(EMEA) | Structure ROI Metrics With Business Objectives at the Core — 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 professional journey, establishing frameworks to measure ROI, setting business objectives, and communicating business value with AI and ML.

Danone is a leading food and beverage company building on health-focused and fast-growing categories in 3 businesses — Essential Dairy and Plant-Based products, Waters, and Specialized Nutrition.

With a career spanning over three industries, Seli has fine-tuned his expertise with data and analytics through his role in each sector. He started working with British Airways, then with a media company in a range of data analytics and strategy roles, before joining Danone.

As a director of data for Danone, Seli states that in his journey so far, he has tried to get maximum value from data for business objectives.

When asked about establishing clear metrics and frameworks to measure ROI, he opines that it is critical to start with identifying business objectives and what needs to be solved. Seli states that with data science and technology enabling everything, the initiatives must derive value.

Therefore, having a clear set of objectives is the starting point of any AI/ML initiative, and the initiative needs to be tied to metrics with objectives in mind. Further, he adds that the objective could be better customer retention, acquisition, productivity, or better predictions, but KPIs must be associated with tracking value.

Further, Seli affirms the need to keep an aggregate effectiveness score of AI or accuracy of prediction, which should improve over time. He reiterates that the ROI metric should be structured to keep business objectives at the heart.

Delving further, Seli opines that to assess growth, he sets a baseline definition of things as they stand today and then measures it with the improved performance over time. Similarly, he looks at success and change in smaller chunks of time and achievements rather than big leaps.

At the core of this philosophy lies the feedback loop of continuous improvement, which is tracked and improved on an ongoing basis rather than hitting the objective target once.

Commenting on ways to communicate business value, Seli mentions approaching the solution around the business problem through storytelling instead of leading from the science aspect. It boils down to getting people engaged and then presenting a solution that might help bridge the problem, he notes.

That is how Seli communicates the value of AI and ML, and he further lists out certain principles, keeping in mind the diversity and audience among stakeholders.

  1. The narrative should be simple, consumable, and avoid jargon.

  2. Consider visualizing the impact of communication and making it tangible for people.

  3. Have a framework to make the discussion outputs or models perceivable to users.

In conclusion, Seli states that the framework will allow users to know how they will use it, what they will derive from it, and how it will enable teams to achieve more. He communicates the value of AI and ML through these key principles while embedding them in the business.

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

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