Cost-to-serve

For a leading media technology client, understanding operational efficiency and cost-to-serve across clients and departments was a growing priority. However, the data required to produce meaningful KPIs and utilization metrics lived across multiple systems ranging from Snowflake and Salesforce to internal timesheets and ticketing platforms. Business leaders lacked a unified, trustworthy view to make informed decisions on resourcing, revenue alignment, and client profitability.

To solve this, I led the end-to-end development of a centralized data model and dashboard suite in Tableau, built to surface key Cost to Serve (CTS) and Resource Utilization insights. I began by consolidating disparate data sources spanning employee hours, revenue, client tier mapping, cost rates, and ticket-level activity into a clean, integrated flat file using Snowflake. This model brought together over a dozen Snowflake tables and Salesforce objects, standardizing employee and client identities, and aligning daily-level activity data to monthly KPIs.

Once the foundational data model was in place, I designed two interactive Tableau dashboards: one focused on CTS trends by client, department, and region; the other on employee-level utilization. The dashboards allowed stakeholders to drill from high-level outliers into specific client accounts, track FTE allocation, and identify which employees were over- or under-utilized, and on what types of work. Interactive filtering by department, date range, client tier, and location gave users the flexibility to tailor views to their needs.

Beyond surfacing trends, the dashboards enabled action. Business teams could now identify clients with unusually high CTS, uncover operational inefficiencies, and rebalance resources based on real-time insights. Embedded tooltips, info icons, and user-guided navigation created a seamless experience for non-technical users, while reusable calculated fields and dynamic date filters made the dashboards scalable and easy to maintain.

By replacing siloed analysis with a single, integrated platform, this solution transformed how the organization approached performance reporting. What began as a fragmented set of disconnected reports evolved into a trusted decision-support system, one that put data at the center of resource planning and client success conversations.