The Value Chain Model (1985)

So far the critique of the traditional strategy content approach has focused on methodologies and techniques that have had an external perspective. The chapter will now consider the largely internal configuration of an organisation as portrayed in Michael Porter’s (1985) Value Chain model. Porter argued that value chain analysis allowed an organisation’s managers the opportunity to identify where value was created in a firm or where the opportunity to create a value was being lost. The value chain can, therefore, be considered to be an activity path through an organisation that identifies what an organisation does in order to create value either by manufacturing a product or by delivering a service and the order in which it performs these tasks. Porter’s original value chain configuration was not unsurprisingly that of a manufacturing firm since this was formulated in 1985 and was heavily influenced by the capitalist industrial era in which the research was undertaken. Therefore, the primary activities revolve around making something. The chain begins with inbound logistics (such as components, inventory control, ordering and management plus transportation planning), it then follows through to a transformation process (where the product is built), and it is then shipped to customers, marketed and supported with after-sales back-up. These primary activities are supported by a variety of activities designed to ensure that they are delivered as effectively as possible.

Although the value chain has been a very useful mechanism for portraying the sequence of linked activities that exist in the physical world within traditional industries (particularly manufacturing), the model has very little relevance when applied to the ICT sector. As products and services have become dematerialised and as the value chain itself no longer has any physical dimension, the concept is now seen as being an inappropriate tool with which to analyse modern industries and uncover sources of value (Norman and Ramirez 1994). This is particularly true in sectors such as banking, insurance, telecommunications, news, entertainment, music and advertising or technology, media and telecoms (Li and Whalley 2002). Furthermore, many industries now exhibit strong co-operative behaviour with inter-firm relationships playing a significant role in strategic performance (Madhaven, Koka and Prescott 1998). The focal point of the value chain is the end product, and the chain is designed around the activities required to produce it. The underlying logic is that every company occupies a position in the chain: upstream suppliers provide inputs before passing them downstream to the next link in the chain that is the customer. This suggests a single linear process that does not adequately capture the close symbiotic relationships between a company and its customers, suppliers and partners. The model also lends itself to mechanistic, linear thinking involving static rather than dynamic processes.

Adopting a network perspective provides an alternative approach that is more suited to ‘New Economy’ organisations particularly where both the product and supply and demand chain have been digitised (Peppard and Rylander 2006). Hearn and Pace (2006), devised a ‘Value Ecology’ model as a substitute for the value chain based on new conceptualisations of how value creation has changed in the digital era. They identified a number of key paradigm shifts including a shift in thinking about consumers to thinking about co-creators of value; a shift from thinking about value chains to thinking about value networks; and a shift from thinking about product value to network value etc. The leading industry sectors in which these shifts were occurring included TV, computer games, e-business, mobile phones and ‘everything that was digital’ (Hearn and Pace 2006).

Unlike the value chain (Porter 1985), Hearn and Pace’s (2006) value ecology model maintained that value creation was not a simple one-way linear process but involved processes of reiteration and feedback. Vargo and Lusch (2004:1) also stated that in the knowledge-based economy the notion of value was inherently different. The customer had become a co-producer or co-creator rather than a target and could be involved in the same value chain. Prior to this, the dominant logic was based on the economic model of there being an exchange of goods usually based on manufactured outputs. However, new perspectives have now emerged where the dominant logic focuses on intangible resources, the co-creation of value and relationships. The computer games sector provides a good example of this while user-generated content on Wikipedia, Facebook, You Tube, Instagram and Snapchat are all testimony to this shift in attitude. Therefore, companies can no longer act autonomously in the value creation process since the co-creation experience itself and not the product have become the basis of value.

The idea of moving from a value chain to a network approach is more appropriate from an information science perspective for two key reasons. First, networks are ideal information allocation and information flow mechanisms. Meanwhile, networks structurally facilitate rapid information transfer by providing horizontal links cutting across institutional boundaries to put people in direct contact with one-another. Networks also help to create information as well as transmit it. As each person in the network receives information, it is synthesised, and new ideas generated i.e. information builds on information. Networks share new ideas and help create them, and they are an ideal learning organisation for acquiring relevant, effective information (Brandenburger and Nalebuff 1996). Open innovation and crowdsourcing are also examples of how the Internet can act as a source of free R&D (Von Hippel 2005).

Second, new value creation is achieved through the manipulation of information while the characteristics of information are very different from ordinary goods. One of the economic characteristics of information is that the cost of information production is independent of its scale of use and this implies increasing returns to the use of information (Rifkin 2014). For example, a digital product can be replicated an infinite number of times at almost zero marginal cost, unlike a physical product. This factor has conferred benefits to firms such as Google, Facebook and Netflix and Internet and app-based firms in general.

Hearn and Pace (2006) also identified a shift from product value to network value which differentiated the value ecology model from the value chain. An important dimension of network value were the information and market externalities. Externalities are what economists use to describe situations where the value of a product is derived from anything outside the product itself. A simple example is the telephone which increased in value after inception following increases in the number of connections. Information externalities occur when products or service choices are affected substantially by information outside the product such as the ‘buzz’ on social networks and virality. Market externalities operate when the value of a product increases in proportion to the number of people who use it i.e. the diffusion of the original iPhone. This is also known as network economics (Arthur 1996). This implies that value lies in the ability of the product or service to connect to others. When connection happens early through various externalities an increasing returns effect is often generated. A network effect will often lead to customer lock-in and the emergence of a de facto industry standard or monopoly. This is what happened during the battle for the PC industry standard where Microsoft software and Intel micro-processor chips became the dominant Wintel standard resulting in high economic rents for both firms.

Arthur (1996: 100) argued that as the shift towards the ‘new economy’ occurred, the underlying mechanisms that determined economic behaviour also shifted from one of the diminishing returns to increasing returns. Arthur (1996) gave a number of reasons why increasing returns occurred:

  • • Up-front costs (unit costs fell as sales increased).
  • • Network effects (the more a product or service gained prevalence, the more likely it would emerge as a standard).
  • • Customer groove (as more market share is captured it becomes easier to capture future markets).

The growth of Amazon and Alibaba as the leading e-commerce platforms in the USA and China and the diffusion of Apple’s ecosystem of mobile products provide good supporting examples of Arthur’s (1996) theory of increasing returns.

Hearn and Pace (2006) also stated that by adopting a network rather than a value chain approach organisations focused not on the company or the industry but the value creating system itself within which different economic actors (suppliers, partners, allies and customers) worked together to co-produce value. This viewed strategy from an ecosystem perspective (Moore 1996). Whereas in a value chain context individual firm’s competed against each other, today competition is between networks (or even ecosystems) of interconnected organisations. Keystone players (Iansiti and Levien 2004) and/or platform leaders (Gawer and Cusumano 2002) need to view the health and wellbeing of their respective networks (and the individual partners that comprise the networks) and to prioritise this as being as important as their own company’s interests.

Value networks are composed of complementary nodes and links. The critical defining feature of networks is the complementarity between the various nodes and links. Firms (nodes) in the network are independent, but the relationships enjoyed by the firms in the network are essential to their competitive positions. The structure of the network, therefore, plays an important role in firm performance and in industry evolution (Madhavan, Koka and Prescott 1998).

Transaction cost analysis (Williamson 1985) also provides a way of understanding the impact of new information and communication technologies and why transformations take place within industries. According to this theory, an organisation can organise its activities either as an internal hierarchical structure or through a market relationship with external firms. Digitisation is significantly altering the cost structure of firms so that the cost of transactions both within and between organisations is dramatically declining. Therefore, many benefits associated with integrated firms (i.e. hierarchy), which primarily arise from their lower transaction costs, are eliminated. This can be seen across traditional industries with the fragmentation of traditional value chains from retail (banking) to manufacturing (automotive). This has also resulted in the emergence of the virtual organisation which is far removed from the physical value chain (Davidow and Malone 1992).

As firms move towards a virtual marketplace (Rayport and Sviokla 1995) in the networked economy traditional analytical tools such as the value chain fail to identify the true sources of value. The key to value creation in the networked economy lies in the understanding of how value is created in relationships. From a network perspective relationships are viewed as part of a larger whole i.e. a network of inter-dependent relationships. These relationships are, therefore ‘connected’ because what happens in one relationship affects the others (positively or negatively). Any analysis undertaken must, therefore, view value creation based on how the organisation creates value within the network and not from the perspective of the organisation as an isolated unit. A good example is provided by Intel when it develops a new microprocessor. The success of the microprocessor chip is dependent on software developers writing applications that leverage the new processing capability; hardware manufacturers must build systems that can accommodate the new chip - including any additional cooling requirements - and new bus architectures may also need to be designed. This is an ecosystem that needs to be cultivated (Gawer and Cusumano 2002).

Finally, as an alternative to the value chain model, Peppard and Rylander (2006) developed a Network Value Analysis (NVA) tool. This technique was designed to generate a comprehensive description of where value lies in a network and how value is created. This comprised a five stage process outlined as follows:

  • 1) Define the network.
  • 2) Identify and define network entities.
  • 3) Define the value each entity perceives from being a network member.
  • 4) Identify and map network influences.
  • 5) Analyse and shape.

The network value analysis (NVA) framework (Peppard and Rylander 2006) therefore aims to address the issues faced when designing appropriate strategies in the absence of the value chain model.

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