From interactive chatbots to digital assistants like Alexa and Google Assistant, consumers have been using Artificial Intelligence since before the COVID-19 pandemic. Business leaders, too, were moving towards these cutting-edge technologies but the pandemic accelerated this digital transition. As the challenges presented by the global lockdown grew more severe, organizations have fast-tracked digital transformation. AI and analytics capabilities that would have once taken months or even years to develop were rolled out in a matter of weeks.
To understand how will power the future of organizations in the future, Ankush Gadi, Director – Data Management & Analytics at CRISIL Limited, spoke with experts across industries at the latest ET Live Roundtable, Data Sessions, powered by Qlik.
Analytics for better decision making
Analytics has become an essential driver of innovation, optimization, and competitive edge in every industry. Manoj Kumar, Lead – Digital Transformation and Cluster Head (Senior Vice President) – Oncology, Transplant, and Plasma at Intas Pharmaceuticals Ltd., believes that the healthcare sector is no exception. He said that, while the industry has always worked with data, it did not actively use it much. Things are changing fast, however. “The world is moving towards complete disease and patient management. Every patient is Googling health data today to try to prevent diseases. Players in the medical, pharmaceutical, and healthcare spaces are already evolving with this changing dynamic,” he said.
According to Mr. Kumar, in the healthcare system, data analytics for disease management is likely to evolve in four areas: the descriptive understanding of diseases, their diagnosis, predictive analysis to determine patients’ vulnerability to a particular disease, and prescriptive treatment. He believes that such an analytics-based approach to diseases and patient management will make for more effective and efficient healthcare processes. “Prescriptive healthcare is not just about healthcare professionals prescribing medicines. It is now about a patient who, based on analytics, is collaborating with doctors to determine whether they need more aggressive treatment, such as a transplant or surgery, or just medication,” he said.
Vijay Aggarwal, CTO at BharatPe, similarly extolled the virtues of analytics in the BFSI space, explaining how new age fintech players are taking innovative routes to include small merchants in the ambit of digital financial inclusion. Most banks rely on traditional data points such as income statements to assess creditworthiness. The process, however, leaves out many creditworthy individuals and businesses. This is the need-gap that, according to Mr. Aggarwal, fintech companies such as BharatPe are addressing by leveraging analytics.
“We enable lending to a lot of merchants, who otherwise do not qualify for bank loans, by first enabling their daily transactions through UPI before using the data generated to assess their creditworthiness. So, data forms the bedrock of our business model,” he said, before adding how the quality of the data also plays a vital role in deciding end-consumer offerings. “Through our app, we receive a lot of data around transactions, merchants’ behavior, products they interact with and their preferences. All this information goes as input to our AI algorithms. This data helps us decide the right kind of loan amount and installments. We also use data to enable new kinds of financial services for merchants, including loans, insurance, and wealth management, tailoring our platform offerings for every merchant.”
Armstrong Mejilla, Director, APAC at Qlik, said that an important trend in data-driven decision making was the increased buy-in from the entire business — and not just the IT department — in establishing the practice of data analytics, business intelligence, and everything in between. “It’s no longer just the CIOs, even CEOs today are taking a more aggressive stance when it comes to data. They are more prominently involved in identifying opportunities to use data and making decisions using analytics. This stage of companies building mature practices around leveraging data is being driven around the awareness of being data literate,” he said.
The growing focus on data will also require the entire workforce to be more data literate. “From the most junior level employee to VPs and beyond, everyone must be able to read, analyse, and communicate with data. It is paramount that non-technical people are comfortable enough with data to make decisions based on it,” he added.
Not just small steps, large transformations
Talking about the agriculture and food ingredients industry, Thiagaraja Manikandan, President and Global CIO at Olam International, explained that the only way for the industry to satiate future global food demand would be through data-driven technological interventions. “For us, digital is not just digital, it is the entire IT ecosystem. Typically, many organizations look for one or two digital strategies, but we set out with the tall ambition of transforming the entire industry. We planned our digital transformation from the farm to the customer and digitized everything in between.”
The approach has reaped rich dividends for Olam. “On the farmers’ side, we have four digital platforms on which 4 million farmers are already enrolled and transacting with us. On the other side of the value chain — the customers’ side — we do millions of dollars’ worth of sales across the globe through e-commerce, so it has been a very successful venture for us. We have already seen a huge increase in revenues since last year and we are expecting further growth this year. We are now creating digitized solutions to completely empower Olam with smart factories, smart farms, precision farming, and digitizing warehouses,” he said.
For Thompson P Gnanam, Chief Digital Business Officer at Conneqt Business Solutions, the convergence of data science and analytics practices with AI, ML, and domain knowledge has been the most important change. “Data science is no longer data science, it is business science,” he said. “In the post-Covid era, demand generation is a huge issue as all of us are trying to come out of a recession. How do we generate demand when all of us have huge constraints on our P&Ls and budgets? All our customers are going through this problem. So, if I throw in a contact center AI, integrate it with omnichannel capabilities, and then throw in data science and analytics, it transforms into a scenario where the system has clarity as to whom to call, when to call, what to say, and what channel to use.”
“We can also get smart recommendations about, for instance, whether a humanoid or a human being should engage with the end-user, or when it would be better for the humanoid to transfer the case to a human being. All these processes get automated and, at the center of it all, is the human being. The employee who is engaging with the customer is now a ‘super associate’ because they are empowered with this technology. Now, they have bots that are assisting them on a live conversation, with dynamic scripts based on hyper-personalization of what the customer prefers. Similarly, NLP and AI-powered bots can raise quality assurance to a different level,” he said.
According to Armstrong Mejilla, Qlik is in the middle of building a solution around such active intelligence. “We have seen organizations that have decision makers who cannot be bothered to log in to a portal to look at a report and then make decisions. Now, we are trying to build a continuous state of intelligence and automate the process such that, if there is a development that can affect business decision making, it is captured and put in a data source automatically. It can then be processed into a report, dashboard, text message or even a chat to someone who needs that information immediately. We are not automating a big set of queries. We are trying to automate all the processes needed in between to make sure everyone can make decisions where and when they need the data.”
Data-driven personalization is another important strategy in a business’ arsenal. Thiagaraja Manikandan spoke about the extent of personalization offered at Olam. “In our sustainability and flexibility product, we have been able to personalize every contract to explain where the material has come from, who the farmer is, what finance was employed, if the product is devoid of child labor, what kind of fertilizer has been used, the kind of impact on global warming, and carbon emissions. Everything has been bundled and provided to individual customers. Without personalization, our entire digital offering will be a complete failure,” he said.
For businesses that leveraged technology to combat the pandemic impact, the resulting digital transformation will power growth and revenue for decades to come. Advanced analytics capabilities can not only help them identify potential supply chain disruptions but also provide support services to workers at risk and determine the efficacy of crisis intervention strategies. As companies look to boost efficiency and revenues, it will be crucial to not just collect and enrich data, but also to use it for insight and make AI-driven personalization core to their operations.
