Amazon Grocery’s Whole Foods Market simplifies operations and boosts performance with modern business intelligence using Amazon QuickSight

Whole Foods Market is a leader in natural and organic foods grocery, upholding rigorous quality standards and a steadfast commitment to sustainable agriculture. At Worldwide (WW) Grocery Data and Tech, we’re responsible for Whole Foods Market’s reporting platform, which supports an enterprise-wide business intelligence (BI) infrastructure for our over 25,000 users across its retail and corporate teams. As part of our digital transformation strategy, Whole Foods Market needed a modern, scalable, and high-performance solution to simplify and optimize BI to improve employee experience and overall performance, because our previous tool was becoming difficult to manage, time-consuming, and expensive.

In this post, we share how we used Amazon QuickSight to provide scalable BI across over 25,000 users generating 1 million views per month, improving efficiency and reducing costs.

From approval to launch—in 6 months

We faced several challenges with our previous BI tool. It integrated data from over 30 diverse sources, including various database connections, as well as cloud storage platforms such as Amazon Simple Storage Service (Amazon S3) and Amazon Redshift. This complex data integration process necessitated substantial computational resources for tasks like data joining, field calculations, and aggregations within the BI platform itself in real time. Consequently, these resource-intensive operations significantly impaired the overall system performance, leading to massive overhead for our team because we had to manually manage the data pipelines and build new reporting. This warranted the need for a more reliable, secure, and high-performant BI solution like QuickSight. As part of our shift to QuickSight, we decided to move to an AWS data lake as a single source of truth. This shift helped us simplify data management, enforce row- and column-level access for more granular control, and enforce data compliance. By performing most of the data preparation before it reaches QuickSight, we’ve reduced the load on runtime processing, improving performance.

We aligned our migration to QuickSight into our top-down vision, which aims to consolidate tools and simplify the user experience across store banners. Our migration started in September 2023, with QuickSight setup and development beginning in November 2023. The project was implemented in two phases: Phase 1, completed in March 2024, focused on migrating frequently used and not so complex dashboards, and Phase 2, launched in May 2024, tackled dashboards with greater complexity that were critical for leadership decision-making but had a smaller user base.

Deploying modern BI with QuickSight across our organization

QuickSight plays a critical role in supporting both our store and executive teams with the insights they need to make data-driven decisions. It supports reporting for a variety of areas, including labor planning, shrink, food safety, in-stock management, production planning, team member engagement, pricing, and store processes. Our store leaders use the Store Leadership Dashboard, which tracks 25 key metrics, to inform day-to-day actions.

QuickSight now powers a range of reporting dashboards to support store-level and strategic decision-making. Key use cases include:

• Store leadership – Provides insights into store-controllable performance metrics used by store leaders to drive daily decisions.
  
• Store process scorecard – Tracks operational processes and compliance across various store functions.
  
• Daily sales dashboard – Offers real-time sales data to monitor performance and adjust strategies accordingly.
  
• Usage metrics dashboards – Tracks usage metrics like top dashboards by number of views and average load time for visuals.
  
  
  

QuickSight has delivered a range of benefits that have transformed how Whole Foods Market manages and accesses BI. These benefits include:

• Improved performance – QuickSight reduced dashboard load times by 90%, from 2–5 minutes to just 5–10 seconds. QuickSight’s SPICE (Super-fast, Parallel, In-memory Calculation Engine) is at the core of this performance boost. SPICE allows us to handle large volumes of data efficiently, replicating it automatically for high availability. This means our dashboards are not only faster but also more reliable. SPICE enables thousands of users to perform fast, interactive analysis simultaneously. By shielding our underlying data infrastructure from heavy reporting loads, QuickSight saves us both time and resources, so our teams can focus on decision-making rather than waiting for reports to load.
• Cost savings – Switching to QuickSight reduces our costs by 75% with usage-based pricing that can scale based on our requirements.
• Auto scalability and flexibility – The auto scaling capability in QuickSight has been crucial in supporting high-volume use cases. The underlying SPICE caching means there’s no limit on the number of concurrent users who can access the platform at the same time. This is essential for our large store teams, where thousands of users access dashboards at the same time without any performance issues.
• Enhanced security and access control – Security was another critical factor in our decision to migrate to QuickSight. The platform provides better security risk detection and global resolution capabilities than our previous BI tool. The fine-grained access control features in QuickSight allow us to enforce row- and column-level permissions, making sure each user only has access to the data they need, which is important in a regulated environment like ours.
• Streamlined operations – QuickSight has also helped streamline our overall operations. Before migrating to QuickSight, our previous BI tool required us to manage multiple data sources and reporting layers, leading to high levels of manual work and impacting the performance of reports.

Lessons learned

Our migration to QuickSight taught us valuable lessons that could benefit other organizations considering a similar move:

• Phased approach – We used the Pareto principle to prioritize our work, focusing on low effort and high impact results, which changed the experience for thousands of users. Breaking the migration into phases allowed us to manage the transition more effectively.
• Data consolidation – Moving towards a single source of truth (Andes) has simplified our data architecture and improved data governance.
• Performance monitoring – Regularly tracking dashboard performance has helped us identify and address bottlenecks quickly.
• Continuous learning – As QuickSight evolves with new features, we’re committed to ongoing training and exploration to maximize the platform’s potential.

Conclusion

Adopting QuickSight at Whole Foods Market has marked a new era in BI by solving immediate challenges, positioning us for future analytics growth. The combination of improved performance, enhanced security, cost savings, and advanced features has made QuickSight an invaluable asset in our technology stack. It has enabled us to explore AI-powered capabilities, such as natural language queries in Amazon Q in QuickSight, which enables users to generate visuals by simply describing them in natural language and streamline dashboard development to provide deeper insights and more efficient operations.

To learn more, visit Amazon QuickSight.

About the Authors

Ravi Reddy is a Data Engineering Manager at Amazon, leading the Operational Reporting and Analytics team within Grocery Data Tech. He oversees enterprise-scale data analytics solutions that cater to thousands of users across various business areas. He is customer obsessed and consistently innovates and simplifies analytics processes to deliver actionable intelligence rather than overwhelming data. He is currently exploring the potential of generative AI and large language models in partnership with AWS to further accelerate speed-to-insight.

Maitri Shah is a Senior Technical Program Manager at Amazon QuickSight. She leads cross-functional programs focused on product adoption and drives strategic migrations. Maitri is passionate about process improvement and finding innovative ways to solve customer problems. Outside of work, she likes to create intricate and meditative mixed media art forms.