Digital infrastructures and their elements

As an overview of the units of analysis has been established, this section identifies the constituent components of the digital infrastructures observed and describes them in the terms defined in the conceptual framework (Chapter 4). Together with the descriptions of the units of analysis presented in Chapter 5, this covers the first three

Agilization Cultivating DI and minding

flows of information to attain an appropriate level

of agility

Infrastructuralization Interpreting the IS in

organizations as DI

Informatization Converting data into information, managing and

sharing information within a DI

Information growing Simplifying the way data is

entered into IS

Information cooking Using existing transactional

data for business intelligence

Information serving Improving workflow by

presenting the right Information at the right time

stages (description, analytical resolution and abduction/ theoretical redescription) in Danermark et al.'s (2002) model for explanatory research, which is used to structure the analysis in this thesis. Based on the three units of analysis presented above, the following three digital infrastructures can be defined:

In the case of Analytics, the key elements of the digital infrastructure are:

 Information that exists within the business – e.g. transaction data from CRM systems, website visits, TV viewer logs

 Tools that produce the information (e.g. CRM, web shop, IPTV infrastruc-ture)

 Additional tools for analytics, e.g. Hadoop, decisioning tool, dashboards for sharing results

 People running analytics experiments, e.g. research team

 People in other parts of the business using information from analytics, e.g.

marketing teams, sales agents

In the case of OfferMaker, the key elements of the digital infrastructure are:

 The Telco web shop that presents offers to customers and sells them

 Operational system – CCP stack

 OfferMaker as a later modification of the digital infrastructure to enable easier editing of data

 People creating and manipulating offers

 Information: e.g. details of offers, market data on competitors In the case of SalesTool, the key elements of the digital infrastructure are:

 The OneView CRM system. This has evolved to be the main tool used for processing orders, even though this was not the intended purpose of the tool.

 SalesTool as a later modification of the digital infrastructure to facilitate agents’ workflow

 Sales agents in the call centres using the tools and e.g. negotiating which tool to use for which purpose

 Information (e.g. from real time analytics) supporting agents in their work, e.g. customer history

This illustrates how the elements of digital infrastructures postulated in the concep-tual framework (IT, people and information) all play an important role in constitu-ting digital infrastructures. These will be considered in more detail next.

IT is at the heart of each of the units of analysis. As Telco is a large, historically grown company, its IT estate is quite heterogeneous and has evolved over time, which has proved a considerable constraint to agility, as the grown systems make it hard to make changes that appear trivial (as the example of OfferMaker illustrated).

The OneView CRM system is a good example of how a tool has acquired a role (processing orders) that it was not very suitable for from the beginning, and how it is now so engrained in the offers digital infrastructure that it is hard to replace it. Often, however, the systems are modular enough to allow for some degree of modifications, as seen in the cases of the offer and sales infrastructures. In the case of analytics, such existing tools serve only as the source of information, whereas new, separate systems (like the Hadoop database) were implemented to serve the growing need for analytics.

Tilson et al. define digital infrastructures as sociotechnical systems – they become useful and generative only through the people using and forming them in the context of an organization. Thus, it is important to understand the role of people as users and developers in digital infrastructures. In the case of offers and sales, it was illustrated how significant improvements of the grown IT were implemented because individual users were frustrated with the tools and perceived them as slowing down the organization. By making them easier to use, they supported their evolution and made them more useful for the rest of the organization. Especially in the case of offers, a complicated process that involved product managers sharing their requirements informally, sometimes on a piece of paper (i9), has been simplified so that they can enter the data into the system themselves. Even in the use of the finished systems, people still play a significant role, as illustrated by the sales agents switching between the (old, more powerful) OneView and the (new, simpler) SalesTool auto-nomously. In the case of analytics, there is a separate team (the Research team) running experiments which then support other teams in the organization. Their chal-lenges include communicating with these teams in order to understand their needs as well as sharing any new tools they develop, so that their potential users may learn

about them. Finally, people decide what data is relevant for them and trigger the capture of data or flows of information.

Information is conceptualized here as an element of digital infrastructures. It is interesting to see how it plays a central role in each of the three cases. In the case of offers, the main goal of the digital infrastructure was to process information. After the change introduced with OfferMaker, the process of creating or entering informa-tion became faster and more flexible. In the case of sales, the significant change lay in the way the existing information was presented to its users. In the case of analy-tics, the main goal of the digital infrastructure is to collect information from around the business and present it to the right users in the right way.