AI-optimized supply chain efficiency and load management

Adapting supply chains to evolving conditions is crucial for manufacturing success. Efficient load planning reduces expenses and fully utilizes truck space. Before, businesses used Excel spreadsheets and macros to manage stock-keeping units (SKUs). However, manual data entry restricts adaptability and decreases efficiency. It also poses challenges in achieving diverse goals across multiple locations. Usually, manual planning prioritizes one goal, like revenue or profit, and coordination between various locations and objectives is challenging.

Despite having access to basic data, our client, an apparel manufacturer, needed a more rapid, optimized, and efficient processing method. They aimed to tackle gaps, margins, and revenues while reducing the number of SKUs per shipment. To achieve these goals, the client needed to conduct multiple processing rounds each day.

Streamlining truck allocation for cost efficiency

The client’s supply chain was burdened by the complexity of scheduling and allocating trucks manually. This not only slowed down operations but also led to inefficiencies and increased costs. They needed an automated system to optimize truck allocations and streamline the process.

Elevating customer service through timely deliveries

Improving customer service was paramount. The client needed to ensure timely and accurate deliveries to keep customers happy and loyal, spurring the need for an integrated real-time tracking and updates system.

Boosting operational efficiency with agile data analysis

The client’s existing data analysis methods were slow and cumbersome. This hindered the quick identification and resolution of inefficiencies in the supply chain. They needed a solution offering fast, simplified data analysis to guide decision-making.

Drawing upon our expertise in supply chain management, we started the project with discovery sessions to pinpoint our client’s unique challenges. Through this process, we identified and applied advanced optimization techniques. These were tailored to address specific constraints and achieve various goals.

What we provided

AI-driven solutions for enhanced user understanding</p>

SKU prioritization

We implemented a sophisticated system for efficient product data management. This system categorizes products into groups and priorities, facilitating advanced processing. It enables easy organization and prioritization of products for swift placement in loads according to customer requirements.

Our solution empowers users to customize load planning manually, allowing complete flexibility. Users can adjust SKU placements or remove loads as necessary, freeing up time for decision-making and execution instead of routine data processing.

Scenario planning

After implementation, our clients could plan loads to meet multiple objectives simultaneously. Thanks to the multi-objective optimization capability, prioritizing items within a load at either the service or item level became more efficient. This approach represents a departure from previous load planning methods, improving efficiency for both standard and unique shipment scenarios.

Load optimization

Our solution uses SKU details and load objectives to create optimized recommendations tailored to each user’s priorities for every run.

These recommendations help operational teams plan truckloads that meet customer demands and align with operational capacities. Additionally, data from each task is saved for review, enabling business leaders to analyze performance and make informed decisions.

This comprehensive suite of solutions equips our client with the tools for effective data management, scenario planning, and load optimization, leading to significant improvements in efficiency and decision-making.

The immediate impact