At Dar, an Average of 40,000 Reports Annually Are Received via Email, Phone, and Apps
Dar, the waste management company serving Nijmegen and its surrounding areas, handles between 40,000 and 50,000 reports each year. These reports range from requests for waste passes to complaints about missed containers and road slipperiness.
Decision Tree Implementation
Lindsey de Beer, a master's student in Data Science at Radboud University, conducted a data analysis to examine reports from residents and the municipality. Using AI and a decision tree, she was able to accurately identify repeat reports. This method proved to be much more efficient than manual approaches, which only detected ten percent of repeat reports. AI enabled the accurate labeling of these reports, leading to a significant improvement in service quality.
Language Recognition
In addition to the decision tree, Lindsey worked on identifying complaints through language recognition. Although Dar did not yet have sufficient specific data to fully implement this, a foundation was laid for future improvements. Collecting more textual data will aid in developing an effective algorithm capable of better recognizing complaints.
Enhanced Customer Satisfaction
Thanks to the collaboration with MKB Datalab-Oost, Dar NV is now working towards achieving an even higher level of customer satisfaction. By acting more swiftly on urgent reports, Dar aims to prevent complaints and enhance its overall service.
Learn More
For more information on how your company can benefit from similar projects, please contact MKB Datalab-Oost.
