Chapters

Compiled by experts

The XLA Institute has active chapters for co-creation, covering various topics prioritized by the council. Members and associates can join chapters.

To enable the chapters to achieve their goals, they work alongside subject matter experts and are supported by a secretary and a team of copywriters, designers, and content editors.

Chapters

The XLA Institute has active chapters for co-creation, covering various topics prioritized by the council. Members and associates can join chapters.

To enable the chapters to achieve their goals, they work alongside subject matter experts and are supported by a secretary and a team of copywriters, designers, and content editors.

The XLA Framework is a collection of guidelines and insights. The objective of this chapter is the ongoing development of the XLA Framework in sensemaking, thinking, experimenting, executing, contracting, and learning about experience management within digital-driven organizations. XLA's mission is to be interoperable with ITIL and Agile.

To ensure the contractual embedding of XLA, we involve legal firms to develop a subset of the XLA Framework to guide effective negotiations, contracting and collaboration. A tangible outcome is a set of Practice Cards to guide the stakeholders. Subject matter experts at legal firms validate the practices.

The purpose of an XMO is to start, organize, embed, and scale Experience Management in digital-driven organizations. This chapter addresses the organizational set of good practices.

For the development of advanced solutions. The chapter is involved in the standards for applying standard measurement of X-data (human experiences) on DEM platforms and using X-data effectively in combination with monitoring data (O-data).

To support and enable the standardization of practices and evaluation methods (like benchmarking and quality improvement), we will work with national and international standards organizations.

To secure independent review for training, a third party will be responsible for the development of exams, the online examination, and the certification of successful students. The objective of this chapter is to oversee the quality and integrity of the examination and certification processes.

We involve universities with data sciences and AI curricula (Master's and PhD level) interested in real-life cases, like emotional AI for voice bots in-service support, contextual machine learning on emotions, and preemptive analytics on UX. We also have the ambition to design training solutions for bachelor students.