SRM Tech partnered with a specialized 3PL service provider serving retail and direct-to-consumer businesses to develop a sophisticated demand forecast engine that improves operational efficiency, eliminates spend leakage, and improves delivery SLAs.
Business Goals
- Throughput per Labor Hour (TPH) for fulfillment operations measuring labor productivity has decreased significantly.
- Increased instances of split shipments and higher frequency of DC-to-DC transfers leading to high transportation costs.
- Higher storage spending due to excess inventory holding.
- Plummeting customer experience ratings because of frequent shipment delays.
Solution
Key Highlights
- Focusing more on data hygiene and decision quality, we analyzed and introduced improved and relevant parameters such as historical sales, sale prices, promos, discounts, product characteristics, market trends, seasons and weather patterns.
- We designed and trained an ML model with new and rich data sources and delivered a more accurate and scalable predictive modeling tool.
- Leveraging this new demand forecast engine, the 3PL brand now has solid decision-making tools at its disposal and has scaled its daily operations to be more efficient and high performing.
Outcomes
- Improvement in forecast accuracy by 37%.
- Throughout per Labor Hour (TPH) increase of 4% resulting in lower cost per unit (CPU).
- 12% reduction in order shipment-related SLAs.
Technologies Used: ML engine, Python, SQL, Streamlit
Are you experiencing similar challenges in forecasting, inventory management, capacity planning, or labour productivity? Our expert team would be happy to extend assistance and deploy our solution accelerators to deliver value across your supply chain journey.
Drop in your enquiry here or email us at dpsales@srmtech.com!