Heuristics for emergence of standards 

Here are seven heuristics that can promote the emergence of open consensus standards. These heuristics are based on experience in the development of standards in several technologies and standards organizations. 

Heuristics condense common experience to offer useful guidelines for system building [Rechtin, 1991]. If history is a guide, these heuristics may be valuable for future open standards development:

• Think Big, Start Small

Have a broad vision of the desired outcome, begin with focused initial activities that build toward the vision. Evolve the vision and the implementation based on experience.

• Open Wins

Standards work best when they are open, developed in an open community process, and open for use with minimal restrictions when published freely.

• STEM

Standards based on Science, Technology, Engineering, and Math are more resilient and longer lasting. STEM principles assist in establishing consensus and provide a basis for adaptation.

• Implementation

The proof is in the doing: “running code wins.” Implementation of initial small steps, iteratively refined using STEM, provides evidence for building consensus.

• Innovation

Technology advancements are based on past achievements. Novel combination and new methods, typically coming from multiple iterations by a small team provide the means to improve on current baseline.

• Maturation

Increasing technology readiness levels through testing, refinement of the specfication, and widespread community use is essential to operational use of standards and a robust standards baseline.

• Adaptation

Standards evolve in an ecosystem of technology development and operational use. Changes to the baseline based on experience from various applications and communities, results in new emergent value.  There is a sweet spot between too rapid of change and no change.  

Complex systems will evolve from simple systems much more rapidly if there are stable intermediate forms than if there are not.  [Simon, 1962]. Open standards are a stable forms in the evolution of systems.

Rechtin, E. (1991). Systems Architecting. Prentice Hall. ISBN 0-13-880345-5 

Simon, H. (1962). The Architecture of Complexity. Proc. AM. Philos. Soc. V.106, No.6, p467-482.