At our recent Virtual Think IT Event, industry experts gathered to discuss how organizations can treat data as a product and leverage data strategies to drive business value. This insightful panel featured Arshad Mohammad, Senior Director, Head of Enterprise Architecture, Data Strategy & Governance at Hilton, Revathi Addagudi, Strategic Technology Director at Mano Infoways, and Anandh Asokan, Vice President, Data Engineering, Management and Enablement at Thrivent. Here are the key highlights:
Data as a Product: Emphasizing Usability and Governance
A central theme of the event was the importance of viewing data not merely as an asset but as a product. Arshad Mohammad explained that treating data as a product means creating data that is self-contained, governed, and ready for consumption. On the other hand, delivering data with product discipline focuses on iterative approaches and continuous delivery. Hilton’s strategy exemplified this shift, moving from source-specific data modeling to a domain-driven approach. This transition, involving 13-14 domains, allowed Hilton to align data closely with business needs and use cases. The panelists stressed the importance of making data self-describing and discoverable to ensure its accessibility and long-term value.
Shifting to Domain-Driven Ownership
The discussion also focused on shifting from siloed data ownership to domain-driven ownership. Anandh Asokan emphasized the need for organizations to move from fragmented, raw data to purpose-driven, user-friendly data experiences. Adopting a domain-driven approach enables continuous value delivery and ensures data remains an ongoing, iterative product. Data quality emerged as a key concern—Anandh highlighted that it should be embedded within the product, not treated as an afterthought. The panelists agreed that organizations must prioritize outcome-driven insights, rather than focusing solely on output metrics.
Real-World Example: Improving Forecasting Accuracy in Retail Supply Chains
Revathi Addagudi shared a compelling case from the retail industry, demonstrating the transformative power of data. Using event-driven architecture, like Kafka clusters, retailers processed and analyzed data in real time, leading to a 28% reduction in stock-outs and 90% accuracy in demand forecasting across channels. Key takeaways included the importance of stakeholder management, fostering a cultural shift, and prioritizing initiatives based on business impact. Revathi also noted the need to avoid disruption during transformation to maintain business continuity.
The Importance of Cultural Shifts and Stakeholder Buy-In
Cultural change was another significant theme. Arshad Mohammad emphasized that success with data as a product requires more than technology; it demands a mindset shift across the organization. At Hilton, clear success definitions helped gain stakeholder buy-in and foster adoption. Revathi further shared that early communication and demonstrating value to leadership are crucial for securing buy-in. Managing dependencies and ensuring backward compatibility with legacy systems are also vital for smooth data transformations.
Measuring Success and ROI: A Journey, Not a Destination
The panelists discussed how to measure the success of data products. Arshad Mohammad shared an example from Hilton, where a dashboard was built in 72 hours to manage the West Coast fires, an initiative that would have taken months with legacy systems. Panelists agreed that ROI is not solely about financial return but also about the speed and accuracy with which businesses can answer key questions. Success indicators include reducing time spent wrangling data and enabling users to focus on insights, with both qualitative and quantitative metrics mattering depending on an organization’s strategic priorities.
Balancing Governance with Practicality
A crucial takeaway from the event was the need to balance data governance with practicality. Governance is essential for ensuring data quality and security but should not stifle innovation. Data governance must be an integral part of the product, ensuring accessibility, reliability, and actionability without hindering progress.
The panel concluded with a reflection on the continuous nature of data transformation. Organizations that prioritize continuous improvement, clear success definitions, and a collaborative culture are better positioned to unlock the full potential of their data.
The key to successful data transformation lies in treating data as a product, focusing on iterative, user-friendly data experiences, and fostering a culture of collaboration and continuous learning. By doing so, organizations can ensure they stay ahead in a rapidly evolving technological landscape. Thank you to everyone who joined the event and participated in this enriching discussion.