#237: Evolving data culture to deliver sustainable business impact, with Niall Keating, General Manager for Technology Data Platforms, Sportsbet

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

In this episode, we explore an engaging talk given by Niall Keating, General Manager for Technology Data Platforms at Sportsbet, during his recent appearance at the Data Engineering Summit in Melbourne.

Niall generously imparts invaluable insights on the journey of cultivating a data culture that yields long-lasting business impact. Throughout the conversation, Niall showcases tangible examples of how Sportsbet has effectively utilised data and technology to drive innovation and elevate customer experiences. Sportsbet, Australia's largest online bookmaker, faces unique challenges due to the dynamic nature of their product, where prices constantly change.

To overcome these challenges, Sportsbet has invested significantly in technology and data infrastructure. One use case Niall highlights is their adoption of machine learning, with over 20 models currently in production. These models are employed to extract actionable insights, enabling Sportsbet to make data-driven decisions and enhance their offerings.

Niall emphasises the importance of establishing a solid foundation in data culture and leveraging data for decision-making and financial reporting. He provides a specific use case of how Sportsbet utilises quantitative analytics to calculate probabilities and set prices for their core product. By harnessing data and analytics, Sportsbet optimises generosity, personalised experiences, and aims to provide the best value to their customers.

Another use case Niall discusses is the application of data in safer gambling. Sportsbet is committed to making gambling safer, and they leverage data to identify potentially risky behaviours and intervene when necessary. Niall highlights the journey Sportsbet has undertaken over the past five years in building effective data products to promote safer gambling practices.

When it comes to sustainability in data, Niall shares three educational stories that provide valuable insights. In one use case, he emphasises the importance of avoiding quick wins and taking an iterative approach aligned with strategic goals. He discusses the challenges involved in transitioning from human to AI automated decisions and the need to bridge the gap effectively.

Lastly, Niall shares a use case centred around Sportsbet's product journey in safer gambling. He highlights the time and collaboration required to build effective data products that prioritise customer safety. This use case demonstrates the impact that data-driven approaches can have in creating a safer gambling environment. By adopting a long-term perspective and focusing on values such as safer gambling and customer-centricity, Sportsbet sets an example of how data culture can drive innovation and create positive outcomes.

Enjoy the show!

Thank you to our sponsor, Talent Insights Group!

Join us for our next events Advancing AI and Data Engineering Sydney (5-7 September): https://www.datafuturology.com/events

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

Topics Discussed:

02:39. Introduction to Niall Keating and his background in software engineering.

04:08 Overview of Sportsbet as Australia's largest online bookmaker, serving one million active customers.

05:04 Investments in technology and data infrastructure, with a focus on machine learning and the impact of over 20 models in production.

07:06 The importance of getting the basics right in data-driven decision-making, financial reporting, and core product development.

09:14 The journey towards sustainability, including the focus on personalization, safer gambling, and aligning products with the company's vision and mission.

15:37 The challenges and lessons learned in evolving the data platform, including the adoption of lake house architecture and partnerships with AWS and Databricks.

22:04 The importance of building data products over time, collaboration between data science and analytics teams