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Implementation of Field Service Management
System for the Telecom Provider Company

AWS
Google Analytics
Net
SendGrid
SQL Database

Overview

One of the prominent telecom providers aimed at improving its field service functions so operational efficiency, cost effectiveness and client satisfaction improves. The company employs more than 10,000 field technicians. It encounters scheduling problems, communication problems, and problems in service delivery. We designed and delivered a bespoke FSMS (Field Service Management System) to facilitate these processes, make them more efficient, address the integration issue, and provide the company with operational intelligence.

PROBLEMS:

SOLUTIONS

Intelligent Scheduling and Dispatch System

◉ Created an AI system that automatically allocated tasks by proximity to the technicians based on the workload and skillsets.

◉ Added GPS based dynamic routing to minimize travel time and heat usage costs.

Technician Mobile Application

◉ Developed an app for technicians to easily find job, client and diagnostic information.

◉ Proposed implementing offline mode for those areas with poor connectivity.

◉ Allowed for online signature and photographic evidence of the work done by the client.

Proactive Maintenance Integration

◉ Deployed IoT Sensors throughout all the network’s infrastructure to identify possible future problems.

◉ Utilized Predictive analytics model to estimate when a disruption would occur and how it could be avoided.

◉ Set up automatic ticket creation for maintenance tasks that require immediate attention.

Customer Engagement Portal

◉ The very first application offered by the Company is the creation of a web portal which allows clients to monitor the location of technicians, the estimated response time and updates on real time when the job itself is done.

◉ The system allowed automatic reminders to be sent out for appointments made, appointments that have been delayed, and appointments that have been completed.

◉ There was a feedback administration added to the system to solicit information from customers and obtain their feedback on issues.

Data Analytics and Reporting Dashboard

◉ Dashboards were created to enable the monitoring of SLA compliance as well as measuring technician activities and the rate of completion of the job.

◉ Tools for root cause analysis were incorporated to help diagnose and fix service problems that occurred frequently.

◉ Insights were also provided for planning workforce and predicting demand supply.

RESULTS

  • Enhanced Operational Efficiency

    ◉ 25 percent cutback in travel distance: Efficient scheduling and planning of routes ensured that the distances travelled by the technicians are as short as possible.
    ◉ 15 percent increase in the daily workload: More jobs a day were possible because of increased efficiency of operations.

  • Improved Service Reliability.

    ◉ 40 percent decrease in downtimes: In a great portion, the combination of preventative maintenance and timely problem detection facilitated the avoidance of some network outages.
    ◉ 30 percent increase in first time fixed rates: Due to improved accessibility of diagnostics and inventory, repeat visits were reduced.

  • Higher levels of customer happiness

    ◉ The introduction of real-time updates and transparency led to a 20% increase in overall customer satisfaction scores.
    ◉ Fewer no-shows and improved communication helped lower complaints from customers.

  • Data-Driven Decision-Making

    ◉ Management leverage with advanced analytics allowed management to pinpoint one element of organization that is drawing from resources without the need of an immediate solution for it.
    ◉ The company used predictive models to anticipate surges in demand to scale up operations quickly.

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