Expert Talks with Maavrus | Analytics, AI and Transformation

Maavrus
Expert Talks with Maavrus | Analytics, AI and Transformation

Welcome to the "Expert Talks with Maavrus" podcast. This show is dedicated to exploring the cutting-edge of technology and its impact on the way we live and work. Each episode, we'll bring you interviews with experts in the field of analytics, artificial intelligence, and business transformation. We'll dive into real-world examples of how these technologies are being used to drive innovation and improve processes across industries. From big data and machine learning to natural language processing and computer vision, we'll cover the latest advancements and trends in the field. Join us

  1. 02/15/2024

    In conversation with Bharathram Ramakrishnan, Global Head of Data Science & AI, Novartis

    “ If you are in a certain domain for a very long time you become more of a subject matter expert and depth-oriented person rather than becoming somebody who can think beyond the traditional way of approaching things. For AI & Analytics which is more of a horizontal function, it works well if you come with a cross-industry experience. If you see many of the successful leaders in the analytics space they don't come from a single domain and are generally able to set up teams with the curiosity to learn about the new domain. The cross-pollination of ideas across industries is what sets them up for success” – Excerpt from the interview with Bharathram Ramakrishnan   Today is Episode 21 of the Interview series on Expert-Talks, with Thought Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Bharathram Ramakrishnan ( Bharath ), Global Head of Data Science and AI, at Novartis.  Before Novartis, Bharath was the Global Head of Data Science and Analytics at Dupont. He also held  Analytics leadership roles at Shell, TCS and Mu Sigma. Bharath holds a PhD in AI, an MBA in Systems and a Bachelor in Electronics Engineering.   We are listing below a few key points from the interview :   ·         Bharath highlights the significance of understanding domain-specific challenges and being able to communicate effectively with business stakeholders. He emphasizes the need for collaboration within analytics teams and across departments to achieve success in delivering analytics solutions. ·         Key functional areas for business analytics in Pharma include operations, research, and distribution, each requiring high accuracy and reliability. ·         In the pharmaceutical industry, there's a push for faster delivery of impactful analytics, necessitating innovative approaches like synthetic data to bypass red tape. ·         Generative AI is predominantly used in research and development within Pharma, aiding in summarizing large volumes of documents for decision-making, while explainable AI remains crucial for ensuring safety, reliability, and compliance within the industry. ·         The interview touches upon the shift towards freelance and remote work arrangements in the industry, necessitating adaptability from both organizations and employees. ·         The top 3 areas an aspiring analytics professional needs to develop, are curiosity about domain challenges; effective communication with business stakeholders; and a collaborative work approach    You can watch/listen to the interview on our Website, YouTube, Apple, Amazon Music and Spotify podcasts on the links given in the comments section below.  Please do share your comments and subscribe/follow us on @maavrus on LinkedIn, Facebook and Twitter.

    2 min
  2. 01/08/2024

    In conversation with Bhargab Dutta, Chief Digital Officer, Century Plyboards

    The point is, how can we create an ancillary ecosystem based on Generative AI capabilities? So that is where the crux for people like me will be because I am not going to focus on creating a chat GPT backend engine. My focus would be on how I can use them for my business needs, right? How can I improve my product description based on an understanding of Google Search parameters, to help improve my organic search ranking, and hence improve my Marketing RoI – Excerpt from the interview with Bhargab Dutta   Today is Episode 20 of the Interview series on Expert-Talks, with Thought Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Bhargab Dutta, Chief Digital Officer at Century Plybvoards.  Before Century Plyboards, Bhargab was Director of Digital & Analytics CoE at Colgate Palmolive India Ltd. He has also held leadership roles in Digital & Analytics at Aditya Birla Group, General Mills and Honeywell. He is recognised as among the Top 10 Chief Digital Officers in India by CEO Insights Magazine and Top 100 AI leaders by 3AI.   We are listing below a few key points from the interview :   Bhargab emphasizes the importance of data-driven decision-making, incremental growth, and cost-saving opportunities for organizations. Domain expertise plays a crucial role in articulating solutions and identifying the right data points. Analytics leaders should tailor their analytics journey & approach based on an organization's technology & Data maturity. Situational awareness is key in analytics and transformation journeys, allowing for immediate course correction and redefining solutions. New technologies, such as neurovision-based analytics , geospatial analytics and AI, are gaining ground in understanding end consumers and their buying patterns in the FMCG industry. Advice for Aspiring Data Scientists and Digital Professionals- Invest at least 5 years in one domain for depth of industry exposure. Focus on basics, especially statistics, before pursuing advanced topics like machine learning. Emphasize defining the problem statement before jumping into solution mode.    You can watch/listen to the interview on our Website, YouTube, Apple, Amazon Music and Spotify podcasts on the links given in the comments section below.  Please do share your comments and subscribe/follow us on @maavrus on LinkedIn, Facebook and Twitter.

    50 min
  3. 12/27/2023

    In conversation with Saurabh Agrawal, Founder & CEO, DAIOM | Ep 19

    Attribution has been word talked about and made more complicated as well. Thanks to a lot of the analytics products and companies who have come through, I would say there is an inherent bias to let people not properly attribute. It is better to focus on the efficiency & effectiveness of each channel. By getting a very strong UTM framework implemented at each channel, you will be able to tell for eg that 50% of my traffic comes from organic, 30% comes from Google, and Facebook, 10-20% comes from CRM, and thereby help maximise the effectiveness of each channel for eg in performance marketing can I reduce that bidding on my keyword so that I can let the organic traffic flow? – Excerpt from the interview with Saurabh Agrawal.   Today is Episode 19 of the Interview series on Expert-Talks, with Thought Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Saurabh Agrawal, Founder & CEO of DAIOM ( Data and AI in OmniChannel ).  Before DAIOM, Saurabh was SVP of Analytics and Growth Marketing at LENSKART. He has also held leadership roles in Digital, AI and Analytics at MothersonSUMI,  Tata Insights & Quants and American Express. Saurabh speaks frequently at industry forums on leveraging marketing analytics to enable profitable business growth.   We are listing below a few key points from the interview :   The key areas where analytics plays a role in D2C brands are growth marketing, customer experience, and financial profitability. These areas help drive business growth and increase customer engagement.   D2C brands are expanding into physical stores to bridge the gap between online and offline customer experiences. This allows customers to overcome challenges like size and product quality, and helps build brand identity and trust.   Digital native brands have an advantage in terms of tech agility and nimbleness compared to traditional brick and mortar retailers. Process digitization and consistent store experiences are essential in ensuring a seamless customer journey.   Data availability and quality are challenges in the omnichannel world. Customer identity management and unifying data from different tech systems are crucial for effective analytics and personalized customer experiences.   Influencer marketing can be a cost-effective way for brands to reach their target audience. It is important to choose the right influencers based on their audience, engagement, and relevance to the brand, and to measure the impact of influencer campaigns using attribution and analytics.   Balancing digital marketing spend across different channels is essential for reaching the right audience. While traditional media can still be effective for brand recall, digital channels offer more targeted and measurable results. Consistent and measurable efforts in organic and influencer marketing can lead to a higher ROI.    You can watch/listen to the interview on our Website, YouTube, Apple, Amazon Music and Spotify podcasts on the links below.  Please do share your comments and subscribe/follow us on @maavrus on LinkedIn, Facebook and Twitter.

    4 min
  4. 12/19/2023

    In conversation with Mathangi Sri Ramachandran, Chief Data Officer, YUBI | 18

    For a long time in the industry, I think we made the mistake of going behind people who were experts in let's say certain set of algorithms; who understood the math very well, but they were not able to convert that mathematical problem or match the mathematical problem to a business context. So without context, they are just algorithms and numbers and libraries and codes which may or may not solve the actual business problem– Excerpt from the interview with Mathangi Sri Ramachandran.  Today is Episode 18 of the Interview series on Expert-Talks, with Thought Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Mathangi Sri Ramachandran, Chief Data Officer at YUBI.  Before YUBI, Mathangi headed Data Science functions at GoFood ( part of GoJek ) and PhonePe.  She has near 20 years of experience in Data science and analytics, 100+ patents to her name, is an author of 2 books and is among the Top 50 Influential AI leaders in India.   We are listing below a few key points from the interview : Data is an organisation’s asset. So if data access gets restricted to only the data science and analytics team, then democratization and large-scale data-driven decision-making will not happen. So depending on how friendly the end users are with technology, you build an application layer and democratize these components so that each can explore their insights. In a simplified manner, Mathangi brackets analytics initiatives into  1. Human-led and Machine-assisted, where you provide self-serve models and data access in intelligent formats to businesses,  for them to make decisions and act quickly and 2. Machine-Led and Human-governed, where the analytics team is building transformative break-through models, with high and long-term business impact. For the Data Science team to create a meaningful impact in an organisation, the pre-requisites are the Quantum of available data, Business problems with constraints and an Organisation culture that encourages experimentation. An organisation that is open to experimentation & failure, will encourage teams to explore probabilistic scenarios and take big bets for non-linear impact. The absence of this can lead teams to be more deterministic in their approach, which by nature will be incremental in impact.  You can watch/listen to the interview on our Website, YouTube, Apple, Amazon Music and Spotify podcasts on the links below.  Please do share your comments and subscribe/follow us on @maavrus on LinkedIn, Facebook and Twitter.

    57 min
  5. 11/06/2023

    In conversation with Vinodh Ramachandran, Head of Data Science & Analytics, Neiman Marcus Group | Ep 17

    For Analytics & AI professionals in GCCs to be successful, developing domain knowledge and context is very important. I really think that it has to come from within. I was always intrigued by retail as a domain and curious about how things operate in the business. And I was always trying to make sense of what the numbers were telling me and What does it mean?. So I was always trying to put myself in the shoes of the business. And that's something that I enjoyed.  – Excerpt from the interview with Vinodh Ramachandran   Today is Episode 17 of the Interview series on Expert-Talks, with Thought Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Vinodh Ramachandran, Head – Data Science & Analytics, Neiman Marcus Group.  Prior to Neiman Marcus, Vinodh was Site Leader and DVP at Saks Off 5th, where he led all their business functions including analytics. He has also held Analytics leadership roles at Lowe’s , Target and Genpact. Vinodh frequently shares his thoughts at Industry forums.   We are sure you will benefit greatly from listening to his perspectives. A few key points from the interview :   Vinodh articulated the key factors that help make analytics initiatives successful.  1. A well-defined problem statement 2.  Alignment with the organisation's goals  3. Sponsorship from Top leadership. 4. Level of data maturity as measured by single source of truth and 5. The ability to explain the solution & insights to the business in an understandable and practical manner.   To develop domain knowledge and context, reading financial performance reports about the company and competition, and understanding the company’s organisational structure & processes from the company’s intranet pages, helps to get an overall perspective of business.   Exploring the data structure in a warehouse to understand product hierarchies, exploratory data analysis to understand customer behaviour and breadth of offerings, and then validating them in discussions with business stakeholders also helps in further building contextual knowledge.    Usage of external & outside-in data, apart from helping an analytics professional build trust and connect with the business, also helps develop strong hypotheses when looking for insights; for eg number & density of pawn shops in a retailer’s catchment, could have a correlation to a electronic / luxury retailer’s store shrinkage.   Generative AI is being used by many retailers, beyond generating content for customer engagement. It is also finding usages in other areas like customer service, where it is being used to summarise feedback from thousands of customer reviews to give a quick 80-100 synopsis to prospective shoppers.

    50 min
  6. 09/29/2023

    In conversation with with Neil Srinivasan, Founder - Canopus Business Management Group | Ep 16

    For continued success, it is necessary that Data Scientists are perceived as business function/process experts by the Business stakeholders. Apart from spending time on the operations floor,  signing up for industry certification courses can help Data Scientists, build good credibility with business  - Excerpt from the interview with Neil Srinivasan.   Today is Episode 16 of the Interview series  “Expert-Talks @ MAAVRUS” with Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Neil Srinivasan, Founder & Managing Principal of Canopus Business Management Group. Prior to starting Canopus, Neil was SVP – Customer Experience and Service Excellence at HSBC. He also held Business Excellence Leadership roles at Bank of America and Stanchart.  Neil is a Six Sigma Master Black Belt and author of 3 books.   We are sharing a few key points from the interview :   Banks traditionally are service-oriented, for which they need to continually drive efficiency into operations. To deliver this change one needs to be able to look at the end-to-end process and make fact & data-based decisions/solutions.  A strong background in Six Sigma process excellence makes it relatively easy to adapt to different industry domains.   In B2B the customer data exhaust follows a 1:10:100 during the “Early stage”: “Pre-order stage”: “Post-order account mining stage”. Conversely, in B2C the consumer data exhaust is significant before the order and comes down during product/service consumption.   Focus AI and Model efforts,  on customer or business segments, where there is a possibility for maximum impact and minimum time required for the model to be implemented, to start showing results. Neil calls this the “local-local” approach as opposed to a large global end-to-end project.   Increasingly customers are buying experience and not the product alone, so manufacturing organisations are required to incorporate the variabilities of customer and employee behaviour, in the way they design their product and consumption experience.  You can watch/listen to the interview on our website, YouTube, Apple, Amazon Music and Spotify podcasts on the links below.  Please do share your comments and subscribe/follow us on @maavrus on LinkedIn, Facebook and Twitter.

    44 min
  7. 08/29/2023

    In conversation with Piyush Chowhan, Chief Information Officer, Panda Retail Company, Saudi Arabia | Ep 15

    For any Business Transformation Leader to deliver on expectations, it is necessary that the leader is (i). In the transformation (ii)  Has a good team on board, and (iii). Is able to align the pace of transformation to the organisation’s pace. - Excerpt from the interview with Piyush Chowhan. Today is Episode 15 of the Interview series  “Expert-Talks @ MAAVRUS” with Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Piyush Chowhan, Chief Information Officer, Panda Retail Company, Saudi Arabia.  Prior to Panda Retail, Piyush was the Group CIO  Lulu Group, UAE. He has also held Technology and Transformation leadership roles at Arvind Lifestyle Brands, Walmartlabs and TESCO.  Piysuh speaks frequently at Industry forums about the technology and customer experience advancements in Retail. We are sharing a few key points from the interview :   One key business expectation of an Omni-retailer is its ability to serve customers seamlessly from its stores/warehouses.  So a Single View of Inventory including the systems, processes and controls to ensure near-accurate inventory data across locations, and an optimised last-mile delivery model, are the first and most important steps in the transition to being an Omni-retailer.   The important thing is having a 360 view of the customer. For a great Omni Customer experience, map the customer journey from an overall interaction perspective starting from pre-commerce to post-commerce, and then look at reducing the friction at each handover. One of the biggest challenges today is that most retailers are focused on improving only the commerce part of the experience, which leads to an overall disjointed experience.   Understanding Cultural nuances across geographies is extremely important for a successful transformation project. Depending on the geography, a leader needs to balance the level of prescription and empowerment.  The same proportion will not work across different geographies.   AI and ML programs & projects have to be embedded as part of larger digital transformation initiatives, for businesses to see the impact in terms of business outcomes. That is why ideally Data & analytics should be part of the Chief Digital Officer or Chief Transformation Officer’s organisation so that there is an aligned enterprise transformation journey.   You can watch/listen to the interview on our website, youtube, apple, amazon music and Spotify podcasts on the links below.  Please do share your comments and subscribe/follow us on @maavrus on LinkedIn, facebook and Twitter.   Youtube Video link. https://youtu.be/KeY98y7NylQ

    49 min
  8. 08/01/2023

    In conversation with Shailesh Jain, Group Head – Analytics & Insights, Landmark Group, Dubai | Ep 14

    People still trust people. While for simpler processes, we may trust machines because of their consistency & speed, when it comes to complex decisions or where the stakes are higher, we will continue to depend on people.  So for the foreseeable future soft skills will continue to be important in terms of human interaction, to get businesses to invest in areas that lead to higher customer experience & satisfaction. - Excerpt from the interview with Shailesh Jain   Today is Episode 14 of the Interview series on Expert-Talks, with Leaders in the Analytics, AI and Transformation space.  For this episode, our CEO Mahadevann Iyerr (Mahaa) is in conversation with Shailesh Jain, Group Head – Analytics & Insights, Landmark Group, Dubai.  Prior to Landmark Group, Shailesh was Senior Vice President & Head of Analytics ( Decision Management ) at Citibank India. He has also held Analytics leadership roles at KPMG Advisory and DunnHumby. Shailesh frequently shares his thoughts at Industry forums.   We are sure you will benefit greatly from listening to his perspectives. A few key points from the interview :   Shailesh spoke about the top 3 building blocks he focuses on,  to build great analytics capability  & business impact. First, deep business partnering with the business & functional leaders to understand their needs & vision better; Second, his analytics team spends quality learning time in the process be it the retail stores/distribution centres/merchandising process etc; and third role-rotation across various functions for each person to understand the interlinkages and the big picture better.   Projects are ideally planned with short-term objectives to create near-term business impact & credibility,  and with long-term objectives which align with the strategic transformational vision for that business.   Getting outside in perspective to complement internal performance has always been a key business expectation, and was mostly collected manually through surveys, research etc. This has now become easier thanks to customer’s digital footprint across social media, search, website journeys etc.   In future, any processes where decisions are based on business rules or discriminative insights will see faster AI adoption,  while complex decision making which requires a leap of faith / probabilistic calls, will still be taken by humans.   When it comes to generative AI,  organisations for now will use it for in-house processes within their private cloud. For any external & customer-facing use cases, it will continue to be with a human-in-the-loop   A Stanford University research validates that Deep Learning models with Explainable AI outperformed other deep learning models.  This is because, rarely does a model work in isolation – typically the output of one model is fed into another model, and so understanding the variables & weights of each model is important.  You can watch/listen to the interview on our website, youtube, apple, amazon music and Spotify podcasts on the links below.  Please do share your comments and subscribe/follow us on @maavrus on LinkedIn, facebook and Twitter. Youtube Video link. https://youtu.be/zOfYCdGNYOc

    52 min

About

Welcome to the "Expert Talks with Maavrus" podcast. This show is dedicated to exploring the cutting-edge of technology and its impact on the way we live and work. Each episode, we'll bring you interviews with experts in the field of analytics, artificial intelligence, and business transformation. We'll dive into real-world examples of how these technologies are being used to drive innovation and improve processes across industries. From big data and machine learning to natural language processing and computer vision, we'll cover the latest advancements and trends in the field. Join us

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