Case studies

Accelerating forecasting workflows at a $12B global consumer goods enterprise

data modernization demand forecasting snowflake snowpark

$

in annual revenue supported with a scalable data platform

0 B

weeks to modernize forecasting pipelines on Snowflake

reduction in forecasting carryover times

0 %

Modernized forecasting workflows within a six week timeframe using Snowflake capabilities and Hakkoda accelerators.

Reduced carryover processing time to enable faster planning cycles.

Built a scalable, future-ready foundation for continuous forecasting improvements and AI deployment.

Challenge

A global consumer goods enterprise depends on accurate demand forecasting to align supply chains, control margins, and meet customer demand. Even small delays in operations can easily ripple into major operational setbacks with commensurate costs to the enterprise.

Unfortunately, their existing workflows were also struggling under the weight of inefficiencies. Forecast edits frequently became locked, and promotional elements were difficult to carry over smoothly. These challenges required costly manual intervention to rework and slowed down decision-making across the business.

At times, forecast carryover delays stretched beyond 48 hours. This lack of timeliness created significant bottlenecks, limiting the organization’s ability to respond to changing market conditions with confidence.

Solution

The client enterprise partnered with Hakkoda to reimagine its forecasting workflows on Snowflake. The goal was not just workflow optimization, but a complete modernization of myriad underlying processes. To that end, Hakkoda introduced proprietary project accelerators and advanced Snowflake capabilities, including dynamic tables and Snowpark, to help streamline the movement of data across the enterprise.

These tools allowed forecasting processes to run more intelligently and efficiently, eliminating downstream bottlenecks and accelerating critical decision-making capabilities. By embedding best practices in clustering keys, data parallelization, and workflow design, Hakkoda helped the enterprise shift from slow, rigid processes to fast, scalable, and flexible forecasting operations.

The re-engineered process delivered a 26% reduction in carryover time, translating into a measurable improvement in planning speed and execution. Beyond immediate efficiency gains, the new data engineering approach created a future-ready foundation, enabling the enterprise to continuously evolve forecasting processes as markets and technologies advance.