CHALLENGE:
One central team forecasting for 800 entities
This company serves a uniquely complex healthcare market by delivering care both in patients’ homes and at its own facilities. Over time, the company grew rapidly through acquisitions, creating a highly fragmented structure with hundreds of individual entities. Each of these entities contributed to the overall financial picture, but the finance team struggled to bring all this information together in a meaningful way.
For forecasting, their finance team used Excel to consolidate 20 million records accumulated over 2 years. The sheer volume of data also meant the team couldn't forecast or control assumptions at the level of detail it needed to. This limited the accuracy of their forecasts and reduced confidence in decision-making.
At the same time, collaboration posed a major challenge. The company had hundreds of stakeholders, yet forecasting remained a centralized process. The finance team created forecasts on behalf of all entities instead of enabling each business unit to contribute. This led to misalignment between corporate expectations and on-the-ground realities. It also slowed down planning cycles and made it difficult to respond quickly to changes.
The healthcare company needed a solution that could better handle large volumes of data, involve more stakeholders, and create more flexible and accurate forecasts. To achieve this, they partnered with Spaulding Ridge.
SOLUTION:
Scenario planning and forecasting at a granular level
To address these challenges, we built a new forecasting solution using Sigma, working on top of the company’s existing Snowflake data platform. The goal was simple: create a system that could handle scale while remaining easy for business users to adopt.
We first recreated the company’s existing financial workflows in Sigma. We then built a dynamic profit and loss (P&L) view that allowed users to switch between GAAP and non-GAAP reporting formats. This gave stakeholders flexibility without changing the underlying data structure.
Next, we introduced a much more flexible approach to forecasting. Instead of relying on a single central model, the new solution allowed users to adjust assumptions at a granular level. For example, each entity could define its own expected growth in patient visits or other operational drivers. These inputs directly shaped the forecast, making it more realistic and tailored to local conditions.
Our team also added scenario planning capabilities. Users could create multiple forecasts, such as optimistic, pessimistic, or baseline scenarios, and switch between them easily. Unlike Excel, where teams often worked in separate files, Sigma brought everything into one shared environment. This allowed different teams to collaborate, compare ideas, and align on the best plan.
To support adoption of the solution, we included features that made it easy to use, including clear instructions, tooltips, and a built-in data dictionary. These elements helped users understand the numbers and reduced the need for training. The result was a self-service tool that scaled across the organization.
Finally, the solution allowed users to save and revisit forecasts. When a user finalized a forecast, the system stored it in Snowflake and made it available for future comparisons. This enabled teams to track changes over time and learn from past decisions.
RESULT:
A scalable, collaborative, and data-driven forecasting
The new solution transformed how the company approached their financial planning. The solution brought together large volumes of data, enabled real collaboration across teams, and gave stakeholders the flexibility to build and compare forecasts with confidence. As a result, the organization now operates with greater clarity, speed, and alignment in its planning process.
- Teams significantly reduced manual effort, saving hundreds of hours each quarter by automating data consolidation and reporting.
- Forecast accuracy improved, as users can now leverage detailed data and adjust assumptions at a granular level.
- The solution expanded access from a small finance team to hundreds of users across the organization, enabling broader participation in forecasting.
- Collaboration strengthened, with entity leaders and finance teams working together in one shared environment instead of isolated Excel files.
- Planning cycles became faster and more efficient, allowing the organization to respond quickly to changes and growth opportunities.
- Stakeholders gained better visibility into performance, with clear, interactive dashboards and easy-to-understand metrics.
Beyond these measurable outcomes, the project also represents an important milestone. We used Sigma to go beyond reporting and support advanced financial planning. As one of the first implementations of its kind, this solution sets the foundation for similar transformations in other organizations.
