I Believe in a Business-first Strategy, Data or AI Comes Second — Mars Wrigley Global Data and AI Expert

(US & Canada) Deepak Jose, Global Data and AI Expert at Mars Wrigley, speaks with Jack Berkowitz, Chief Data Officer at Securiti, in a video interview, about his professional journey, the evolution of data in the Consumer Packaged Goods (CPG) space, and the need to change the mindset to build the right organizational strategy.

Mars Wrigley is a leading manufacturer of chocolate, chewing gum, mints, and fruity confections. The company's products are sold in over 180 countries and include brands such as M&M's, Snickers, Orbit, Extra, and Skittles.

Jose mentions Mars Wrigley as one of the most purpose-driven companies in the world. He begins with the Mars slogan, “The world we want tomorrow starts with how we do business today.”

Further, Jose feels privileged to be a part of one of the largest family-owned companies globally and to carry out long-term initiatives for the organization. Since joining Mars in 2019, he has had the opportunity to work on several initiatives that transformed the company across all segments.

Being in the data analytics and AI domain, Jose transformed the organizational data analytics practice as part of a program called One Demand Data and Analytics for the Mars Wrigley Division. He also mentions working for global organizations like Coca-Cola and Mu Sigma prior to joining Mars, which shaped his journey as well.

Moving forward, Jose sheds light on how the data space has evolved for large brands or consumer goods companies. Over a decade ago, he says, the organizations in the CPG domain would have massive sets of internal data such as finance, supply chain, and R&D.

In addition to that, such organizations would get consumer data from third-party data providers like Nielsen, IRI, and Kantar to help consumer-focused companies make the right decisions. On the contrary, now there is an integrated strategy of zero-party data, first-party data, and second-party data.

Zero-party data is the data that consumers proactively share with brands or large organizations. Next, the first-party data is data that gets acquired through consumer purchases on websites as part of D2C businesses. For second-party data, the organization partners with large companies that are its customers.

For instance, second-party data would come from partnering with Walmart or Amazon, says Jose. This shows the evolution of data space from internal and external third-party data.

Now, it is imperative for a large consumer-led organization to build a connected data strategy, says Jose. To explain the reason behind this, he uses the analogy of four blind people describing an elephant. All four people end up describing the elephant based on the part they had touched.

Similarly, in a large organization, the customer is the elephant. When the sales, marketing, and supply chain teams explain consumers in their own ways, it becomes critical to have an integrated and unified data strategy for everyone to work on a single truth.

Thereafter, Jose highlights the need for building the perfect organizational strategy. After connecting with several CDOs, he mentions discovering that everybody has a different strategy.

While many CDOs believe in building an AI-first strategy, there are many others who are building a data-first strategy, says Jose. However, he believes in building a business-first strategy, and data or AI comes second.

According to Jose, it is fundamental for organizational leaders to have a business decision-backed mindset to begin with. Based on his experience, he says that organizations that tend to call themselves "data-first" companies incentivize massive data ingestion to build a huge data foundation.

In continuation, Jose says, earlier such large organizations had data warehouses, which then became data lakes, and now they have data lakehouses. Consequently, it boils down to building a data foundation on top of the existing one, and with people generating insights, those will eventually create small value.

As a practitioner, Jose advocates inverting the pyramid by starting with a value-first and business problem-first mindset. To do this, one must comprehend the organization’s largest business priorities and focus on those first.

Then, organizations can leverage data to solve business problems. Jose asserts that it is more important to find the right business problem than to solve the problem right. He suggests sticking to the fundamentals, having a business problem for strategy, and utilizing data and AI as enablers to solve it.

Furthermore, Jose says, there is a significant opportunity to leverage AI, specifically generative AI (GenAI), to drive value creation for the organization. Also, in that journey, GenAI will be an enabler.

In conclusion, Jose states that sometimes, if a traditional classical machine learning algorithm can solve a specific problem, it should be used. However, to make it all work, it is critical to have trusted, quality data that enables the algorithm. He mentions that at Mars, the relevancy, trust, and usage of data are focused on to ensure building the right AI tools.

CDO Magazine appreciates Deepak Jose for sharing his insights with our global community.