Last Friday, fifteen people gathered at the NC Biotech Center, where Dr. Milton Krivokuca, an ASQ Fellow, led the discussion on integrating data science and quality to achieve organizational excellence.

After each attendee introduced themselves, Dr. Krivokuca shared his personal journey and decades of association with ASQ and its members. A key message was that connections created by ASQ could lead to new opportunities!

The first half of Dr. Krivokuca’s presentation was focused on the technical, social, personal, and managerial aspects of Quality 4.0 — how does technology enable the organization? Specifically, how do organizations achieve different levels of data/digital maturity? It’s certainly challenging for an organization to respond and adapt quickly to technological advancement while staying focused on its business, customers, and employees.

In addition to understanding what data science (or big data, machine learning, artificial intelligence, etc.) means, the discussion of digital transformation again pointed to organizational culture and how people respond to change.

The first breakout session had three key questions:

• What are your perspectives of where the data scientist should reside in an organization?
• Do these quality-data science concepts align with your organization’s digital transformation?
• What next steps wold be most appropriate for your organization?

Three breakout groups shared their perspectives, for example

• How to communicate change to employees and customers?
• How to manage varying levels of digital maturity within the organization? Where do we start?
• How to overcome the tendency of implementing technology in silos without considering the value stream?
• What systems or governing structures do we need?

The second half of the presentation and breakout discussion moved into understanding data science and data scientists, making the connection between continuous learning (data science) and continuous improvement (quality).

A key question was “what’s the role of a data scientist?” The related questions are

• What skills (technical and non-technical) are needed for successful transformation?
• Which skills do quality professionals already have?
• How should the organization be designed to develop data science capability?
• How do Quality and IT organizations fit in the transformation?

The discussion could definitely use more time than scheduled. We look forward to more sessions on such topics. Let us know if you have any suggestions!