Digital business strategy & value creation
Margherita Pagani, EM Lyon
International conference on
“DATA, DIGITAL BUSINESS MODELS, CLOUD COMPUTING AND ORGANIZATIONAL DESIGN”
24-25 November 2014 ,
Université Paris –Sud
In this study we break down a value chain into its functional components and examine the ownership and organization of these components, which are critical in controlling the value dynamics of core and edges, how do components change and why.
To accomplish this task, we construct a view of the value chain as a configuration of control points, which comprise the various service transactions involved in implementing the functional components required to deliver a service offering. We call these configurations control point constellations (CPCs).
Control points are analyzed in this study in terms of how, and to what extent, they create and capture value, and in what forms.
Purpose of this study is to frame the structure and dynamics of the configuration of control point constellations.
In this study we break down a value chain into its functional components and examine the ownership and organization of these components, which are critical in controlling the value dynamics of core and edges, how do components change and why.
To accomplish this task, we construct a view of the value chain as a configuration of control points, which comprise the various service transactions involved in implementing the functional components required to deliver a service offering. We call these configurations control point constellations (CPCs).
Control points are analyzed in this study in terms of how, and to what extent, they create and capture value, and in what forms.
Purpose of this study is to frame the structure and dynamics of the configuration of control point constellations.
To accomplish this task we address the following research questions:
What does it mean to control the value network, and what are the different ways to gain control?
Does owning the customer relationship necessarily mean controlling the value network?
If you don’t control the customer, what are the other opportunities to compete in the video 2.0 value network for different types of players?
In order to identify the evolving path of the CPCs we followed a three-phases process:
1. experiment (empirical results emerging from case studies).
2. selection of the model structure
3. model estimation and validation
In this study we apply the methodology suggested by Eisenhardt (1989) to induce theory using case studies. The study is structured into two main phases: (1) empirical survey; (2) system identification. Overall, the process adopted is highly iterative and tightly linked to data. This research approach is especially appropriate in new topic areas (Eisenhardt 1989).
System identification is the task of inferring a mathematical description, a model, of a dynamic system from a series of measurements on the system. We adopted in this study the identification process called black-box modeling (Norgaard, Ravn, Poulsen and Hansen 2000).
The video industry is an excellent setting to understand the evolution (and revolution) in value systems and control points constellations. We propose four different value configuration systems and study their control points constellations. Each structure assumes a longer time constant:
- the first model defines the short-term static properties of industry structure and refers to development of traditional analog TV;
- the second and third models define the mid-term dynamic - but non-evolutionary - process of competition (full development of interactive digital TV and peer to peer network),
- and the fourth phase defines the long-term co-evolutionary process of industry change with video 2.0.
From 1960 to 1980 in US and Europe media companies have adopted strategies aimed at obtaining scale economies within mutual horizontal core-businesses (focalization strategies).
Although achieving scale economies could be a must for long-term success (Chandler, 1990), in time such condition proved to be insufficient. The growing convergence of different technologies and skills led to the realization that media companies with a wider scope could carve a profit for themselves which put them at an advantage over more strictly focalized companies. Media companies expanded their activities to adjacent markets (1980-1985 phase) through cooperation strategies and alliances (vertical and horizontal strategies).
However, scale and target economies could not guarantee dominance in the converging industries.
The key changes in traditional TV include the digital transmission of TV signals (technology trigger), which enables the delivery of more channels and the high definition (HDTV) format, as well as interactive services like the EPG ,VOD, interactive advertising.
What I want to show in this slide is that in this phase the emerging interactive digital television marketplace is more complex with competing platforms and technologies (satellite, cable, terrestrial, IP) providing different capabilities and opportunities. The traditional communications value chain is increasingly being deconstructed, which is leading to the development of a complex and rapidly evolving value network.
We looked in depth at the changes occurring in the traditional TV value chain, that is, the terrestrial, cable, and satellite systems We conducted two empirical parallel analyses. The first developed by Natalie is based on the digital TV in US aimed to map all the players and related functions involved in the provision of TV services.
The second analysis was conducted on the terrestrial digital TV in Italy (see slide) and aims also to identify the types of relationship among players (i.e. contractual, ownership etc.).
These two studies allowed us to gather data and map the main functions of the emerging value network.
In this changed context we can distinguish the emergence of hub firms defined as the ones that possess a central position in the value network structure, and that use their prominence and power to perform a leadership role in pulling together the dispersed resources and capabilities of network members.
Interactive television has in this phase a larger number of key stakeholders and a more complicated set of processes and relationships than traditional TV. The multi-channel revolution coupled with the developments of interactive technology is truly going to have a profound effect on the supply chain of the TV industry which is more disintegrated and open. Traditional broadcasters, who in the previous stage have been developing primary skills in the phases of packaging and signal transmission (network provision) develop contractual links with other players in the market (application service providers, network providers etc.).
TV Channels and delivery platforms compete to capture the attention of the viewer and the value is provided by the most compelling content and useful interactive service.
Based on data gathered from field analysis (case studies in US and Italy) we constructed the basic model of the network ordering the units in layers, letting each unit in a layer takes as input only the outputs of inputs in the previous layers or external inputs. (see slide)
The function of the network is determined by the architecture of the network, the magnitude of the weights, and the processing element’s mode of operation.
Each node is a processing element that takes a number of inputs, weights them, sums them up and uses the result as the argument for a singular valued function, the activation function.
The mathematical formula expressing what is going on in the MLP-network take the form: