One of CECI's core establishments is to create a formalized shared model that serves as the centerpiece for administering an event technology framework. Thus, CECI will develop a living framework designed to evolve the event technology industry by supporting research, model maturity, and the voices of event technologists, while providing the infrastructure for collaboration, education, advocacy, and access to data.
Advance Foundational Research
Support ongoing efforts to structure domain-specific data and terminology under the Certified EventTech Classification Initiative.
Accelerate model development through broader member participation in event technologist collaboration.
Drive industry education by transforming raw research into actionable insights.
Maintain and Evolve the Shared Model
Publish and refine a classification framework that reflects current industry realities.
Ensure the model remains flexible, accessible, and responsive to member feedback.
Establish clear mechanisms for versioning, term stewardship, and structural updates.
Champion Member Voice in Domain Structuring
Enable members to shape and define categories within their specialties.
Create transparent pathways for identifying gaps, misalignment, or missing verticals.
Regularly engage members in audits, working groups, and iterative model updates.
Build Scalable Infrastructure for Collaboration
Develop digital systems and workflows that facilitate collective input and validation.
Fund tools that connect members, support synchronous alignment, and track contributions.
Maintain governance processes that keep participation structured and focused.
Lead Education & Strategic Outreach
Produce vendor-neutral educational resources grounded in the shared framework.
Partner with associations, buyers, and industry media to promote clarity and trust.
Advocate for the guild’s standards as a foundation for better buying and planning decisions.
Deliver Tiered Access to Event Tech Data
Roll out a structured, staged access model prioritizing integrity and usability.
Provide early access to guild members as model fidelity improves.
Ensure data tools support decision-making, benchmarking, and taxonomy refinement.
