Data and Analytics At the Heart of Every Part of the Mondelez Business

Alarice Rajagopal
Senior Editor
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Advancements in technology have allowed consumer goods companies to design and manufacture products faster than ever before, sell those goods in multiple channels, and quickly react to changing demands ― dynamically transforming the entire global supply chain.

These value chains produce troves of data and insights that can help CG companies maintain a competitive edge. In a recent Analytics Unite 2020 session Ash Mehra, global data and analytics lead and North America CIO for Mondelez International, joined the company’s chief data scientist Abdul Raheem to explore how organizations can incorporate cognitive, predictive and prescriptive analytic strategies to supercharge the value chain - and how they can be leveraged to improve operations in times of unprecedented demand.

Clockwise from top: RIS and CGT editor in chief Tim Denman, Ash Mehra and Abdul Raheem

Mehra and Raheem couldn’t talk about the 19th largest consumer goods company’s vision without first revealing their favorite products: Oreos for Raheem and Cadbury for Mehra, which he explained is synonymous with candy in his native India. Then, the Mondelez vision was revealed that “data and analytics touches all aspects of the business.” That means from its business model to consumer engagement to customer experience to operational efficiency to employee engagement, data analytics is at the center or “at the heart of Mondelez,” said Mehra.

He then talked about some of the common pains and challenges that CGs face when it comes to leveraging data such:

  • Insufficient re-use of data
  • Too many projects: POC trap
  • Making a material business impact using D&A
  • Fragmented data architecture
  • Lack of sufficient ‘purple’ people
  • Data ownership and data management

However, Mehra revealed that the Mondelez strategy is what they call 3+1: Three strategies (scale proven products, establish data and digital platform, innovate with analytics Lab), plus one critical enabler (transform data and analytics).

For example, Mondelez has been using AI for suggested order to scale proven product (starting in India and expanding at scale globally in the next three years).

“We do integrate with Google API to get a wealth of demographic information from locations and the concentration of the different outlets out there, so Google API is really strong in providing a wealth of information that can be used for model iterations and future engineering,” Raheem explained, later saying that it was useful for test and learn (for all his data scientist friends out there).

Another example Raheem talked about was round waste analytics unveiling that in 2019, waste analytics was a key contributor to $78M in waste reduction in 2019 and on plan for similar waste reduction for 2020. He then covered "1 Sales Analytics" ― trying to equip the sales organization with the right level of analytics that is actionable.

“Not just to harmonize the data, but also be able to provide them with daily sales analytics that are predictive in nature,” Raheem said.

After talking through more detailed use cases such as details around the Mondelez Analytics Lab, and the 3+1 strategy, Mehra and Raheem closed the session with some key takeaways including:

  1. Focus on a few proven products when scaling for high value business impact.
  2. Establish a holistic, future-proof data strategy and architecture.
  3. Transform D&A through an entrepreneurial and collaborative mindset.

“We have to keep developing our innovation muscle as well so that we can be ready for new challenges, and we have to transform our organization with a much more of an entrepreneurial and collaborative mindset,” added Mehra, noting that Mondelez still has a long way to go.

This is also published on CGT. 

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