MANUFACTURING
DATA DRIVEN FIELD SERVICE MANAGEMENT SOLUTION IMPACTING MASSIVE REVENUE LOSS OF 100,000 A YEAR ON REACTIVE AND SCHEDULED SERVICES
About the Client
American coin and dollar counting machine manufacturer and distributor serving to 1500+ Banks across North America.
The Challenge
Client was managing Field service for all the Banks based on reactive and scheduled maintenance data. Despite of having 800+ field technicians, client was not able to give Smart Field service to their customers.
- Most of the inspections and maintenance are still done with pen and paper, putting an undue burden on field technicians to organize and ensure the accuracy of their handwritten results.
- Audit locations are selected randomly, without considering efficient travel routes, impacting the field technician’s productivity and effectiveness.
- With around 1500+ sites for various technicians and without data driven prioritization/scheduling, critical maintenance is not addressed in time.
What We Did
- Data Acquisition
- Data Cleansing
- Predictive Analysis
- Statistical Modelling
- Clustering
- Classification
- Machine Learning
- Enterprise App Development
- Data Acquisition
- Data Cleansing
- Predictive Analysis
- Statistical Modelling
- Clustering
- Classification
- Machine Learning
- Enterprise App Development
The Solution
With predictive analytics and ML based statistical modelling technique, client managed to offer premium SLA with predictive and prescriptive maintenance.
- Failure Prediction – Predict time of the next machine failure. This will ensure there are fewer emergency calls.
- Inventory Acquisition Prediction – Predict part(s) that will fail or wear out. The field technician will come over to the call site with the correct spare parts.
- Service Time Prediction – Predict the time it will take for a technician to complete the call.
- Smart Allocation – Suggest the most competent technicians for a given service call.
Results & Outcomes
DXFactor developed Smart Filed Service Management with Predictive Maintenance based on historical and real-time data to achieve Zero down time of Machines for all the Banks.
100%
uptime with Smart field services management.
98%
accuracy in predictive maintenance of machine based on data model.
85%
boost in Customer engagement for sign-off with Premium SLA.