Standards and Platforms

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A Conceptual Framework for Economic Decision Making in Advancing Manufacturing Industry Competitiveness: Standards and Platforms

For more information, see NIST AMS 100-80.

Successfully implementation of the framework across an organization or ecosystem hinges in part on creating platforms in such a way that metrics can be estimated and stored in a consistent way. Methods and platforms need to facilitate data collection, storage, utilization, and analysis; thus, there are needs for the following:

• Dataset 1: Opportunity map
  • Standardized data categories
  • Standardized metrics
• Dataset 2: Hypotheses and Impact Estimates
  • Standardized methods for generating hypotheses
  • Standardized methods for impact assessment
  • Standardized data categories
  • Standardized metrics

A critical component is the classification of projects, which is necessary for generating actionable information. Impact estimates must be disaggregated by source to enable meaningful attribution of outcomes. When data is aggregated across projects, it becomes difficult to determine whether increases or decreases in impact are driven by specific project characteristics. This can be illustrated through the analogy of a factory containing two types of machinery, such as an additive manufacturing system and a stamping press. Each system has distinct inputs and outputs. If the inputs or outputs of the systems are collapsed into a single observation, it becomes difficult to optimize the efficiency and productivity of either machine because the effects of configuration changes are obscured by the performance of the other system. Therefore, data must be categorically separated at a level and specification that enables measurement of the impact of specific configuration changes. It is not sufficient for data to be granular; it must also be properly classified according to the source of impact. Detailed data that combines fundamentally different systems still obscures causal relationships and limits attribution. Accordingly, project categorization must distinguish between different mechanisms through which impact is achieved.

Framework Components, Logic, and Implementation

Credit: Pixabay The Framework	Credit: Pixabay Framework Logic	Credit: Pixabay Implementation Infrastructure
The Framework's Process	Background: Impact Forecasting	Notes and Cautions
Data Layers and Feed Back Loops	Supporting Logic and Evidence	Standards and Platforms
Metrics and Units of Observation	Economies of Scale	Modular Adoption

Credit: AMS 100-80

Collaboration is a key component to reducing change agent costs and enabling compound learning. If you are considering adopting this framework, consider reaching out to the author Douglas Thomas, Economist: douglas.thomas [at] nist.gov (douglas[dot]thomas[at]nist[dot]gov)