The Implications for Strategy and Competition
The platform stack concept (Choudary 2015) and the architectural approach to the analysis of complex platform ecosystems is in stark contrast to the classical (Ansoff 1965; Andrews (1971); positioning (Porter 1980, 1985) and the RBV (Grant 2016) approaches to strategy discussed so far. It is, therefore, worth exploring the benefits of the approach and making some comparisons with well-established models from the classical, positioning and RBV schools.
First, the platform stack provides a useful tool that helps to understand the different types of platforms that exist. It can be used to identify potential threats from both new and established platforms and/or highlighting opportunities to provide complementary assets. Second, the platform stack helps to decide which layers in a platform a firm should differentiate itself in and how. This can be likened to the resource based view (RBV) where a strategy is selected based on the most appropriate fit between the resources at hand and the demands of the external environment and marketplace (Barney 1991; Grant 2016).
Third, the platform stack helps platform-builders to understand the key drivers of value and how to benchmark a platform on these key parameters against competition and substitutes. In this instance the platform stack can be viewed as a substitute for the Value Chain (Porter 1985) model. It not only helps to identify the core value units but also how the value is configured. It also provides an easy method to use as a benchmarking tool when analysing the value configurations of competitors.
Fourth, although we have focused on the differential aspects of the platform stack and how firms often dominate specific layers over others, some of the very large Internet firms (Amazon, Alibaba and Google) are dominant in all three layers and this is known as “building-out-the stack” (Choudary 2015). This could be likened to Porter’s (1980) monopolistic power (Five Forces Framework) where a small number (oligopoly) of very large data-rich firms hold a dominant position. This is likely to strengthen as these firms develop artificial intelligence capabilities. These are also what Tidd and Bessant referred to as high involvement in innovation (HII) companies (Tidd and Bessant 2013).
It can be seen from this analysis that the ecosystem and platform theories are more appropriate for the analysis of the ICT sector. The analysis also highlights the differences in approach between the classical, rational view of strategy (Ansoff 1965) and the platform-ecosystem paradigm (Moore 1996; Gawer 2009).
However, the analysis does still raise a number of important questions. The speed at which technological change is occurring has meant that the current theories now need updating. Gawer’s (2009) typology of platforms does not take account of the business model innovation and disruption being created by the new multi-sided platforms (Downes and Nunes 2013) and how this type of platform is becoming even more pervasive than the original industry ecosystem (Evans and Gawer 2016). In fact, the two types of platform ecosystem are now converging, and the boundaries between them are blurring or disappearing altogether in some instances. Meanwhile, Fransman’s (2010) layered ICT ecosystem model does not recognise how the sectors boundaries have now extended to include artificial intelligence (AI) and all forms of data transmitted via the Internet. Nevertheless, Fransman did state quite emphatically that the Internet was a network of networks as well as a platform of platforms (Fransman 2010: 19).
These issues will, to a large extent, be addressed in Chapter 5 where a hydrothermal vent ecosystem model is used to provide a new and more dynamic perspective. However, before analysing the new model, the chapter will conclude with a summary and discussion of the key differentiators that characterise the classical (Ansoff 1965; Andrews 1971) and resource-based views (RBV) of strategy (Grant 2016) and the platform- ecosystem approach (Choudary 2015; Moore 1996).