Schedule

Data-driven decision making is increasingly becoming the norm rather than the exception. However, as decision makers, or enablers of decision making, our laser focus on outcomes sometimes leads us to ignore what is not immediately beneficial, or immediately obvious. In this talk, we explore the theme of looking beyond the obvious in data-driven business decision making, through its various manifestations: trading off between exploiting what appears to be the best option and exploring the less desirable ones, understanding the impact of a series of actions rather than a single action, finding a balance between structured decision making and ad hoc tactical adjustments etc.

There is something every business can do about the weather, a powerful disruptor. Today, newscasters, pilots, energy traders, insurance agents, state employees, retail managers and more can gather insight into weather’s impact on their businesses, helping them make smarter decisions to improve safety, reduce costs and drive revenue. In our recent survey of 1000 c-suite executives globally, 93% believe that improved weather insights can positively impact annual revenue growth. An effective weather integration strategy can serve as the foundation for enterprise wide analytics applications. Join us to hear how we uncover the business value of weather to power new possibilities of decision-making.

Today Artificial Intelligence (AI) and Machine Learning (ML) is possibly the most widely discussed technology trend which is seen as a new age invention to solve important business and social problems. In most cases, machine intelligence is being used as a supplement to human decision making, thereby “augmenting” human intelligence. In this context Augmented Intelligence (the other AI) is proving to be more critical rather than Artificial Intelligence. Augmented Intelligence is also critical in considering the real-life constraints in leveraging machine intelligence within business context. Business leaders look at Augmented Intelligence (AI) as the next competitive edge to drive incremental top-line or bottom-line impact in their organisations. However, the path from “Data” to “Dollars” (business benefits) is time- intensive and full of challenges. Like an iceberg, the steps that require significant time and effort are mostly hidden under the water. Hence, the process of generating “Dollars” from “Data” appears exceptionally slow and frustrating to most business leaders. What if, we could navigate the entire data-to-dollar path in an agile manner? What if, we could get a data lake up and running in less than 15 days and create data marts in less than 30 days and have models implemented within 45 days? And last but not the least what if we could empower the business managers to do all the above themselves? The Actify Data Labs session will outline the agile approach and the tools needed for generating “Dollars” from “Data” at an extremely fast pace. And illustrate the same with a case study for consumer businesses within the Indian context.

Analytics of the Millennials <> Analytics for the Millennials <> Analytics by the Millennials The generation gap between analytics consumers and analytics providers are yawning. In the era of digital consumerism, every organisation has or plans to have an Analytics Centre of Excellence. Big Data is becoming a hygiene and no longer a competitive advantage. With more computing power and real time streaming, has analytics become omni present? AI, ML and DL are here to stay. But in the midst of Asimov’s RPA revolution – where is the need for human intervention in designing solutions? The NextGen analytics is all about aesthetics, and values - and not just law of gravity – but laws of tide. This session is to bring in the hues and shape of things to come in analytics.

How do organizations become more data driven in their processes? Through the behavior of managers / leaders at various levels. But as data science becomes more advanced, how do they stay abreast?

AI is soon becoming as critical as electricity. However, making AI and Data Science real for enterprises is not so easy. In this talk, we will discuss how to make AI real for enterprises with actual case studies. We will discuss what is the value that Data Science brings to for investors and operating teams and how to deploy AI modules in real world enterprises. We will discuss case studies of live deployments in diverse sectors like Hotels, Finance, Real Estate. Logistics and Automotive.

With an experience of over 25 years in analytics, Shailendra will showcase how the operational data and experience data can help an organisations to create an unmatched customer experience and significantly increase revenue and reduce operational costs. The bestselling author of the book Making Money Out of Data, will unveil the complex equation required by businesses to connect the dots.

1.) Future of AI for different sectors ( based on panel composition) 2.) Sensitizing leadership to the benefits and limitations of AI 3.) Getting the workforce to view AI as an enabler than a threat 4.) Creating a culture of experimentation along with a data-first approach 5.) Pro-actively building systems to support the implementation of AI at scale 6.) Building out talent - upskill existing resources & hiring external talent with a focus on the gap in talent and technology across India, US & China.