Digital Transformation in Cargo Handling: A Case Study on Forecasting and Planning Capabilities Enhancement
Technology Category
- Functional Applications - Enterprise Resource Planning Systems (ERP)
- Functional Applications - Inventory Management Systems
Applicable Industries
- Transportation
Applicable Functions
- Discrete Manufacturing
- Logistics & Transportation
Use Cases
- Demand Planning & Forecasting
- Last Mile Delivery
Services
- System Integration
About The Customer
The customer is a leading provider of cargo and load handling solutions with a global presence. They are committed to becoming a leader in sustainable and intelligent cargo handling. Their business model is configure-to-order, with a sales cycle that varies between 3 to 6 months and an order-to-delivery time between 2 to 4 months. The company is focused on implementing digital transformation throughout their end-to-end supply chain to drive efficiency, with a particular emphasis on speed, automation, real-time data, and transparency. They aim to optimize their logistics and reduce inventory through improved forecasting and planning capabilities.
The Challenge
The case study revolves around a leading provider of cargo and load handling solutions aiming to become a leader in sustainable and intelligent cargo handling. The company embarked on a global initiative to implement digital transformation throughout their end-to-end supply chain to drive efficiency, focusing on speed, automation, real-time data, and transparency. However, they faced significant challenges in their business scope. Firstly, they lacked proper forecasting capabilities, relying heavily on their order book for decision-making. Secondly, their configure-to-order business model resulted in a sales cycle varying between 3 to 6 months, with the order-to-delivery time between 2 to 4 months. The company aimed to reduce this lead time to increase customer satisfaction. Lastly, the absence of planning tools led to issues with the finance team, who could not comprehensively view the order lifecycle and the associated revenues.
The Solution
The company implemented o9’s Digital Brain to address their challenges. This provided them with a holistic view of all relevant sources of demand planning, shared across all stakeholders and external dealers in a collaborative workflow. This improved their forecasting capabilities significantly. To reduce the delivery lead time, they used o9 to derive the configured product group forecast and key component demand by analyzing potential scenarios and using a bill of materials to plan component orders and inventories. For their planning capabilities, a demand plan based on quantities was easily transformed into a revenue plan considering leasing contract durations of the orders. o9 provided truly end-to-end planning software, including Demand Planning, Supply Planning, S&OP, Control Tower, Inventory Planning, and Production scheduling. The o9 Digital Brain was integrated with the ERP system (SAP HANA), the CRM (Salesforce), and the TMS (Oracle). A pilot on scheduling for discrete manufacturing was also deployed.
Operational Impact
Quantitative Benefit
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