RESULTS
Increased
Productivity
0 %
Improved
Accuracy
0 %
Ability to
Scale
0 %
Automating the Entry of Customer Orders
SphereGen Case Study
For a Connecticut manufacturer, the creation and entry of orders into their ERP system was tedious, time consuming and only able to scale by increasing the number of staff assigned to the task.
By using Intelligent Document Processing with AI and Machine Learning, SphereGen was able to electronically process customer POs and pull all necessary data to automate 80% of Order Entry transactions for their largest customer and about 50% for all other customers. As the AI training continues, these numbers will increase.
As a result, the challenge of scaling order creation has been resolved and quicker processing allows for order shipment to be accelerated, improving customer satisfaction. Time spent on data entry can now be focused on improving customer experiences.
Automating the
Entry of Customer Orders
SphereGen Case Study
For a Connecticut manufacturer, the creation and entry of orders into their ERP system was tedious, time consuming and only able to scale by increasing the number of staff assigned to the task.
By using Intelligent Document Processing with AI and Machine Learning, SphereGen was able to electronically process customer POs and pull all necessary data to automate 80% of Order Entry transactions for their largest customer and about 50% for all other customers. As the AI training continues, these numbers will increase.
As a result, the challenge of scaling order creation has been resolved and quicker processing allows for order shipment to be accelerated, improving customer satisfaction. Time spent on data entry can now be focused on improving customer experiences.
O V E R V I E W
Our client relied on a manual process to build their customer orders. Purchase orders are retrieved from email and appropriate data gathered for entry into their ERP system. This process was time consuming as each customer has a different PO format and multiple lookups were required to confirm pricing, item availability and shipping information. They needed a solution to increase efficiency and provide the ability to scale.
Challenge
As our client’s business grew and the number of orders to be processed daily increased – the tedious, manual process of Order Entry could not scale without increasing staff assigned to the task. In addition, lack of staff to process the orders was ultimately affecting order turn around time. Our client needed a solution which improved the efficiency and scaling of order entry processing.
SOLUTION
Intelligent Document Processing (IDP) with AI and Machine Learning was employed to process customer purchase orders. As POs are received electronically, IDP retrieves the necessary order information and creates the order in the ERP system. The original PO is attached to the order. If the order cannot be created due to unavailable stock, shipping issues, or not enough information present to create the order – the order is flagged and written to a report for review.
The automation can run 24/7 if needed, to handle all incoming orders. If there is a surge in orders, the automation handles the increased processing requirements. Overall productivity has increased as less time is spent on manual data entry.
THE DETAILS
In developing the Order Entry automation, there are multiple steps in understanding the current process, defining actions and training AI to produce the desired results.
Researching Purchase Order Formats for Data Extraction
Our client’s Order Entry process currently encompasses over 85 different styles of purchase orders. Therefore, a key step in researching data extraction was identifying business rules for retrieving data. One of the most complicated extractions involves determining the shipping address, as many POs have multiple addresses within their layout – and may also have multiple locations for shipping.
Training the Automation Digital Worker
Based on the PO format, business rules were identified and used to train the digital workers. Training with input and feedback builds the confidence level of the digital worker in correctly reading, processing and translating each PO format. The goal of the training phase is to achieve a high degree of success is processing the documents.
Creating the Order/Flagging Exceptions
When a PO is processed from an email queue, the ERP system is accessed for order entry. Each line item is evaluated and data extracted to build the order. If all data is processed successfully, the order is created and written to the ERP. The original PO pdf is attached to the order.
If any of the following errors are encountered during the order creation process, the order is flagged and moved to a report for review:
- Not enough data could be extracted from the PO to create a valid order
- An order quantity is not in stock
- The order cannot be delivered within the desired date range
- The correct shipping address could not be determined
Human Review of Results
When working with AI, it is important that human oversight remain an important step in all workflows. When training the digital worker, staff input is extremely important in identifying translation errors and providing adjustment corrections.
Once the automation is in production, order reports are spot checked for accuracy and all error reports are reviewed and orders reworked for correction.
CONCLUSION
By using Intelligent Document Processing (IDP), our client was able to automate the entry and creation of about half of their customer orders. With AI being continually trained, this number should improve. As a result, they were able to recognize the following benefits:
- Less Data Entry/Increased Productivity and Accuracy – With automation, the amount of data entry and time required to manually input data has significantly decreased, improving accuracy and productivity. This allows staff members to task shift and turn their efforts on work which brings more value such as focusing on the customer.
- Ability to Scale – Automated digital workers now handle the majority of customer order creation. If orders surge or grow exponentially, digital resources can be increased to handle order volume. This allows our client to more quickly scale to meet demand.
- Improved Employee Experience – With less time performing the tedious work of entering data and fixing errors, staff can now engage with more challenging work, increasing job satisfaction.
Using Intelligent Document Processing in an automated workflow is a powerful AI tool to positively impact process productivity and efficiency, however there are multiple ways AI can make a difference in your organization. If you have any questions regarding AI or IDP and its benefits, we would be happy to discuss any potential opportunities for automation you may have!
SphereGen is a unique solutions provider that specializes in AI and Intelligent automation, cloud-based applications, and custom web/mobile apps. We offer full-stack custom application development to help customers employ innovative technology to solve business problems.
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