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3.2.1 Conceptualizing digitalization

As argued in the previous chapter, digitalization has led to important changes in organizations and their IT, which have not yet been fully acknowledged in Informa-tion Systems research on organizaInforma-tional agility. This secInforma-tion relates the term to digital convergence, defines it and reflects on how it affects IT in organizations.

As shown by Sambamurthy et al. (2003), digital convergence is an important driver of the current changes to IT in organizations. Initially, it was discussed around concepts like “mergers of core functionalities from the computer (calculation), the telephone (point-to-point connection), and the television (broadcasting)” (Sørensen 2011b, p. 470). Sørensen charts how usage of the term proceeded to shift to “the digitization of previous analogue communications and data, thereby allowing pro-cessing of data across previously separated carriers through open standards” (ibid.).

This notion is developed into the broader concept of digitalization by Tilson et al.

(2010), who define it as “a sociotechnical process of applying digitizing techniques to broader social and institutional contexts that render digital technologies infra-structural” (p. 749). This is distinguished from digitizing, which they see as merely

“a technical process” (ibid.). As the term ‘convergence’ is fairly vague and not con-sistently used (Herzhoff 2009), this thesis will use the term ‘digitalization’ instead.

The above definition illustrates how digitalization increasingly affects a variety of areas of IT and business. Tilson et al. speak of “IT tearing down the old analog world and its associated social infrastructures” (p. 756). Nevertheless, research on digitali-zation is often focussed on the areas where the concept of digital convergence originated, e.g. digital artefacts (Kallinikos et al. 2012), digital media (Yoo 2013) or mobile ecosystems (Tilson et al. 2010). In contrast, some authors have used it also in the broader context of more traditional information systems in organizations (e.g.

Hylving & Schultze 2013). There seems to be a case for applying the concept of digitalization more broadly in research on information systems.

3.2.2 Consequences of digitalization

Digitalization has led to a number of changes in the nature of information systems and the way they are conceptualized. Three of these are briefly introduced here,

namely modularity, generativity and the increased role of information in information systems and organizations.

As digitizing has separated information from a fixed medium for storage and transfer, more flexible, modular information systems are possible (Yoo et al. 2010).

As per Yoo et al.'s (2010, p.727) definition,

a modular architecture is characterized by its standardized interfaces be-tween components. Modularity is a general characteristic of a complex system and refers to the degree to which a product can be decomposed into components that can be recombined.

Yoo et al. show how the digitalization of well-established analogue products has made new products possible that have significantly affected the competitive land-scape, giving Amazon’s Kindle and its ecosystem as an example. They theorize a layered modular architecture with loosely coupled elements integrating across boundaries like different companies or the physical vs. digital world. This illustrates how digital technology has become a part of business strategy. Consequently, Infor-mation Systems research can focus on supporting such net-enabled firms driven by modular architecture. Yoo et al. see this as evidence for the “profound changes in the industrial structure and competitive landscape” (p. 724) enabled by digitalization.

While their focus is on product design, Yoo (2013) broadens the argument by pointing out how modularity “also affects the way firms are organized” (p. 229), as already demonstrated by Sanchez & Mahoney (1996). Specifically in the area of organizational agility research, Tiwana & Konsynski (2010) show how a modular architecture can help sustain alignment by increasing agility.

Modularity in turn increases generativity, defined as “a system's capacity to produce unanticipated change through unfiltered contributions from broad and varied audien-ces” (Zittrain 2008, p.70). Eck et al. (2015) discuss the ways the term has been used in the Information Systems field. They argue that Zittrain intends to capture three aspects of generativity, namely “that technologies can drive individual and collective creativity” (p. 3), “that only through the participation of humans the generative capacity of a technology can be realized” (ibid.) and “that innovation happens on different layers – e.g., technology, content, and society – each of which may possess generative capacity on their own” (ibid.). Yoo (2013) argues that as a consequence

of digitalization, modularity is no longer sufficient as a framework for research and that innovations based on generativity are “distinctly different” (p. 228) from those based on modularity and better able to explain contemporary phenomena. His call for “a more precise and nuanced understanding of the nature of digital technology that enables and constrains activities that produce generative innovations” has been mentioned above as one of the starting points for the argument developed here.

Another consequence of digitalization proposed here is that the role of information in the context of information systems and organizations may also increase in signifi-cance as it gains relevance as an actor:

information’s involvement in socio-economic life is acquiring comprehen-sive dimensions that enlarge and deepen the impact it had on organizations during the second half of the 20th century (Kallinikos 2009, p.183 f.)

Information is conceptualized here as an element of digital infrastructures, and is introduced as such below (subsection 3.3.3). As discussed, digitalization and digital convergence lead to the separation of information from a fixed medium. For ex-ample, information that used to be stored on a CD may now exist in an MP3 file without any physical properties. This can be applied to other areas, as in the case of the separation of computing from a physical medium, as seen in some examples of cloud computing (Venters & Whitley 2012). It also enables a more modular archi-tecture in which systems can be combined from standardized components like application program interfaces (APIs) or add-ons (Yoo et al. 2010). Some authors have speculated on the consequences of this. For example, Kallinikos et al. (2013) reflect on the properties of “digital artefacts”, which they describe as “editable, interactive, reprogrammable, and distributable” (p. 357). In a similar vein, Mayer-Schönberger & Cukier (2013) look at datafication, the transformation of social action into online quantified data allowing real-time tracking and predictive analysis. In this context, the term ‘big data’ is often used. Mayer-Schönberger & Cukier (2013) define big data as “[t]he ability of society to harness information in novel ways to produce useful insights or goods and services of significant value” (p.2). Definitions in Information Systems research focus more on the aspect of data, e.g. “data that’s too big, too fast or too hard for existing tools to process” (Clarke 2016, p.77). This is the definition followed in this thesis. Similar terms are applied by Constantiou &

Kallinikos (2014) and Loebbecke & Picot (2015). Goes (2014, p.iii) adds that “[b]ig

data has been defined by the 4 V’s: volume, velocity, variety, and veracity. The new paradigm comes by combining these dimensions.” While Mayer-Schönberger &

Cukier are very optimistic about datafication and the big data tools it enables, Kallinikos (2009) gives a more balanced view of the similar concept of infor-matization, “the computational logic by which reality is rendered as information” (p.

183).

3.2.3 Digitalization in the context of organizational agility

This thesis introduces the concepts of digitalization and digital infrastructures to Information Systems research on organizational agility in order to address some of the issues identified in the literature review. It argues that digitalization is relevant for researching the use and development of IT in large companies (defined by the British government (HM Revenue & Customs 2015) as companies with more than 500 employees and an annual turnover over €100 million). As shown in the literature review, digitalization has led to new ways to conceptualize information systems in organizations, notably the concept of digital infrastructures (Tilson et al. 2010). This thesis aims to show how this concept, originally used mainly to refer to present-day, web-enabled infrastructures like the Internet itself (Hanseth & Lyytinen 2010) or the iPad ecosystem (Tilson et al. 2010), can be used to describe the evolution of more traditional information systems in large organizations. This is illustrated using the case of Telco and the example of modifying historically grown infrastructures to increase agility.

The next section discusses how digital infrastructures are conceptualized here.