Managing Supply Chain Networks: From Value Chain to Value Network
As introduced in the preface, during the past few decades academics and practitioners have debated about the best approach do define a firm’s strategy. Different approaches generate specific consequences on the effort to implement the designed strategy and on the quality of the business results that derive from the strategy’s lifecycle. The model based on the mechanism of imperfect competition within an industry called the Five Forces That Shape Strategy (Porter 1985) is largely accepted, despite several dissonant opinions.1,2,3 Recently, an interesting approach called the Blue Ocean Strategy (Kim, et al. 2005) suggests management strategies that focus more on creating or entering unexplored markets rather than competing in aggressive environments where Porter’s forces exist.
Both models offer theoretical arguments to support a “what-to-do” approach for these methodologies that follow a strategy-definition sequence. Despite any discussion regarding the validity or applicability of the theoretical arguments these models use, the fact is that no what-to-do model is capable of delivering a quality response to contemporary business environment challenges. The firm’s success depends on “how-to-do” elements (see Figure 1.4).
The idea that “every firm is a collection of activities that are performed to design, produce, market, deliver, and support its product” was presented in (Porter 1985) and illustrated as shown in Figure 1.1.
Figure 1.1 The generic value chain
Porter (1985) explains the design and performance of a firm’s value chain “are a reflection of its history, its strategy, its approach to implementing its strategy, and the underlying economics of the activities themselves.” By not referring to any relative weighting between these elements and not defining any sequencing, this statement suggests these elements equally influence the design and performance of the value chain, as shown in Figure 1.2.
Figure 1.2 Value chain dynamics, 1
The reality, though, imposes different dynamics as there are only two independent variables:
- Firm’s history, which also defines its culture
- The underlying economics of the activities
These elements influence the others.
The authors believe a third element should be unveiled: the existing strategy. Except for the situation when the organization is first ever in defining a strategy, which is unlikely to happen in most cases, the existing strategy will certainly influence the shape of the future strategy as the effort of transformation has to be considered when managing the value chain redesign. A similar argument was presented by Werner (1984),4 who questioned the feasibility of evaluating the attractiveness of an industry, independently of the resources a firm brings to that industry.5 Therefore, there are three independent variables to influence the value chain design and performance:
- Firm’s history
- Underlying economic activities
- Existing value chain design
To explain the reasons why the authors believe Porter’s theory is unlikely to survive in the existing business environment requires additional consideration of these apparently independent variables.
Figure 1.3 Choice of competitive strategy
The firm’s history includes the business relationship history (products, suppliers, customers, service providers, internal interfaces), which defines what things are done and the culture of this firm, which defines how things are done. Gerry Johnson’s Cultural Web (Johnson, et al. 1999) model offers a valuable approach to diagnose a firm’s culture, observing the following dimensions: routines, rituals, symbols, stories, control systems, power structure, organizational structure, and the paradigm. Therefore, a firm’s history influences the following:
- The strategy definition.
- The approach to implementing the strategy.
- The (re)design of the value chain required to meet the strategy’s goals.
- The value chain performance. Both business practical attributes and business culture are present during a strategy’s lifecycle.
Figure 1.4 Strategy definition, internal factors
As cited, the second independent variable that defines the firm’s strategy is the underlying economics of the activities. Using a simple approach to address this variable, it is possible to observe that economic activities lie on two time horizons:
- A short-term microeconomics scenario, usually subject to national or regional specificities
- A medium- to long-term macroeconomic structural environment
Porter’s value chain theory indicates two attributes that define a firm’s competitive strategy:
- Long-term profitability
The relative position within an industry.
This statement is guided by the premise that the Five Forces Model is only applicable at the line-of-business industry level, which disables industry group or industry sector-level analysis. In other words, it neglects several significant interactions within supply networks. This guideline is crucial to determine the obsolescence of Porter’s theory.
Long-term profitability and relative position within an industry are extremely sensitive to different economic horizons. If economic stability horizons shorten, the risk that a given strategy becomes obsolete increases dramatically.
Therefore, it is expected that the economics of the environment influence not only the strategy itself but also the approach to its implementation and in the long run, its performance. Note that we have segmented Porter’s suggested “value chain design and performance” into different elements because they do not have a mutually exclusive interaction. It is not possible to define the value chain performance only by its design.
Figure 1.5 Strategy definition, external factors
The selected firm’s value chain strategy, influenced by (1) the existing strategy, (2) the underlying economics, and (3) the firm’s history, suggests a value chain design. The effort and the roadmap used to move from the existing shape to the proposed value chain are influenced by a firm’s culture (the way things are done) and by the external elements which are mostly determined by the industry’s economics, as described before.
The speed, quality, and completeness of the strategy implementation define business performance during the transition and when the new value chain foundations have been settled.
This business approach suggests that four elements will drive value chain modifications:
- Existing business practices (what the firms do)
- Business culture (how the firms do it)
- Micro-economics (local/regional business environment with short- to medium-term perspective)
- Macro-economic (medium- to long-term structural balance with local, regional, and global impact)
While the internal factors are expected to face very limited spontaneous change due to people’s unwillingness to do things differently, the external factors have always been more dynamic and uncontrollable by businesses mechanisms.
The Supply Network Alignment Reference Model
Over the years, the common understanding of world-class operations has evolved from the simplistic, focused management of functional silos of isolated knowledge islands (see Figure 1.1) to a comprehensive approach to supply network management as the driver to orchestrate fluid and complex environments in order to deliver ultimate shareholder value (Oliveira and Gimeno, 2014).
Numerous approaches have attempted to describe this evolution, but none has properly addressed the supply chain’s fundamental building block: the management of knowledge. Therefore, previous works have also missed adequately referring to the only element capable of delivering long-term sustainable shareholder value: people.
The Supply Network Knowledge Maturity Map (SKMap) is a reference model to understand the intermediate evolutionary stages of knowledge management within the supply network and is formed by five stages:
- Pre-supply chain stage
- Supply chain early stage
- Supply chain maturity stage
- Supply chain excellence stage
- Supply chain innovation stage or supply network management
Because organizations are hardly likely to have one single supply chain to support all their operations, it is commonly found that several “supply chains” are managed concurrently and each of these will have a particular moment within the SKMap. The complete model has eight different maturity levels and five key evolutionary outputs. Over time, companies tend to move through the maturity levels, from the functional knowledge silos to the developed supply network management environment:
- Functional silos
- Supply chain building blocks
- Tactic integration
- Supply chain governance
- Integrated business
- Selected supply chain management
- Extended supply chain management
- Supply network management
Even in the past, when the supply chain concepts had not yet been introduced, companies already had policies and routines which were the pillars of today’s best practices. But the transition from disconnected functional silos to the supply chain building blocks can only occur through the proper management of knowledge.
Attempts to communicate how supply chain maturity develops within the organizational structures have failed either due to a limited or incomplete perspective of supply chain management or due to a biased approach focusing on specifics elements of the supply chain. Some of these proposed models are based on a purely academic approach, unable to grasp the flavor of real-world dynamics. Common disciplines, usually forgotten over the years, include governance, risk management, knowledge management, human resources, and project management.
Examples of biased supply chain management approaches include expressions such as customer-centric supply chains, demand-driven supply chains, lean supply chains, and agile supply chains. All these propose value through arguments structured upon a limited perception of the complexity of supply networked companies. Although relevant, these approaches are insufficient to deliver the real promise of any business: lifelong shareholder value and significant stakeholder value.
Even though several management models have been used to suggest how companies can create and sustain adding value supply chains, none of these has succeeded in properly addressing the basic issue of managing the knowledge and its core strategies. Despite the promise that several so-called best practices promote the eventual benefits achieved by using a variety of state-of-the-art methodologies, all areas of the organization need a common basic resource: people. People represent the only true building block capable of delivering sustainable long-term shareholder and stakeholder values.
Figure 1.6 SKMap
The knowledge areas that interact in the supply network dynamics are structured according to the Supply Network Alignment Reference Model (SNAR Model). Although the SNAR model is detailed in the section in Chapter 2 called, “SKMap,” it needs an introduction at this point to support the discussion in the following pages of the book. The SNAR model organizes all knowledge areas of the business environment and emphasizes those closely related to the value network.
The supply chain building blocks define two important functional areas: planning logistics and synchronous operations. The synchronous operations knowledge area has five pillars:
- Manufacturing operations
- International logistics
To build solid foundations for bold supply chain planning, the company ought to master four key functional areas:
- Demand planning and forecasting
- Procurement planning
- Inventory planning and control
- Production planning
Tactic integration knowledge areas coordinate the efforts to consolidate the building blocks (planning logistics and synchronous operations) and set up the primary strategic connections. These strategic connections will capture customer signals, to interpret major business needs, to enable knowledge management strategies, and to facilitate information flows. Tactic integration has five pillars:
- Customer services
- Project planning
- Human resources
- Information technology
These structures build the architecture capable of aligning supply chains to other areas within the organization and to external elements, such as suppliers and customers.
Corporate governance is a complex discipline. A didactic approach to understand the concept of governance lies in the principle of balancing performance, risk, and cost. Some examples of recurrent situations that stretch organizations to their limits are as follows:
- Competition and change of players
- Product proliferation and lifecycle reduction
- Improvement of financial performance, including cost reduction
- New technologies
- Changing market regulations
- Increased customer expectations
The following is the supply chain governance group, which has three knowledge areas:
- Supply chain risk management
- Supply chain business intelligence
- Other key knowledge areas of specific interest to the business
These knowledge areas targets are as follows:
- To establish and lead supply chain risk management strategies to supply chain governance
- To define which key knowledge areas must be acquired
- To synchronize supply chain strategies with corporate governance goals
The interaction within the organization determines the creation of a diverse group called business departments that aggregate several knowledge areas such as sales, finance, controllership, quality assurance, engineering, R&D (research and development), HE&S (health, environment, and safety), marketing, IT, human resources, and regulatory. Other areas can be added as business conditions require.
Finally, the SNAR Model considers three stages for the external elements of a firm’s supply network. These stages evaluate five elements:
- Service providers
The SNAR Model has diverse applications, such as in the definition of strategies and policies that deliver shareholder value (Oliveira and Gimeno, 2014), as well as in the performance management through indicators (Oliveira and Gimeno, 2014) and in the management of customer service strategies (Oliveira and Gimeno, 2014).
To facilitate its applicability in diverse scenarios, the SNAR Model defines a coding system that identifies each knowledge area described earlier. The SNAR Model coding system is illustrated in Figure 1.8.
Figure 1.7 SNAR Model
Figure 1.8 SNAR Model Coding System