The existing Field Service Management system was an internally developed application with significant limitations for modifications. The company struggled with manual ticket flows and notification processes, lacked standardized reporting and monitoring capabilities, and was integrated with non-strategic applications. The single data center solution created reliability concerns, while disparate business workflows and end-of-life architecture hindered operational efficiency and growth potential.
Eclantiqx implemented a comprehensive ServiceNow-based Field Service Management solution that managed the complete lifecycle of Work Orders and Work Order Tasks. The platform automated the creation, qualification, dispatching, and execution of off-site work requests. The solution established robust integration between end client systems and company resources to manage ticket lifecycles and parts dispatch efficiently. Field Engineers were systematically assigned to resolve tickets at customer sites, with appropriate role-based access for work order creation and management.
The organization suffered from a poor employee experience due to outdated, legacy applications that required employees to navigate multiple systems manually. The existing system not only slowed down the selling process but also failed to offer features that were relevant to individual customer needs. Furthermore, there was no efficient mechanism in place to maintain the relationship between a single customer and the multiple accounts they held, leading to a high churn rate and missed opportunities to upsell or cross-sell products
Eclantiqx implemented a transformative solution that leveraged intelligent next-best–offer technology. In this approach, call center executives (CCEs) received automated suggestions generated from a sophisticated application that analyzed customer profiles, geographical data, and nature of expenses. The solution was built on Pega 8.6 and integrated with a Python-based data processing system and Tableau for business intelligence, enabling the backend marketing team and data scientists to continuously refine the offer engine. This multi-channel approach also supported call center, email, and web interactions so that every customer inquiry could be met with the most relevant and personalized offer.
