Data Science - the new silver bullet in retail?
16 March 2023, 16:30 - 18:00
FAW 9.04 (Fawcett House)
How is data science is helping retail business to create new revenue channels, improve efficiency, reduce working capital, become cybersecure, increase customer loyalty and accelerate sustainability?
Machine vision, structures/ unstructured data and hyper automation using ML, supervised/ unsupervised learning models and hyper personalisation are transforming retail. In this interactive lecture, Sunil Ramakrishnan will discuss real life examples of how data science has become a critical strategy at retailers like Amazon, Alibaba, Netflix, Disney, Nestle, Co-op, ZARA, OpenSea etc. Sunil will discuss the failures and successes in this path, learnings and the value being realised.
Sunil argues that data science is now the new silver bullet for companies in their defensive strategies where an incumbent is fighting new competition to lead as well in new offensive strategies where a new disrupter is creating a new blue ocean and taking away customers from lazy incumbents.
Speaker:
Sunil Ramakrishnan
Sunil is a Data Science leader and Vice President for Consulting at CGI and a sought-after inspirational speaker at numerous AI conferences across UK & Europe.
Before joining CGI, he was Chief Revenue Officer & Board member at QiO Technologies (a data science company), Head of AI & IIoT at IBM and Analytics leader at KPMG.
He has 25 years of experience in consulting with 10+ in using big data, statistics and data science to help retail, banking, energy and manufacturing businesses improve efficiency, reduce working capital, become cybersecure, increase customer loyalty and accelerate sustainability. Experience includes machine vision, structures/ unstructured data and hyper automation using ML, supervised/ unsupervised learning models and hyper personalisation.
Sunil is an IBM Data Science practitioner, MBA from Imperial College London and has an Honorary degree in Chemical Engineering.
Connect with him on LinkedIn and Twitter.