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2024 Analytics Symposium: Roundtable Takeaways

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IIA, Symposium

Recently, IIA held its annual Analytics Symposium to help clients cut through the AI hype and unlock the full potential of data and analytics at their enterprises. Roundtable discussions led by IIA experts proved to be a highlight of the day. These sessions were small, interactive conversations where peer-to-peer sharing was encouraged by all.

Here’s a snapshot of these roundtable sessions. IIA clients have access to the detailed insights in the client-only portal.

Symposium attendees: Join the private 2024 IIA Analytics Symposium LinkedIn Group to connect, collaborate, and keep the Symposium insights alive.

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1. Data Strategy and AI Readiness

The interplay between data strategy and generative AI is pivotal as businesses strive to leverage unstructured data and proprietary AI models. Discussions at the roundtable highlighted the essential evolution of data governance frameworks to support AI's integration, emphasizing the need for robust data management and AI literacy among executives. Companies shared their journeys toward aligning AI with strategic objectives, focusing on infrastructure readiness and continuous updating of AI strategies to stay competitive.

Facilitated by:

  • Jon Agnone, Head of BI and Strategic Analytics, Atlassian
  • Greg Nelson, Vice President, Data Operations, Highmark Health

2. Data and Analytics Leadership: The Pursuit of Visible Value

Data and analytics leaders are central in shaping business strategies that visibly drive value. The roundtable explored how generative AI is transforming operational and customer service strategies, with leaders emphasizing the need for well-defined strategies before deployment. Discussion also covered the integration of business acumen within data teams to ensure that data initiatives align with broader business outcomes, highlighting shifts in organizational structures to enhance strategic data use.

Facilitated by:

  • Neil Bhandar, VP IT, Enterprise Data, Analytics and Innovation, Generac Power Systems
  • Kari Jones, Executive Director, Transformation and Operational Delivery, Financial Markets Authority—New Zealand

3. Measuring and Communicating the Value of Analytics and AI Initiatives

Capturing and conveying the value of analytics and AI remains a complex blend of art and science, particularly with the advent of generative AI. Leaders shared methodologies for quantifying impacts and the importance of developing clear metrics and feedback loops. Effective change management and stakeholder engagement were discussed as crucial for fostering organizational buy-in and leveraging analytics and AI across businesses.

Facilitated by:

  • Ritu Saxena, Director, Analytics Engagement and Data Science, Merck
  • Sandy Steiger, Senior Director, Advanced Analytics and Automation, Total Quality Logistics

4. Analytics and AI Maturity: Strategic Workforce Planning

As analytics organizations mature, the balance between acquiring new talent and developing existing employees is critical. The roundtable underscored the use of AI and technology in enhancing HR processes and strategic workforce planning. Leaders shared insights on internal training programs, partnerships with educational institutions, and the integration of AI competencies into job roles to address the evolving demands of analytics organizations.

Facilitated by:

  • Durrell Robinson, Senior Manager, People Analytics and Employee Listening, Colgate-Palmolive

5. Generative AI Use Cases: Lessons Learned, Next Steps

The practical application of generative AI in business processes dominated discussions, with insights into overcoming obstacles from proof-of-concept to production. The roundtable also tackled the complexities of data governance and regulatory compliance, highlighting the need for transparent and accountable GenAI deployments. Evaluating the impact of GenAI projects through clear, measurable objectives was emphasized as essential for demonstrating value and securing stakeholder support.

Facilitated by:

  • Michael Barber, Director, Data Science R&D, Highmark Health
  • Anshul Jain, Data Science Leadership, Meta
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