Artificial Intelligence Real-Time Analytics for Efficient OTIF Performance in Complex Supply Shains

Related Vendors

FAULHABER Drive Systems

Wuxi InfiMotion Technology Co., Ltd.

How long do you need to determine the cause of non-compliance with the OTIF (On-Time In-Full) requirement and assess the impact on the global supply chain?

The supply chains of large manufacturing companies are extremely complex due to their global distribution and deep vertical and horizontal integration. In addition, external factors such as trade conflicts and wars are increasingly disrupting operations in unpredictable ways. Nevertheless, customers expect on-time deliveries in the right quantity and quality.

The causes of OTIF failures or deviations are difficult to identify, and even when they are identified, their impact on the supply chain often remains unclear. This is due to the fact that many companies still rely on manual, isolated analyses, which hinder both a holistic overview of the supply chain's performance and its ability to respond to disruptions.

In addition, the complexity of processes and the sheer volume of process data make it difficult to identify inefficiencies and cost drivers—which often leads to reactive, suboptimal decisions and missed opportunities for improvement.

Getting A Grip on OTIF Performance

For our client, a leading global provider of electrification, connectivity and automation solutions, we implemented an AI-powered, Celonis-based analytics solution that provides end-to-end visibility across the supply chain, enabling optimization of the OTIF metric.

By integrating data from sales, production and procurement into intuitive dashboards, the solution provides a cross-functional and cross-system view of OTIF performance with the underlying causes and effects. This enables the company to make targeted, data-driven decisions and drive continuous improvement initiatives.

Supply Chain Analytics Cockpit: The analysis cockpit consists of a total of seven modules that are supported by AI. Each module has its own focus and enables users to work on specific questions or problems in the context of holistic OTIF optimization.

Dashboard "OTIF Overview": The OTIF Overview dashboard provides a near real-time overview of delivery performance in sales, production and procurement. It provides both aggregated overview statistics and detailed information that teams can use to monitor development trends. Orders are categorized into groups such as "too late" or "too early" for performance segmentation.

The calculation basis can be flexibly configured in terms of time stamps and tolerances. If critical performance thresholds are exceeded, AI-based alerts can be sent to relevant stakeholders, enabling fast and targeted responses.

Dashboard "Production Overview": The dashboard for production supports OTIF performance analysis by dimensions such as plant, material group or order type with trend visualizations that are aggregated over adjustable time intervals.

Users can break down specific sub-areas down to individual production orders in order to identify causes and derive more in-depth insights. These functionalities are equally available for sales and procurement.

Network Root Cause Analyzer: Causes of OTIF deviations within the supply chain or network can be identified with the Network Root Cause Analyzer. Delays can be traced along the document chains, which include sales, production and procurement. The module offers a multi-level view of the supply chain network, displays order relationships in detail and shows exactly where bottlenecks exist.

Network Impact Analyzer: The Network Impact Analyzer evaluates how disruptions affect both upstream and downstream stages as well as supply chain stakeholders. Once a cause has been identified, the module visualizes the affected orders, customers, plants or other network dimensions. This enables well-founded, targeted measures such as the rescheduling of orders, the notification of stakeholders or the redistribution of resources. This ensures greater robustness against disruptions.

Network Explorer: The Network Explorer provides an interactive, visual representation of document and material flows along the entire supply chain. It helps users to understand the relationships between plants, subsidiaries and production units. This allows dependencies to be shown, for example how a delayed production order affects several customer deliveries.

Resource Utilization Analyzer: The Resource Utilization Analyzer provides a comprehensive overview of the utilization of production resources within the network. It enables the identification of bottlenecks or unused capacity that could affect OTIF performance. The module highlights capacity discrepancies by linking them to specific production or planned orders.

AI layer: The cockpit has three AI components to provide the user with the central functionalities.

• Mapper: intelligently links documents across systems and plants to create a consistent network overview
• Categorizer: dynamically assigns performance categories to each order, allowing OTIF performance to be tracked and evaluated at different levels of aggregation
• Calculator: determines resource utilization on a daily basis by comparing demand and supply for production capacities

Advantages

With the cbs Supply Chain Analytics Cockpit, the causes and effects of anomalies in the supply chain can be identified within 120 seconds. This transparency enables companies to make quick, fact-based decisions and take effective countermeasures.

This minimizes delivery delays, increases customer satisfaction and significantly reduces avoidable operating costs. These improvements can lead to an increase in OTIF performance of up to 35%. By using AI-powered supply chain analytics, manufacturing companies can move from reactive troubleshooting to proactive, data-driven performance management.

Nils Kleiber is Senior Consultant BPM & Analytics at cbs Coropate Business Solutions

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