Driving Manufacturing Innovation with QAD Labs Applied Collaboration
For nearly two years, QAD has been collaborating and experimenting with customers in the QAD Labs. QAD Labs is not a physical place with scientists in white lab coats. Instead, it is a virtual combination of people, technology and passion for addressing the challenges of manufacturing planning and operations. The guiding force behind QAD Labs is the collaboration between QAD and our customers and the experimentation efforts that follow. The collaboration involves experimenting with advanced technologies to address legacy or emerging challenges. And experimentation is not hindered by the large budgeting cycles of major projects. By design, the QAD Labs approach allows for rapid application evaluation and strategic pivots to build on success or investigate alternatives.
Robotic Process Automation (RPA) Use in Manufacturing
Some of the most recent experimentation has been aligned with Robotic Process Automation (RPA). RPA is a method of automating repetitive routing tasks through mimicking the activity a human would typically carry out on a screen to perform such tasks. Manufacturers can benefit from this technology by using it for any manual processes or repetitive tasks that involve an application or manual data entry.
RPA Drives a More Efficient Harvesting of Order Data
QAD is working in the Labs with a well-known tier one automotive supplier to develop an RPA-based approach to a data collection challenge. The tier one supplier receives information relevant to demand from the various automotive OEMs in a variety of ways. In some instances, the data is provided through well established EDI. Alternatively, there are scenarios that require the tier one supplier to periodically log in to an OEM portal and manually check for supporting information, orders and/or change in demand. This information then has to be transcribed and transferred into the appropriate QAD Adaptive ERP functionality. RPA is being used to automatically log in to the OEM system, check for relevant information, automatically collect the information in digital form and finally input the information into the ERP.
This RPA approach has some clear advantages to the manual approach. The automated process can be scheduled to repeat as often as necessary, assuring that none of the critical information is missed due to holidays or employee absence. The automated process delivers the highest level of data integrity without the risk of transposed digits or other common manual data entry errors. The automated process can also free up personnel to perform higher value-added tasks. The tier one automotive supplier can use variants of their RPA approach to harmonize data from multiple OEMs and avoid over-customization of their own systems.
Improving Finance Processes with RPA Collaboration and Experimentation
As part of the QAD Labs effort and collaboration, it was essential to evaluate a number of RPA vendors and associated approaches. QAD engaged its own finance team as part of the process. The finance team welcomed the idea of collaborating in support of the customer and, like most finance functions, have no shortage of complex and diverse data sources in terms of their day to day business activities. RPA toolsets were used in developing approaches to journal postings and data migration activities. QAD will benefit from an RPA approach, but most importantly the QAD Labs environment allowed for the comparison of RPA tools and approaches that can be applied more broadly to our customers.
Collaborate and Experiment with Us in the QAD Labs
QAD is always looking for additional lab partners! Whether the activity is centered on machine learning, IoT, RPA or other emerging technology, QAD is providing a platform and resources to jointly move our customers’ capability along. If you have a need or an idea for experimentation around advancing technology, then please let us know at QAD_labs@qad.com. And if you plan on joining us in Las Vegas for QAD Explore, look out for a special QAD Labs session focused around RPA and its use in a manufacturing environment.