Introduction

In the dynamic world of aerospace distribution, Proponent has established itself as a leader, boasting 50 years of industry expertise. As the largest independent aerospace distribution company globally, Proponent places a strong emphasis on delivering value to its customers and suppliers by optimizing their supply chains. As Proponent's reputation grew, so did the number of product quotation requests from airline companies, their primary customers.

Machine Learning's Impact on Proponent's Quotation Process

To improve Proponent’s existing quoting system and be ready for the upcoming future, JAVRA proactively initiated the use of Machine Learning in the quoting process. The goal was to simplify and enhance the quotation process by leveraging automation and machine learning technologies. This solution would be capable of automatically scanning and analyzing customer email information and extracting critical details like part numbers, quantities, and customer requirements. Upon implementation, the new software transformed Proponent's workflow. Incoming customer emails are now automatically sorted and classified based on their purpose, primarily quotations. The machine learning program within the software then scans the email contents, extracting relevant information to streamline the response process. The software seamlessly integrated with Proponent's quoting application platform, creating accurate and readyto-send quotations within seconds.

Figure: Quotation Process

While the software significantly expedited the quotation process, it also had built-in checks to ensure accuracy. In cases where the machine learning program flagged uncertain information, the email would be assigned to a quoting specialist for manual analysis and resolution. This hybrid approach combined the efficiency of automation with the expertise of human analysis, further improving the overall process. The implementation of Machine Learning yielded exceptional results.

Javra's Next Phase in Advanced Quotation Automation

Building on the initial implementation's success, next phase of the project is in development, which is expected to extend the software's current functionalities, leveraging machine learning algorithms to automate and optimize the quotation process even further by streamlining the identification of the email's purpose. In other words, the aim is for the software to automatically generate and dispatch precise quotes to Proponent's clients with the utmost speed and accuracy. By staying at the forefront of technological advancements, Proponent remains poised for sustained growth and continued success in the aerospace industry.

Machine Learning Success Result at Proponent

In summary, the implementation of the Machine Learning software proved to be a resounding success. By implementing the innovative software solution, Proponent revolutionized its customer quotation process, overcoming the challenges of a rapidly growing request volume.

JAVRA embraces its mission to deliver exceptional solutions through innovation and creating a lasting impact. Introducing Machine Learning in the quoting process brought a remarkable transformation in the quoting process. The software's ability to analyze customer emails, generate accurate quotes, and seamlessly integrate with Proponent's existing systems propelled the company to new heights of success. By leveraging innovative technologies and prioritizing customer satisfaction, Proponent stands out as a leader in the aerospace distribution industry, cementing its reputation as a reliable and forward-thinking partner for airlines worldwide

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“JAVRA has been a great partner for us, and this application of machine learning to our quoting process is just one example. They brought the idea to us after understanding the pain points in our quoting process, and then worked along-side our team to successfully deliver results. We can’t wait for the next enhancements! “

 

John Valantine 
Chief Information Officer, Proponent