T-Mobile US, Inc. Enhances Sales Commissions through AWS Collaboration

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T-Mobile US, Inc., one of the leading telecommunications providers in the United States, is experiencing rapid growth in its subscriber base. However, they faced challenges in meeting daily sales level agreement targets for their frontline staff and business stakeholders. Previously, they relied on a legacy Software as a Service (SaaS) application for compensation calculations and reporting, which proved to be inflexible, lacking scalability, and ultimately failed to deliver the expected value. In response, T-Mobile partnered with Amazon Web Services (AWS) to create a fully agile, auto-scaling, and cost-effective solution for sales performance management. This innovative approach has enabled T-Mobile to effectively drive sales and revenue growth while managing sales performance with greater efficiency. Impressively, the new system surpassed the initial performance goals, even as sales traffic volume doubled over the past two years.

The Solution

The AWS and T-Mobile teams adhered to several key design principles when developing the new application framework:

1. Adopt a microservices architecture.
2. Facilitate parallel processing and synchronous task management.
3. Allow customizable execution flows.
4. Operate without licensing fee constraints.
5. Maintain a stateless design with minimal infrastructure overhead and Infrastructure as a Service (IaaS) on demand.
6. Integrate auto-scaling capabilities to handle unpredictable processing needs.

In pursuit of enhanced scalability and reliability, the teams strategically decoupled application capabilities from business rules implementation, utilizing SQL for submission and processing within T-Mobile’s custom Spark application. This decision not only improved platform capabilities but also expedited time-to-market, facilitating quick development of new necessary business rules. Additionally, it alleviated concerns regarding application-level complexities, allowing seamless handling of computational tasks in the background.

The solution architecture consists of two key applications designed to boost agility and remove business dependencies:

1. Sales Compensation Data Application: This core application manages all upstream data essential for compensation calculations. It acts as a landing zone for data pushed by upstream systems (billing, CRM, payments, and more). Utilizing Amazon EventBridge for event-driven actions, the application employs AWS Lambda functions to trigger data migration via AWS Database Migration Service (AWS DMS) with the AWS Schema Conversion Tool (AWS SCT) for database schema conversions and ETL jobs. Furthermore, it uses Amazon Simple Notification Service (Amazon SNS) to notify the Sales Calculation and Reporting application.
2. Sales Calculation and Reporting Application: This application calculates, adjusts transactions, and reports on the process’s overall state. AWS Step Functions orchestrates synchronous job execution, while jobs run in Amazon EMR using T-Mobile’s custom Spark code. To handle batch traffic efficiently and cost-effectively, the team utilized Amazon Elastic Cloud Compute EC2 spot instances with auto-termination enabled for scalable jobs. It relies on Amazon Simple Queue Service (Amazon SQS) to queue messages from the Sales Compensation Data application and leverages Amazon RDS MySQL for metadata storage, along with Amazon DynamoDB for key-value pairs related to sales agents. Amazon Simple Storage Service (Amazon S3) serves as the central object storage for both raw and processed data, while Amazon Athena facilitates querying data in S3, and AWS Glue is employed for Spark jobs and integration with external systems like on-premises SQL databases.

Data Flow

The data ingestion process involves collecting data from over fifty diverse systems, including business inputs and manual overrides. This data may encompass transactions, quotas, HR, CRM information, metrics, or configuration data. Upon ingestion, rigorous validation ensures accuracy and completeness, with any discrepancies flagged for review and correction.

Eligible transactions are identified based on predetermined criteria, including payee eligibility and quota/target earnings calculations. These transactions are then assigned to appropriate payees using specific business logic to support compensation structures like Sales Performance Incentive Funds (SPIFs), individual performance metrics, or store metrics. Once properly assigned, payouts are processed in conjunction with downstream systems, such as payroll applications and CRM, facilitated through AWS Lambda and Amazon EventBridge.

Elasticity in Batch Operations

The auto-scaling capabilities of AWS services like Amazon EMR and AWS Step Functions are crucial for managing batch operations. The elasticity of Amazon EMR allows clusters to scale up or down automatically in response to workload fluctuations, optimizing resource use and cost efficiency. It adjusts cluster instance size based on metrics (such as CPU and memory utilization) to ensure adequate capacity for efficient batch processing during peak loads. AWS Step Functions, a serverless orchestration service, enhances the coordination and automation of workflows, including Amazon EMR steps, providing flexible resource allocation and supporting parallel processing. To reduce costs, T-Mobile utilized an ephemeral design, releasing assets when not in use.

The Results

T-Mobile has observed substantial enhancements throughout the sales compensation process:

• An 80% reduction in application-related issues, improving system reliability.
• A 40% decrease in platform costs.
• A 50% reduction in processing time.
• Elimination of delays between sales reporting and compensation statements.

Conclusion

By leveraging AWS services, T-Mobile US, Inc. has developed a highly scalable, reliable, and cost-effective solution to digitize their sales performance management. This new system has saved time and money while enhancing application reliability, resiliency, and operational excellence. For insights on how telecommunications companies are utilizing AWS services, visit Telecom on AWS or connect with an AWS representative today. Additionally, if you’re interested in further improving your work-life balance, consider exploring this worry journal which offers helpful strategies. For human resource professionals, the 2023 Palentine’s Day infographic from SHRM is an excellent resource as well.

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