SUCCESS STORIES

SLA Management Platform

Cloud scalable platform to monitor wholesalers performances and manage contractual agreements

Published On: abril 29, 2022none
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THE CHALLENGE

The Client, who operates the leading multi-channel pay television, has launched a new fiber connectivity service on the Italian market.

As more content is delivered to consumers over the internet, the new fiber offer aims to bring together the best media content with the best connectivity available in the Italian market.

In order to achieve this ambition, the Client needed to implement a SLA management tool to monitor end-to-end service performance alignment to contractual agreements with network wholesalers and internal IT Service Providers. The tool should support monitoring and business decisions on a changing environment for a new player in the market, adapting to new regulations, new wholesalers and with an increasing number of SLA metrics to manage.

OUR SOLUTION

Bip supported the Client in the implementation of the cloud-based, scalable SLA management platform that serves as a central point of SLAs and Penalties monitoring, where to navigate and keep track of external and internal partner performances against the contractual agreements. The solution provides many features to support contract managers in their day-by-day business: directional reporting, business intelligence views to deep-dive on SLA trends and main related KPIs, self-service analytics platform to analyse anomalies and root-causes using both Client’s and wholesalers’ data, tracking of litigation processes, data reconciliation and what-if analysis application to simulate new scenarios.

The solution has been implemented on AWS services, leveraging on serverless and event-driven architecture to build a scalable solution and reduce operational costs. The entire layered data stack, from ingestion to data consumption, is operationalized with services such as AWS Lambda, S3, AuroraDB, Fargate and SQS. The SLAs calculation engine and the what-if web application is implemented with services such as AWS Elastic Container Service, Elastic Container Registry. The business intelligence layer is implemented with Tableau. In order to support the constant updates on the solution, such as the implementation of increasing number of SLA and the autonomous creation of new SLA by the business users, a full DevOps architecture has been implemented for each component of the solution leveraging on Code Pipeline and Cloud Formation AWS stack.

RESULTS

The solution has a deep impact on the Client Wholesale Operations business. Contract managers can monitor all operational areas of assurance, fulfillment, network and IT services, leveraging on dedicated dashboards that show a multitude of KPIs, level of services, penalties on different timeframes and aggregations, e.g. geographical. The scope of SLA monitoring increased by more than 300% with respect to previous management of those activities. Drastically reducing manual data entry for SLA calculation by the automation of the process of data ingestion from business and operations systems, the users can focus on data analysis, by using standard reports and working autonomously with advanced analytics features. For example, the users are autonomous in editing, versioning and simulating SLA scenarios in order to manage the relations with wholesalers and negotiate contracts updates.

BENEFITS

One platform for SLA monitoring, analysis, and scenarios simulation of contractual agreements with wholesalers

Automatic data ingestion from +20 data sources, from +5 different business and operational data providers

Automatic computation of +60 SLAs and Penalties, increasing over time

+60 directional and operational reports, providing advanced data analysis features and data export capabilities

SLA litigation processes management integrated within the platform to support data analysis, insights data sharing with wholesalers and SLAs reprocessing

Cloud scalable architecture to manage big data ingestion, spikes of scheduled workloads for reports generations and what-if analysis

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