The Necessary Architecture of Self-Regulating Teams

In this paper we present the meaning of self-regulation in Self- Regulating Teams (SRTs) and show the importance of self- regulating teams in a learning organisation. Self-regulating (also known as self-managing) teams guide and perform their own tasks without a visible leader. In the present dynamic business environment, SRTs promise to deliver higher motivation and empowerment to the individuals that participate in them as well as elevated performance and efficiency to the organisations that implement them. However, as management support and change in business culture are prerequisites for the success of SRTs, their implementation is not an easy task. Often, unsuccessful SRTs have been (in our opinion, wrongly) criticized as a source of ambiguity for organisations and as yet another management technique that does not deliver its promises. We start exploring the validity of such a criticism by discussing the shift from a training paradigm to a self- development paradigm in order to draw the picture of a learning organisation as an entity that facilitates learning of all its members and continuously transforms itself as a whole. We continue by showing the contribution that SRTs could make to the process of an organisation that aims to become a learning organisation. In this paper we adopt a cybernetic approach to describe the role of SRTs and to identify the necessary conditions for SRTs to work at all. We present the necessary architecture of SRTs; the architecture that is needed to deliver their promised advantages. We show how Gordon Pasks Conversation Theory could be applied to self-regulating teams and present how learning conversation could provide the framework for successful organisational evolution through team development and team self- regulation. We show how the establishment of such an architecture can lead to a better understanding of self-regulating teams and thus to their successful evolution and development within an organisation. We conclude by stating the implications of our analysis.