Home Out-of-the-Box Thinking Case Studies AWS-Powered Forecasting Transformation

AWS-Powered Forecasting Transformation

Automating financial forecasting, validation, and variance reporting with AWS-native orchestration and Snowflake integration.

aws

Situation

The finance teams of a global electronics company relied on Excel-heavy workflows to collect and consolidate forecasts across multiple regions and business units. Manual processes slowed down variance analysis, introduced errors, and created friction for leadership during budgeting and month-end reporting cycles.

Problem

Manual spreadsheet-based processes were error-prone and time-consuming. Forecast submissions often contained incomplete, inconsistent, or incorrectly formatted data. Without a scalable, automated framework, finance teams spent more time reconciling data than driving strategic decisions.

Solution

Mu Sigma designed a semi self-serve financial forecasting and variance analysis platform leveraging AWS, Snowflake, and PowerApps. The system automated ingestion, validation, transformation, and reporting – ensuring data accuracy, scalability, and speed.

Key Components:

  • Data Ingestion: PowerApps Forecasting Input Portal supported manual entry and bulk Excel uploads, with files securely stored in Amazon S3 and routed via API Gateway to AWS Lambda.
  • Validation Logic: AWS Lambda and EventBridge enforced file formatting and business rules (mandatory fields, data types, duplication checks). Failure reports returned via PowerApps reduced rework.
  • ETL & Data Transformation: Matillion ETL pipelines moved data between Snowflake and S3. Snowflake hosted fact and dimension tables with embedded business logic for allocation and splits.
  • Reporting & Writeback: Variance calculations automated in Snowflake, with results distributed in Excel and Qlik dashboards for interactive analysis.
  • Performance Optimization: Snowflake Materialized Views and batch parallelization ensured high-speed processing during peak loads.
  • Monitoring & Observability: AWS CloudWatch, Matillion logging, and Snowflake analytics provided full system traceability.
  • Security & Governance: IAM roles and Secrets Manager safeguarded access, credentials, and compliance across the architecture.

Impact

  • 80% reduction in manual processing time by replacing Excel workflows with a PowerApps input portal and automated variance logic
  • 4x faster report delivery through AWS Lambda-driven ETL across regional business units.
  • Enabled scalable, auditable, and business-friendly reporting that empowered teams to make faster, insight-driven decisions.

Business Impact

  • 80%

    faster manual processing

  • 4x

    faster variance reporting

A forecasting input and variance analysis solution built on AWS Lambda, Snowflake, and PowerApps to streamline financial data collection, validation, and reporting. Enabled self-service analysis and faster reporting across global business units with built-in automation and governance.

Let’s move from data to decisions together. Talk to us.