Change models in need of renewal: Building strategic practice to prevail in industry transitions
Organizations find it hard to survive industry transitions. To succeed, organizations need to rethink the way they do business and the renewal efforts have to overcome the lock-in created by the organizational system, capabilities and organizational culture. Moreover, in an industry transition a clear view of what to change into is often lacking. This could be seen as a special case of change: a case of renewal.
One suggested way of succeeding with renewal is to separate the new from the old (structural ambidexterity). However, that is not always possible. In such situations, the old and the new have to co-exist and develop simultaneously (contextual ambidexterity). In this licentiate thesis, the latter is discussed.
This calls for a practice, where renewal initiatives cannot rely on traditional change models. Change processes are often assumed to be guided by a vision for the future and a clear process ahead, outlined by management. Instead, in the case of renewal, a practice is needed where the organization creates the road ahead, utilizing organizational capabilities such as creativity and learning,
How traditional prerequisites for change apply in a renewal context is discussed in this licentiate thesis, leading to a proposal of how the well-known “change formula” (representing traditional change models) could be modified to be relevant in the context of renewal. I argue that this thesis contributes to the understanding of what is needed to succeed with renewal, hence taking a step towards building strategic practice to prevail in industry transitions.
The empirical data for this thesis is presented in three appended papers. Paper 1 and 3 draw on a longitudinal study of a media group, studying their renewal initiatives in the midst of an ongoing industry transition. In paper 2, 10 different strategy processes were followed, with data from 28 strategy creation workshops. The data has predominantly been collected through action research.