Summary

A 75-year-old Fortune 500 toy company is undergoing a comprehensive modernization effort across its organization, with cost-efficiency and improved data analytics, as the primary objective.

Customer Challenge

The project team engaged with the customer to perform a comprehensive discovery process, analyzing billing data and customer-provided information to understand and manage their current spend. Given the substantial costs associated with their compute, container, and analytics services, these areas became primary focal points, with additional attention to serverless solutions due to growing customer interest.

A significant challenge for the customer was their limited ability to effectively manage and reduce costs within their existing data infrastructure. With legacy systems and outdated lifecycle policies in place, the organization faced difficulties in optimizing their data estate, lacking the necessary expertise and in-house resources to streamline their environment. As a result, they were heavily reliant on external support to identify cost-saving opportunities and develop a roadmap for modernization and efficient resource utilization.

Project Deliverables

Provided the client with regular updates on the status of their high-priority feature requests (P1/P0), indicating alignment with expectations and whether they could be added to the release schedule.

1. Previously, only a general quarterly business review (QBR) was conducted with the client. The project team initiated a new QBR process specific to productivity tools, which was highly appreciated and proved valuable, helping the client gain visibility with product leadership.

2. Held quarterly discussions on the video conferencing tool’s engineering plans, product designs, and additional feature roadmaps, to inform the client of upcoming features expected over the next quarter.

3. Organized meetings between client leadership and the product manager for video conferencing hardware to discuss a new hardware product line designed to address many of their audio hardware requirements and preferences.

Impact

The analysis identified three primary areas for further review, with an estimated potential savings of over $106,000 in annual recurring revenue. Key impacts and ongoing implementations included:

• Analytics Cost Reduction: Analytics expenses were reduced by approximately $13,000 per month between July and September through the implementation of best practices and a query observability dashboard. This enabled more efficient usage, allowing the organization’s analytics activities to resume organic growth from a more sustainable baseline.

• Compute Savings: Compute costs saw a monthly reduction of $6,000 as a result of commitments initiated from December through February, with further optimizations underway.

• Analytics Slot Management: Slot management for analytics emerged as the next area of focus, with initial analysis already in progress to unlock additional efficiencies.

The conclusions were reached through a comprehensive approach:

• Best Practices Workshop: Conducted a workshop focused on best practices for analytics to educate the customer’s team on optimizing their usage and managing costs effectively.

• Cost Optimization Report: Developed a detailed cost optimization report by performing an in-depth analysis of their current workload sizes, data pipelines, and infrastructure costs.

• Extensive Questionnaire: Administered a thorough questionnaire covering use cases, workloads, compute shapes, and specific requirements, ensuring a complete understanding of data landscape.

Lessons Learned

• Cost Visibility and Education: While the company initially viewed analytics costs as a significant concern, much of the cost optimization was achieved by educating users and creating visibility into query costs. This approach empowered users to make more cost-conscious decisions, effectively reducing unnecessary usage.

• Prioritization and Alignment: The customer had several areas of interest that were not necessarily high-impact in terms of actionable insights. The project team helped prioritize these interests based on spend analysis and cost optimization strategies, ensuring the customer understood the impact of each product while noting additional areas of interest for future exploration.

• Compute Optimization: Compute presented the largest opportunity for actionable insights, particularly given spend in container and virtual machine environments. However, the optimization process required significant research and education to build customer confidence. A Compute Commitments Bootstrap Guide was established to streamline this process for similar customers, equipping project teams with a structured approach for clients new to commitment-based cost-saving strategies.