; IoT generated data will need cloud for storage, processing and edge computing.
Enterprises need to navigate the complexity of myriad choices of tools around digital, Data, AI into their technology stack and integration of these technologies in their landscape, and optimally manage their Opex. Infosys Data Analytics is well positioned to help our customers define their strategy to adopt these disruptions and deliver value.
DQ: How are enterprises reworking themselves in the new normal?
Satish HC: The crisis was a wake-up call for enterprises to accelerate digital and there is a pronounced need to create a ‘Digitized Ecosystem’. The use of digital technologies has increased multi-fold. We have seen firms enhancing their capabilities to transact with customers and vendors alike through multiple channels, moving away from staying bounded within traditional channels.
From CPG firms, automobile firms, to insurance firms, across the board a digital way of conducting business became a necessity and is now here to stay. This transition necessitated a seamless experience between physical and digital worlds.
CPG firms realised a direct to customer channel was important at this stage, today individuals can place orders directly with some CPG firms and receive a home delivery of products. These firms leverage existing physical infrastructure to enable this delivery. Today, most businesses have become phygital, or are on their way to become phygital in this manner.
Enterprises have had to enable their workforce to WFH, and enable infrastructure and connectivity. Data analytics is playing a crucial role in daily operations be it real time demand sensing or new ways of selling or making key business decisions like stores opening aided by data science models. Enterprises should have the ability to sense, respond in real time and become sentient.
Another area of focus for the enterprise is employee wellness during this crisis. Enterprises are finding innovative ways to use collaboration technologies to engage their employees in the new normal. At Infosys, we had an existing backbone infrastructure,which has now been put to full use to ensure no dip in productivity. We have further added digital employee engagement programs, events, contests etc. to keep the team motivation high.
DQ: Are they also reimagining their business models, such as data-driven insights?
Satish HC: The digital economy is leading to a data economy. Data is the new capital pivoting the next generation disruption of industry structure, transformation of economy and society. Enterprises are relooking at their business models to become platforms for their business segment enhancing interoperability, creating new efficiencies in their ecosystem along with defining new leadership role for them, e.g., healthcare, automobile, retail etc.
This extends to the ability to re-imagine and bring zero latency in key business processes, e.g., providing touchless claims, augmenting doctors, nurses and health workers with real time insights and information of customers, digital notification around symptoms of pandemic to avoid overloading of customer calls, automated ordering of stock based on demand and leverage the optimal supply chain considering various factors, etc.
As enterprise systems grow in complexity, data is expanding rapidly from on-premise systems, cloud systems, clickstream data, social media and third-party data aggregators. Further, data consumption is growing exponentially with multiple consumers, platforms, analytical needs driving innovation in the way data is being consumed, shared, and monetized.
The Infosys Connected Data Economy, with trusted partners, addresses the need for a seamless mechanism bringing together data providers, data aggregators and data consumers with effective sharing of data and secure consumption with data governance in an efficient manner.
Some examples of the work we are doing for our clients to power the data economy are listed below:
• For manufacturing enterprises, we are exploring new customer segments to understand how new offerings can be best positioned to customers. We are increasing client engagement to better understand their needs as they adapt to a post Covid-19 world through fine-tuned social listening analytics tools. We are also trying to bring further digitalization of sales processes to enhance online sales (online vs. branch strategy) and increase attractiveness of customer loyalty programs to stabilize demand.
• Direct Policy Purchase – At present, direct-to-consumer channels struggle with sequential operations and inability to meet with scale, complexity and personalization of quotes and subsequent follow-ups. Through persona-based approach, with the help of micro-bots on knowledge graphs and experience configurator, enterprises can handle simultaneously ‘000s of personalized quotes using wide array of products and follow-up conversations.
DQ: Elaborate on how are you building hyper personalized solutions across retail, CPG, insurance, financial services, etc.?
Satish HC: Infosys is taking a cognitive-first approach for hyper personalization that leverages power of AI, edge intelligence, and industry domain ontology to harvest knowledge from all the data (structured, semi-structured, content and external), senses the customer’s intent/purpose, contextualizes the response that is relevant, and activates intelligence across phygital (physical/digital) channels in an autonomous fashion.
The two key assets that we have in this space are Infosys Genome Solution and Infosys Digital Brain. We have built ontologies across multiple industry domains – retail/CPG, healthcare, life sciences, insurance, automotive, manufacturing, energy and utilities, etc., and the AI agent libraries in line with the various industry ontologies for various personas/processes as applicable.
With the Infosys Genome Solution and Infosys Digital Brain, we have enabled a large CPG major that was struggling with a fragmented consumer journey (> 40% bounce rate) for their 40+ brands across channels.
With cognitive-first approach we harvested knowledge from content, touch points — internal and external data, realized Consumer Taste Graph leveraging AI that provides mind map of consumer intent, purpose with all their brands/recipes and leveraged the same to sense consumer signal, generated a contextual response in terms of content /brand/product/recipes and orchestrated the consumer journey across their brand sites through hyper-personalized, real-time response. This has decreased the bounce rate by 23+% and increased the consumer engagement by 80%.
DQ: What is the role of hyperscalers in amplifying the use of AI?
Satish HC: Hyperscalers play a crucial role in industrializing AI in an enterprise. They have rich AI capabilities embedded in their stack and powerful front-end tools to enable agile development of AI and analytics. For example, Google uses Tensorflow, Azure uses AzureML and Data bricks, and so on.
Hyperscalers also support AI engineering with third-party data science tools. We have tied up with niche partners like DataIku, databricks, Trifacta, etc., to offer AI and advanced analytics solutions on top of the hyperscaler stack.
DQ: What is the impact of industrialized data and analytics on automation?
Satish HC: Leveraging data analytics, we can enhance cognitive and real-time quotient of automation so that we can evolve towards autonomous automation. With clients on board, digital acceleration and industrialization of data and analytics, it is imperative to leverage this data to become more context aware, real time and intelligent.
At Infosys data and analytics practice, we leverage automation as core across all our levers from technology, IP solutions, and service delivery.
We approach automation with a structured framework and track progressive automation maturity to ensure continuous improvement in our services. We have defined automation maturities across three levels from Task based to Assistive to Autonomous automations. Within each level, we leverage specific automation design patterns based on the lifecycle of engineering thus ensuring there is consistency and reliability.
We are constantly enabling each of our clients navigate through this automation maturity with an incremental approach which gives an effective and future ready foundation to the data powered enterprise.
For a multinational CPG client, Infosys is delivering machine–first delivery to help elevate their customer experience and freeing up per capita for modern technology adoptions. Infosys is transforming their data platform and operations to be sentient with cognitive capabilities, powered by Digital Brain. This has enabled data and intelligence to positively influence the actions of requestors and fulfillers, through the pro-active nudges and contextual visuals.
Enabled with capabilities like real-time prediction of ETA for resolution, pro–active identification and creation of problem records, autonomous linking of problem records with historical incident data and community expert tagging for topics for faster and effective resolutions. We are helping them deliver and realize more from their data investments with automation and modern technology adoptions.