Efficient order processing: from manual processes to AI-supported automation

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In a world where speed and efficiency can make the difference between success and standstill, optimising business processes is crucial. One area that often takes up time and resources is order entry and processing, especially when done manually. In this article, we take a look at the traditional manual process of receiving orders by email and manually processing them through to the ERP system, before looking at the benefits of an automated version using artificial intelligence (AI).

Manual process for incoming orders

Step 1: Incoming emails — The process begins with the receipt of orders by email. Employees must review each incoming email, identify the order and manually extract relevant information.

Step 2: Manual data entry — Once the order has been identified, employees must manually enter the data into the ERP system. This step is error-prone and time-consuming as it requires accurate recording and transfer of information.

Step 3: Review and approval — After data entry, orders must be manually reviewed and approved to ensure that all information is correct and complies with company policies.

Automated process with AI

Step 1: Incoming emails and data extraction — In the automated version, AI is used to analyse incoming emails and automatically extract relevant information. This is done with the help of AI-supported document understanding, which is used to understand the content of the emails and identify the required data.

Step 2: Data integration into the ERP system — The extracted data is seamlessly integrated into the ERP system without manual intervention by employees. This not only reduces the susceptibility to errors, but also speeds up the entire process considerably.

Step 3: Automatic checking and approval — Based on predefined rules and algorithms, the AI can automatically check and approve the orders. This minimises human error and shortens the processing time.

Benefits of automated order processing

Automated order processing has many benefits. Here are a few examples:

• Cost/time savings: Automating incoming orders significantly reduces processing time, as manual data entry is no longer necessary
• Process acceleration: Processing is carried out in real time or without latency. This enables a 24/7 service
• Error reduction: The use of AI for data extraction and integration minimises human errors that can occur in manual processes
• Scalability: Automated processes are scalable and can be easily adapted to increasing order volumes without requiring additional resources
• Real-time monitoring: Automation allows companies to track the status of their orders in real time and proactively address bottlenecks or delays.

Overall, automated order processing with the help of AI offers numerous advantages over traditional manual processes. By optimising incoming orders, companies can increase their efficiency, reduce costs and strengthen their competitiveness.

Example from practice

A practical example from one of our projects clearly shows the potential of automation. The process goes through further steps here. Incoming emails are first classified according to whether it is an order at all, as it cannot be ruled out that any replies, enquiries or complaints will also end up in the monitored mailbox. These must first be sorted out. The data from the incoming emails is also enriched with additional data from the ERP before the employees carry out a check. The following diagram shows the process in simplified form:

In this project, we had the task of reducing the workload of an 8-person sales support team. This team had to process an average of 500 emails per day as pure incoming orders and manually transfer them to an ERP system. The average processing time for an order was therefore around 7.5 minutes. By reducing the workload, the team should finally be able to concentrate on “higher-value” tasks. Fluctuation in the team was very high due to the very monotonous task and replacements were time-consuming due to the unattractive nature of the work.

With the help of the system outlined above, we succeeded in reducing the average processing time to less than 2 minutes, despite an additional quality control. This corresponds to a reduction of over 70%.

· All the customer’s business benefits summarised:

· Relief of the team by >70%

· Additional quality assurance

· Team free for “higher-value” work

· Team can handle peaks in incoming orders without problems

· Higher team satisfaction, reduced fluctuation

The successful implementation of this automation system shows once again how effectively the use of modern technologies can not only increase efficiency, but also significantly improve the quality of work and employee satisfaction.