(EMEA) | Success of Data Initiatives Often Depends on Soft Skills — Danone UK&I CDO, Director Data and Analytics

Amitabh Seli, Director of Data and Analytics and UK&I CDO at Danone, speaks with Jack Berkowitz, CDO of Securiti, in a video interview about his role as an effective CDO, the role of cross-functional collaboration, communicating the privacy and governance aspect of live systems, and two successful analytics initiatives he has worked on in the past.

According to Seli, the effectiveness of a Chief Data Officer (CDO) often hinges on their ability to collaborate across organizations. It's not just about technical skills but also the softer, more intangible aspects that determine success or failure.

Seli further states that understanding the business goals is paramount. He emphasizes the importance of engaging not only with senior stakeholders but also with their teams, fostering cross-functional collaboration. This involves adopting a workshop-style approach, where diverse teams come together to discuss problems and devise joint solutions, especially when implementing new tools or technologies like AI and ML.

Educating teams about the models being used and their objectives, and defining success collaboratively are crucial steps. Additionally, communication about the value of initiatives and aligning on overarching goals and specific use cases are vital. Seli stresses the need for close collaboration with teams to foster a data-aware culture, mindful of privacy and compliance concerns. Both sides of the business need to be aware of privacy and regulatory guidelines when implementing AI and ML initiatives.

In a similar vein, Seli emphasizes the critical importance of ensuring that business users and internal teams understand that AI and ML projects are dynamic systems requiring continuous monitoring and enhancement. It's paramount for businesses to extract value not only from AI and ML initiatives but also from any data-related efforts they undertake. This value must be quantified and demonstrated tangibly, whether through ROI, productivity gains, efficiency improvements, or overall business growth.

Furthermore, Seli stresses the significance of two foundational principles in this context - privacy and data governance. These principles ensure that data is used ethically, legally, and responsibly. Given that AI and ML tools function as live assets within organizations, it's essential to maintain their accuracy and effectiveness.

Seli underscores the necessity of establishing standards and thresholds to monitor the performance and precision of these models continually. This monitoring process, facilitated by MLOps or similar units, helps mitigate the risks associated with potential errors or misinterpretations, which could have damaging consequences if left unchecked. Thus, he advocates for a cautious and controlled approach to the deployment and management of AI and ML tools.

In conclusion, Seli goes on to highlight a couple of past data and analytics initiatives that drove positive outcomes for both consumers and the business. One notable project at British Airways enhanced consumer loyalty through a deep understanding of behavior patterns.

Similarly, a project at Sky involved analyzing media consumption data to tailor subscription offerings based on consumer preferences, resulting in propositions that better served the customers' needs. These experiences underscored the value of using consumer insights to inform decision-making and drive engagement.

CDO Magazine appreciates Amitabh Seli for sharing his insights with our global community.