How Can Data Leaders Shift from Data-First to Business-First Mindset? With Deepak Jose, Global Data, Analytics and AI leader
Oct 16, 2024
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Deepak Jose, Vice President of Data Sciences & Business Intelligence at Niagara Bottling, discusses his career transition from mechanical engineer to data leader. He emphasizes the necessity of a business problem-first mindset over a data-first approach. Deepak shares insights on the evolving role of AI in business, advocating for adaptable strategies rather than rigid capabilities. He stresses the importance of empathy and collaboration in leadership to truly solve organizational challenges. Personal reflections highlight the significance of family and work-life balance.
Deepak underscores the importance of shifting from a data-first mindset to a business problem-first approach to drive value in analytics.
He highlights the necessity of active collaboration and emotional intelligence in aligning data initiatives with business needs and stakeholder engagement.
Deep dives
Transitioning from Engineering to Leadership
Deepak Jost's journey from mechanical engineering to leadership in data and analytics highlights the necessity of adapting one's mindset throughout career progression. Initially, his technical background offered a solid foundation, yet he recognized the growing importance of emotional intelligence (EQ) and a business-focused perspective in transformative roles. This transition involved moving from a purely data-first approach to a more value-driven framework, where understanding business challenges became paramount. By embracing empathy and engaging with stakeholders, Deepak learned how to influence organizational culture and drive successful change management.
The Importance of a Value-First Mindset
Deepak emphasizes a fundamental shift from a data-first mindset to a value-first approach within data analytics organizations. Rather than investing heavily in data infrastructure without a clear purpose, he advocates for identifying business problems that need solutions first. This approach ensures that data initiatives directly address specific challenges faced by the organization, thereby maximizing their utility and relevance. By prioritizing business value over technical specifications, Deepak has been able to foster more effective collaboration between data teams and business stakeholders.
Embracing Active Collaboration and Engagement
Active collaboration is essential for data analytics practitioners who seek to align closely with business needs. Deepak shares his experiences with earlier missteps in his career, where generating insights without adequate engagement with stakeholders resulted in wasted efforts. He highlights the significance of design thinking and understanding how analytics can drive business outcomes, stressing the necessity of creating user-centric solutions. By fostering direct communication and collaboration, data professionals can overcome the traditional barriers that often hinder effective decision-making.
Navigating the Future of AI and Data Strategy
Deepak envisions a future where generative AI reshapes the way data analytics drives business decisions, emphasizing that responsible usage of AI is non-negotiable. He outlines the significance of developing a clear strategy that prioritizes automation of mundane tasks, enhancement of existing processes, and fostering innovation in product development. Additionally, he recognizes the role of synthetic data as a potential game-changer in ensuring data adaptability and enabling organizations to respond to market changes. By focusing on a balanced investment in technology and upskilling employees, businesses can cultivate a culture of innovation while serving their core objectives.
A Mindset Shift: Business Problem First, Data Second (9:31)
Learning From Missteps (11:00)
The Gazelle and the Lion Analogy (14:53)
The Role of AI: Do Things, Do Things Better, and Do Better Things (25:58)
Built to Last versus Built to Adapt (40:01)
Key Quotes
"Instead of a data-first mindset, you need to have a business problem-first and data-second mindset. That has helped me transform myself as a leader quite a bit."
"It’s more important to define the problem right than solving the problem. How can we understand what you’re trying to solve, and how it impacts the stakeholder?"
“The head of data analytics functions need to be business problem driven, empathy driven, and not technology-first minded or AI-first minded. Our objective is to solve the business problems of the organization. Data, AI, and tech are the enablers.”
"In the past, we built capabilities to last. Now, the mindset has to be to build capabilities to adapt."
Deepak Jose is Vice President, Head of Data Sciences & Business Intelligence at Niagara Bottling. He is a member of the Forbes Tech Council, AWS Retail and CPG Executive Advisory Forum, industry standards associations, Editorial Board for CDO Magazine, and an advisor for startups and AI analytics service companies.
Before Niagara, Jose was part of global brands like Coca-Cola, Mars, ABB Group, Asurion and Mu Sigma in strategic roles driving business growth. He was named to the 2023 Consumer Good Visionaries by Consumer Goods Technology and Retail Info Systems News, the 2023 40 under 40 by CDO Magazine, the 2022 and 2023 Top 100 Innovators in Data & Analytics by Corinium Global Intelligence, the 2023 100 Most Influential AI Leaders in USA by AIM Research, the 2023 Direct 60 List by The Lead, and the 2023 DataIQ 100 lists.