2.A. Goal-Directed Research

To receive an Excellent rating, the individual must demonstrate contribution to knowledge through a focused, goal directed program of research or other scholarly activity.

My multidisciplinary research agenda explores the relationships between quality, innovation, and transformational experience to help people and organizations realize their potential. I employ data science to explore new ways to think about quality systems and innovation, with a focus on emergent environments for living and learning, leveraging alternative economies and gift cultures such as Burning Man. The articles, presentations, and workshops I deliver address these topics:

  • quality consciousness (improving awareness, alignment and attention to help individuals improve quality and productivity; creating novel, innovative organizational quality systems),
  • quality informatics (data- and algorithm-intensive quality improvement), especially in technology management, software engineeering, and astronomical instrumentation, and
  • understanding how innovation is catalyzed by culture and transformational experience, particularly in higher education.

Quality can be defined as “the totality of characteristics of an ENTITY that bears on its ability to satisfy stated and implied needs.” (ISO 9000 para 3.1.5; formerly ISO 8402) Usually, when we’re thinking about quality systems within business organizations, our entities are products and processes and projects.

But we’re never on our own – whatever we pursue or accomplish, we’re always individuals in relationship to, and in community with, one another. As a result, what if the ENTITY in the definition above is YOU? The quality of any product, process, relationship, or venture you engage in will depend upon the QUALITY YOU EMBODY and how you relate to, and align with, the environment in which you are embedded.

Quality consciousness and quality informatics are related in the same way that artificial intelligence is related to consciousness: we can improve our ability to influence quality by improving the cooperative awareness and attention of humans and machines who must sift through increasing volumes and varieties of data to make goal-directed decisions.