Headline Partner

Mihir Rajopadhye, Chief Data and Analytics Officer, Rich Products Corporation

Describe your career to date

I am the Chief Data and Analytics Officer at Rich Products, a leading global supplier of innovative food products and solutions. In this capacity, my responsibilities span the entire data value chain, overseeing the development of capabilities from data acquisition through consumption to the realization of value from data, analytics, and artificial intelligence (AI) solutions.

I have been fortunate to work with amazing people at multiple outstanding organizations, including Rich’s, Walmart, and Accenture, and data has been one of the constants throughout this journey. This journey began in graduate school at Duke University, where I researched commercial applications of intelligent systems.

Over the years, I have developed forecasting solutions for supply chain software suites, implemented data warehousing solutions, consumed insights for strategy development, optimized organizational capabilities through use of analytics, and successfully built and deployed analytical and AI solutions. Along this path, I have played a pivotal role in establishing and scaling data teams across multiple companies. Earning an MBA from Wharton further strengthened my conviction in the effectiveness of data driven approaches in addressing business challenges.

These diverse experiences have provided me with a deeper understanding and appreciation of the role of data within organizations. At Rich’s, I am driving the development of organizational data and AI capabilities, to accelerate our growth ambitions and elevate everyday experiences for our customers, associates, and ecosystem partners. Technology, data, and AI stand as key enablers on our transformation journey, and I am excited about leading AI-driven innovation at Rich’s.

How are you developing the data literacy of your organization, including the skills of your data teams and of your business stakeholders?

Data literacy is a critical component of Rich’s enterprise data strategy and aligns closely with the development of our data and analytics capabilities. Our approach to crafting a robust data literacy program is grounded in understanding the unique requirements of diverse stakeholder groups.

For executives and business leaders, the focus lies in fostering awareness of how data – or its absence – influences analyses. Equipping leaders with the right questions is crucial for obtaining better and quicker insights. Business users seek guidance on interpreting and analyzing data to make informed recommendations and decisions. Operations prioritize actionable and explainable insights, empowering them to execute processes with speed and efficiency.

Data professionals, spanning roles such as data stewards, analysts, and scientists, demand a deeper understanding of data sources, proficiency in analytical methods, and mastery of tools for effective data manipulation. By tailoring our data literacy program to the specific needs of each stakeholder group, we work to ensure that the content and training cultivate robust data acumen and foster a culture of data-driven decision making throughout the enterprise.

What role do you play in building and delivering conventional AI solutions, including machine learning models? Are you involved in your organization’s adoptions of generative AI?

At a high level, I am responsible for crafting and evolving the organization’s AI strategy, accelerating the widespread deployment of AI solutions, and implementing safeguards to effectively manage associated risks.

We are witnessing an incredible surge in AI-based solutions addressing diverse business challenges across various functions. The value realized from these solutions hinges on our ability to deliver at scale and with speed. This involves leveraging our data assets, technology capabilities, and human expertise, alongside the efficient reuse of analytical and machine learning models.

Concurrently, we have implemented controls to ensure that the promised value from deployed AI solutions is tangibly realized within the business. Upholding ethical, privacy, security, and responsible AI standards is embedded in our delivery framework.

Our approach to managing the AI portfolio spans the spectrum of advanced analytics, conventional AI, machine learning, and generative AI (genAI) solutions. While we have updated our playbook to incorporate the nuances of genAI, the overarching responsibility for driving the adoption of genAI solutions remains firmly within the scope of the organization’s AI strategy framework.

How are you preparing your organization for AI adoption and change management?

Research continues to identify trust and interpretability of AI models as important factors that affect end user adoption of AI solutions. We include likelihood-of-adoption as one of several criteria in evaluating AI opportunities at Rich’s, and provide development teams with support to make models outputs more explainable and easier to understand.

Additionally, we include design and user experience considerations in the development of AI solutions to facilitate last mile adoption. We are also extending our persona-based data literacy framework to AI literacy.

Rich’s has a strong culture of embracing change, and I am fortunate to have an executive team that understands the transformative potential of AI. We have an established transformation and change management office that oversees strategic business transformation initiatives, and the ability to tap into these change management capabilities is a key enabler for accelerating organization readiness for AI solutions.

Mihir Rajopadhye
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