The success factors in quality management and improvement work are context-specific, and the context is changing. In addition to rapid change, the future is increasingly calling for new abilities in completeness, improving and developing quality in truly complex systems. The urgent challenges to make the world more sustainable is clearly pushing this agenda. The United Nation's 17 sustainable development goals (SDGs) require, by definition, improvements to be made on the scale of the whole; the goals, like their solutions, are often complex and dynamically interconnected. Hence, sustainable development requires a system view, lessons to be learned from leading complexity, and cross-border collaboration that allows the treatment and improvement of the whole as a unit. This urgently needed mindset and practice has recently been referred to as the fourth “emergence” paradigm of TQM.
Thus, emergence points to the need for collective intelligence rather than experts having the answers. This also implies that solutions and improvements cannot be imposed; rather, they arise from probing, sensing and an interplay with the complex context. In short, the understanding and improvement of quality becomes a participatory process of continuous dialogue including “the whole system” for all stakeholders. Consequently, what works to manage and improve quality is different in this emergence paradigm of TQM. Being practical, one of the specific methods that is then recommended as a complement to the TQM toolbox is the change method known as Appreciative Inquiry (AI). AI has been used for more than three decades and has repeatedly indicated its potential as a successful method for engaging and driving improvements and rapid change on the scale of the whole. The method has evolved and been refined towards perfection in regard to the design of events, processes and meeting places that successfully connect and initiate cross-border improvement and development initiatives. One of the most powerful practices for this approach is known as the AI summit. However, from a QM perspective, it is what happens after the summit that truly makes a difference. This is when a wide spectrum of improvement ideas and initiatives around which people have self-organized is realized, or not, in a dynamic process of emergent change. This critical phase of keeping the momentum alive is referred to as the “drum” phase, and in it, of all of the AI summit phases, there is the least agreement, guidance or support for what happens after the AI summit event.
The purpose of this paper is to advance towards the called-for emergence paradigm of TQM by exploring the emergent drum phase of the Appreciative Inquiry method.
2019.