This course addresses the critical need of manufacturing practitioners and executives to understand the power of real-time decisions for manufacturing operations metrics before and after linked to financial and business level metrics. The differences between the various types of metrics are explained. 

The link between operations and financial metrics can be approaches from both ends. The Vollman decomposition is applied to construct metrics models from an operations perspective. As an example the Three Layered Model and the Metrics Construction process, which is published in the MESA Metrics Guidebook (2nd edition), are introduced.

Cost Accounting approaches as Grenz Plan Kostenrechnung (GPK), Activity based Costing (ABC) and Resource Consumption Accounting (RCA) start from the financial perspective.
While metrics approaches are reactive, analytics are focusing on continuous improvement. Application of Machine Learning, a subset of Artificial Intelligence, can help manufacturers to improved decision making in complex situations.

  • Recognize the increased decision making capabilities of mapping operations metrics to financial and business metrics.
  • Explain the different types of metrics from different business levels and how they influence one another for effective optimization of the business processes.
  • Describe the Vollman decomposition as a tool to create a metrics framework.
  • Recognize cost accounting approaches.
  • Describe the differences between metrics and analytics.
  • Identify the basic elements of Data Analytics and Machine Learning.
  • Introduction
  • Metrics Do Matter!
  • The Great Divide: Operations and Finance
  • Metrics Models
  • Cost Accounting Approaches
  • Analytics
  • Machine Learning
  • Conclusions and Wrap-Up

Test and Exercises:
1. In-Course Formative Assessment Test: 10 Questions, Open notes in discussion, Answers recorded in Test Form
2. Out-Course Summative Assessment Test: 10 Questions, Open notes in self study, Answers recorded in Test Form

Course Prerequisites:
None

Reference Materials:
MESA Guidebook: MESA Metrics Guidebook