GFL Environmental Inc. operates within the environmental and waste management sector, focusing on innovative solutions to improve sustainability. Their challenge arose from an inability to efficiently analyze customer satisfaction data from Microsoft 365 training webinars hosted on GoTo.com. These training sessions, aimed at improving employee proficiency in tools like Teams and SharePoint, were critical to their internal operations.
However, manually compiling data from GoTo.com into usable reports was a time-consuming and error-prone process, preventing GFL from gaining timely insights. They turned to Allston Yale, a trusted Data Analytics Consultant, to bridge this gap and deliver actionable insights.
The primary goal of the project was to create a comprehensive Data Visualization solution that allowed GFL to quickly assess participant satisfaction and attendance across all webinars. Specific objectives included:
- Enabling data-driven decision-making about future training initiatives.
- Validating the return on investment (ROI) for their webinar resources.
- Providing a clear view of customer feedback to inform strategic business planning.
Nestlé required a demand forecasting system capable of accurately predicting finished goods demand 78 weeks in advance. The system needed to function seamlessly across six product hierarchies while ensuring forecast roll-ups and roll-downs maintained a 99.99% accuracy rate. With such high precision required, traditional forecasting methods and manual processes were not scalable.
Furthermore, Nestlé needed a way to integrate historical sales data with anticipated demand trends to prevent stockouts, reduce overproduction, and optimize inventory levels—all while keeping their supply chain responsive and efficient.
To overcome these challenges, Nestlé turned to Allston Yale, a trusted Data Analytics Consultant, to design a scalable, automated forecasting solution that would streamline their operations and improve decision-making.
