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MIDACOST01-BP01 Implement data-driven cost management using AWS cost tools and manufacturing data - Modern Industrial Data Technology Lens
Implementation guidanceKey AWS servicesResources

MIDACOST01-BP01 Implement data-driven cost management using AWS cost tools and manufacturing data

Create reliable cost forecasts by combining AWS usage data with manufacturing schedules to enhance resource provisioning and budget planning accuracy. This involves analyzing production patterns, seasonal variations, and historical cloud usage to make informed decisions about resource allocation and cost optimization.

Desired outcome: Develop precise monthly and quarterly cost forecasts by combining AWS usage data with manufacturing schedules to improve forecast reliability for resource provisioning and budget planning.

Common anti-patterns:

  • Relying solely on default AWS cost reports without implementing manufacturing-specific cost allocation tags

  • Making resource provisioning decisions based on short-term usage data

  • Failing to account for seasonal production variations when forecasting cloud costs

  • Using the same forecasting approach for all types of manufacturing workloads without considering their unique characteristics

  • Neglecting to correlate cloud spending with production output metrics

  • Setting static budgets without considering manufacturing cycles and production schedules

  • Making Reserved Instance or Savings Plan commitments without analyzing historical usage patterns

  • Ignoring the impact of planned maintenance windows and product launches on resource requirements

Benefits of establishing this Best Practice:

  • Improved budget planning and cost predictability

  • Better alignment between IT spending and OT production needs

  • Reduced risk of over-provisioning or under-provisioning resources

  • Enhanced ability to optimize costs during varying production cycles

Level of risk exposed if this best practice is not established: Medium

Implementation guidance

To systematically analyze and optimize costs:

  • Configure AWS Cost Explorer to track resource usage by manufacturing workload

  • Set up cost allocation tags that map to specific production lines and processes

  • Create monthly reports comparing AWS resource utilization with production output

  • Use AWS Budgets to set alerts based on predicted usage thresholds

  • Integrate production scheduling data from your MES/ERP systems with AWS cost management tools

  • Review and adjust resource allocation quarterly based on collected metrics

Implementation steps

  1. Enable detailed cost and usage reporting for all cloud resources.

  2. Create cost allocation tags aligned with manufacturing processes.

  3. Establish a system to collect and analyze production schedule data.

  4. Implement forecasting models that consider:

    • Seasonal production variations

    • Planned maintenance windows

    • New product launches

    • Historical resource utilization patterns

  5. Set up regular review cycles to validate forecasts against actual usage.

  6. Take advantage of cost saving mechanisms like AWS Savings Plans and Spot Instances.

Key AWS services

  • AWS Cost Explorer

  • AWS Budgets

  • AWS Supply Chain

  • Amazon SageMaker AI Canvas

  • AWS Data Exports with Quick

Resources

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