Background and initial situation

A large manufacturing company that operates globally is constantly dealing with a huge volume of procurement requests. The purchasing team spent a lot of time responding to queries regarding supplier data, order status and managing order processes. This not only led to inefficient workflows, but also to delays and an increased workload.

Aims of the project

The main objective of the project was to increase the efficiency of the purchasing department by automating recurring tasks and reducing response times for inquiries. Specific objectives included:

  • Automation of routine supplier and order status queries.
  • Reducing the processing time for procurement requests.
  • Improving transparency and efficiency in supplier communication.
  • Relieving the purchasing team of administrative tasks.

Solution implementation

To achieve these goals, the AI was integrated into the company’s existing purchasing and ordering systems. The implementation process was divided into several phases:

a) Needs analysis and planning:
  • Identification of the most frequent requests: By analyzing historical data, the most frequent requests were identified, e.g. regarding order status, delivery times and supplier availability.
  • Determination of integration points: The relevant systems, including the enterprise resource planning (ERP) system (e.g. SAP) and the supplier management system, were determined.
b) Development and integration:
  • Creation of call workflows: Development of specific workflows for automated processing of supplier data and order status.
  • Technical integration: The AI was seamlessly integrated into the ERP system and the supplier management system.
c) Training and knowledge database:
  • Data import and structuring: Historical procurement data and frequently asked questions were used to expand the AI’s knowledge base.
  • Regular updates: Planning regular updates to the knowledge base to ensure the relevance and accuracy of the information provided.

Application example and process scenario

Scenario: Request for order status

  • Step 1: An internal employee of the company asks for the current status of an order via the internal chat system.
    – Employee: “AI, can you tell me the current status of the order with the order number 789012?”
  • Step 2: The AI processes the request, searches the ERP system for the corresponding order number and retrieves the current status.
    – AI: “One moment please, I’m checking the status of your order.”
  • Step 3: The AI finds the current order status and informs the employee.
    – AI: “Your order 789012 was shipped on 01.10.2023 and is currently being delivered. The expected delivery date is 03.10.2023. Would you like to receive additional details or the shipment number?”
  • Step 4: The employee states exactly what they need.
    – Employee: “Yes, please send me the consignment number.”
  • Step 5: The AI communicates the consignment number and provides further relevant information on request.
    – AI: “The consignment number of your order is XYZ987654. You can check the status of your shipment with our shipping partner. Do you need any further information?”

Results and benefits

Following the implementation of AI, there were significant improvements in purchasing and procurement:

  • Reduced processing time: The average processing time for procurement requests was reduced by 60%.
  • Increased efficiency in the purchasing team: The purchasing team was able to concentrate on more strategically important tasks.
  • Improved transparency: Employees had access to up-to-date order and supplier data at all times.
  • Increased employee satisfaction: By automating repetitive tasks, the team’s workload was reduced.

Conclusion

The integration of AI into the company’s procurement processes led to a significant increase in efficiency and satisfaction for both internal employees and the purchasing department. By automating repetitive tasks such as answering frequent questions and tracking orders, valuable time was freed up and the quality of the procurement processes was significantly improved. Future enhancements could include the implementation of proactive notifications for order status changes and the use of advanced analytics tools to further optimize purchasing strategies.