Detecting Disruption: : an Ex-ante Study in the Automotive Industry

Abstract: In history there are numerous examples of strong market-leaders who have lost everything through the emergence of a new breakthrough technology which has replaced the existing one. That could be the reason why Christensen received such high attention when he presented his famous work about disruptive technologies in 1997. In his work, and in many following studies, several aspects of this phenomenon have been investigated. However, the key point for the market leaders, the ability of identifying a market disruption before it happens, ex ante, is still a field that has not reached a definedstate of the art. In this work one of Christensen's original ideas of disruption, driven by changes incustomer demand, is highlighted as a possible improvement for the ex ante methodology. In this thesis a selected existing holistic prediction model is extended explicitly with this aspect of need change. The purpose of this work is thus to evaluate if including the property of shifting customer needs in an existing holistic model would improve the ex ante prediction of disruption and lead to a simple, practical but yet rich model. With a literature review of the existing types of ex ante methods a fitting base model for the holistic approach to disruptive prediction is found. A second literature review is performed with the focus on disruption and its link to changes in need, as expressed by customer demand. This serves as a starting point for the extension of the base ex ante model into a methodology that look also upon the aspect of shifting customer demand. To validate and use the proposed extended ex ante model a qualitative approach is selected. It consists of two studies within the automotive industry. One is a history analysis of a known disruptive case to validate the extension, the entry of Japanese car manufacturers into the US market. One is a case-study of a present potentially disruptive case to apply the extended method as a genuine ex ante method for final evaluation at a post-disruption stage. It investigates the effects of electric vehicles on the Chinese automotive market. Through the analysis of the two studies the conclusion is reached that a qualitative improvement of the prediction has been obtained. Additionally it is shown that the analysis of customer need change can provide an increased understanding of the underlying drivers of the disruption.