Equipamiento eléctrico

In Baxter and Sommerville’s (2011) proposal of a generic pragmatic model for socio- technical design, the model is presented as integrated development circles: 1) Organisational change process, the main objective in the organisational change cycle is to understand the behaviour and goals associated with the change activities; every time a new goal is instituted,

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the organisation should follow a specific process to ensure the quality of mapping and implementation. 2) System engineering process, this shows the activities to be conducted to choose, design and implement the information systems. 3) Socio-technical system engineering, to bridge the two by aligning organisational change to system engineering using sensitisation and constructive engagement (Baxter and Sommerville, 2010). However, this model still lacks interoperability and realisation since it does not propose an explicit detailed implementation process or consider the environment as an input to organisation internal. I see the socio-technical system in a different way. If we look more closely at the environment, generally, we can distinguish main components: the social system, business and economic system, political and regulatory system and ecological system, which are considered to be the three higher-level components responsible for producing the characteristics of the environment in which the system/enterprise operates. These guidelines and policies represent the top-down approach for imposing facts and obligations that need to be considered in the operative system. The most important fact is that these systems are all highly dynamic, characterised by uncertainty and hard to predict. Thus, the requirements of any operative system emerging from such an environment evolve continually to conform to the dynamic environment.

On the other hand, the resources components should be designed carefully to match requirements. We need the appropriate organisational structure and human capital investment, and the appropriate information and knowledge to help us to advance the work and achieve the goals. Additionally, we need to build a suitable information and technical system structure to support our business model as represented by the business activities. All in the end need financial resource and supportive assets. In general, the business model could take one of two forms: 1) An essential business model; and 2) A comprehensive and domain- based business model. The essential business model is that what enable enterprise to achieve specific purpose, through specific process and under specific circumstances. Therefore, we should look at information systems (ISs) as essential information systems represented by the business motivation, business process system, rule management system, event management system and required services to generate value. For comprehensive domain-based information systems (ISs), we need to decide on the components, configuration and size/capacity of the information systems: do we need ERP, CRM, SCM system applications and so on? Do we need to develop new systems, COTS products, or maybe cloud services? The complexity of the system could be reduced by using techniques that consider structural and behavioural aspects. A system is considered to be complex if it has many changeable components with

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many dynamic relations/interactions; behavioural aspects could also be the reason for a large, ambiguous number of possible future statuses of the component. As a result, we can distinguish four important analysis points of view: the point of view of the typical agents and their interactions in the business context need to be taken into consideration when designing socio-technical systems to improve contextual sense-making, as follows:

• The agent is outside the enterprise and looks at the service or value that the organisation can deliver to them, and what impact this organisation can bring to environment

• The agent is inside the enterprise and looking outside the organisation: who are the customers, how do we deliver value to them, and influencers of internal processes. (What are the interfaces with the customers, and how do we cope with the market). • The agent is outside the enterprise and looking at the whole value network, including

the influencers (ecology, economy, politics, etc.), and how they work together. • The agent is inside the enterprise and looking into the details (capabilities, resources,

products) that are required in order to fulfil tasks and achieve the organisation’s objectives.

The evolution of socio-technical systems should be supported with an abstract model and a reasoning technique to guide the response to changes in the socio-technical system environment and the biddable interactions of its participants, particularly within organisational models and processes, as specified in Hall and Rapanotti (2005). Sterman (2000) argued for the need for an increased understanding of dynamic and complex business problems by expanding mental boundaries; the results will appear in the form of accelerated decision-making and learning about the complex business environment.

Here the proposal of a new model conforms with complexity theory. As suggested previously, three categorised levels are proposed - environment, enterprise and resources; these are intertwined among each other in terms of both action and feedback. Additionally, the major contribution of this framework that it is intended to offer an alternative implementation model that has the ability to systematically and systemically implement socio-technical change using existing open industry standards and tools. Thus, the model offers a way to bridge the gap between the theoretical and practical domains by realising theory operationalisation. In addition, it represents work continuity in each perspective, where knowledge is produced in some stages and diffused and used in another stages. The

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research will consider feedback mechanisms to describe the dynamics and rationale for reasoning and justification as ways to fulfil a socio-technical design gap. On the IS side, during any activity involving socio-technical systems, humans should handle some of the activities, and some other activities can be fully automated. The concern of implementation is how to define a robust approach that can handle the dynamic requirements of the internal and external configuration. The research suggests that essential information systems are required for efficient business operation management and monitoring that have an agility suitable for handling changes in the environment. From the research point of view, the development will be based on modern approaches to managing information systems through Model Driven Architecture (MDA) and Service Oriented Architecture (SOA). Methods presented in much research (Meijler, 2006; Vidales, 2008; Kim, 2008; Radhakrishnan and Wookey, 2004; Jardim-Goncalves et al., 2006) show the usefulness of this approach in the realisation of research propositions.

The most innovative part of the proposed socio-technical model is the alignment among environment, requirements and actual resources, represented by two important activities in the framework: Sense-making and Constructive Fusion.

• Sense-making and reasoning: awareness and sensing around the hypothesis, expectation, design options and alternatives. This activity is concerned with how to make the most sense of the situation and the possible future directions; how we can design a stable socio-technical system by providing a clear justification and argument regarding our choices, which is based on assessing the internal and external issues/influencers. It is important to understand issues of what aspects are under enterprise control and what aspects are out of enterprise decision, however, the enterprise context and the external aspects should be well understood and assessed. Also it is important to understand the interfaces between the enterprise internal and external, and what are the formal and non-formal inputs and values for both. After all, the enterprise needs to test the robustness of its internal system during each phase of organisational design and modelling.

• Constructive Fusion: the collaborative visual design process. This starts by understanding all of the related concepts, and shares common understanding among stakeholders, ensuring that the knowledge flows smoothly among all stakeholders in order to build a robust alignment between the designed system components necessary for building a mature, modernised socio-technical system. Not only used for design

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alignment, this is also a post-design technique for providing feedback: once a change occurs in a certain component, it alerts the other related components to adapt to the change. This continuous learning through building in a collaborative manner is one of the most important characteristics of constructive fusion. A generic model for these activities is represented in Figure 13.

FIGURE 13: GENERIC DYNAMIC SOCIO-TECHNICAL MODEL

In particular, this offers a new conceptual interpretation of the current complex dynamic socio-technical environment by adapting complexity theories; new principles have emerged when complexity theories are reinterpreted to describe a way in which to handle dynamic requirements, analysis and design socio-technical systems. These have emerged from the analysis of the interviewees' answers as follows:

4.3.2.1 Principle 1 - Descriptive: The dynamics of the organisational

environment is an input to the organisation’s internal aspects

The environment is dynamic and there is an unclear interface between the environment and the internal aspects of the organisation. Therefore, it is essential for sustainable practices that the analyst should understand the change rate of environment artefacts and bridge the gap between these and the internal activities to adjust work practices to match the context requirements. This principle has been derived from aspects of complexity science theory

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related to the concepts adaptive tension and change rate, which in complexity theory are considered a reflection of ideas of the environmental dynamics where the environment has an interface with the internal activities of the organisation; this interface passes the change from/to the enterprise at different change rates and speeds via so-called strange attractors (Pavard, 2002).

4.3.2.2 Principle 2 - Requirement: Knowledge as a key asset

The enterprise’s knowledge, especially in the information era, should be managed carefully, understanding the knowledge life-cycle (creating, codifying, storing, sharing and using) across both tacit and explicit knowledge types and escalating collaborative knowledge for innovation, creativity and maintaining competitive advantage. All enterprise knowledge is based on formal and informal interactions in a dynamic network topology. In other words, human actors should learn in the real timescale; for intelligent systems applications, artificial agents should have the ability to perform a dynamic search in the real timescale, as well. The artificial agent’s learning and adaptation will be based on knowledge that will be perceived from input tools (Knowledge Management (KM) tools), and it is the agent’s responsibility to extract the required knowledge from the tool repository or database then use it according to its role which will be controlled by governance rules, and the same situation applies with the human actors. This will support McKelvey’s (2004b) notion of Distributed Intelligence (DI).

4.3.2.3 Principle 3 – Analysis Requirement: Analysts and designers as

evolvers of internal design with context

Understanding the change rate and what needs to be done to evolve with environmental change is mostly the responsibility of analysts and designers, where they need to evaluate, assess and reason about the internal structure in order to cope with changes in its context. Sterman (2000) argues for the need for increased understanding about dynamic complexity by expanding mental boundaries resulting in accelerated decision-making and learning about complex environments. Analysts can use special analysis tools and techniques to do so; intelligent systems can support the fulfilment of some areas in sensing the change in the context. Thinking and creativity are one of the important means of survival for enterprises. Without human sense, it is difficult to cope with changes in the environment. In complexity theory, the concept of modular design is a way of designing independent sub-components and attractors in a structured manner in order to help to facilitate and bring evolution into the internal level; modular designs act as ‘Cellular Networks’ containing nodes working as adaptive units characterised by high autonomy, with a certain level of control and flexibility.

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4.3.2.4 Principle 4 - Analysis and Design: Structure vs. dynamics

A first-time setup needs to be structured, and enterprises should always define their ‘as-is’ status, where the enterprise needs to clearly define where they stand by modelling the ends and means in order to facilitate the complexity: these will evolve with the context over time. The ‘to-be’ status can be defined, but by using simulation and dynamic modelling, the organisation can also illustrate the ‘to-be’ status under different circumstances and conditions. Understanding the emergent and chaotic situation makes the enterprise able to sustain itself during high-tension situations without malfunctioning. In complexity theory, adaptive tension causes several transitions, and it is noticed that critical values such as emergence and chaos could cause disruption. Environmental, organisational and technology change rates should be balanced carefully with defining clear interfaces (adaptive tension) to pass on patterns and map the artefacts.

4.3.2.5 Principle 5 - Design: Strategy and rules as a governance hub

A top-down ‘official’ and goal orientated approach provides a framework and guidelines for the internal structure. The ends and means of the organisation are not always followed strictly by the employees, nor should they be in some cases. The value lies in building a comprehensive reference model to be followed in the usual work routine and in exceptional scenarios, which are to be continually assessed and re-evaluated. In complexity theory, the heterogeneous agents interact within the environment, agents governed by rules, and the different types of rules required to: 1) govern attributes, 2) govern interaction 3) govern change. However, self-organisation is a characteristic of agents.

4.3.2.6 Principle 6 - Design: Technology architecture as enforcement

level

As the documented ‘ends’ and ‘means’ do not necessarily really reflect the real situation, and stakeholders' goals might be varied and changeable, implementing technology such as business process management, rules engines, access control policies and performance measurement with dashboards can provide the necessary control and insight about real activities. Commonly, technical systems are characterised by less autonomy and less uncertainty compared to social systems. Governing human behaviour using technology is desirable in order to reduce human error and increase monitoring. The technical architecture can provide real-time feedback that allows the consideration of new requirements once they are needed.

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4.3.2.7 Principle 7 - Design: Design vs. architecture

Design is a field of science which needs creativity and talent, whereas architecture needs systematic engineering processes with quantitative and mathematical calculations. Design needs to be more dynamic and adaptive; architecture looks more solid, usually the architecture play the role of incubator or framework for several design aspects, while designs change over time, evolve with new requirements and is shaped in different ways depending on the designer’s experience. Linearity and non-linearity, autonomy, intelligence, chaos and socialisation are all concepts contributing to both fields. Design is mostly associated with interfaces, human understanding, reflection, cognitive, mental and sense aspects, where architecture is associated with measurement, skeletons and the tangible value of human use. The activities of design and architecture represent the difference between a mental cognitive task, which has a higher level of flexibility and quality judgement, and a practical/applied task, which is more controlled and structured. In the organisational/IT domain, we first think about architecture as a boundary defining upper and lower limits, then there is a degree of flexibility to decide the design based on criteria of preference.

4.3.2.8 Principle 8 - Design and Operation: Personal goals vs.

organisational goals

As the actor, person or agent is autonomous, they are expected to have a personal goal. Everyone sets personal goals as a way to focus their effort and energy, and when working towards these goals, actors form and shape their behaviour to conform with their goals. The goal could be partnership or team shaped as well, therefore the business and organisation can define their goals to work towards an achievement. It is critical for the organisation and employees to match their goals. A negative work impact is caused when the staff of the organisation are working toward goals that contrast with the organisational goals: selection, planning and monitoring the human resources is crucial, while it is obvious that the existence of conflicting personal and organisational goals will harm employees’ motivation to achieve the organisational objectives. It appears to be easier and more useful to have artificial agents and smart ISs to do the job, since the system goals are instituted by the enterprise, although it is tricky to obtain good analysis that will reflect the business needs being implemented in their IS infrastructure as required.

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4.3.2.9 Principle 9 - Operation and Design: Autonomy vs. control

(process)

Individual agents/actors are characterised as autonomous. Putting autonomous entities into an organisational entity contains a risk of emergent behaviour ambiguity unless it is well controlled and governed. Computer science work aims to build more smart systems from dumb components, while organisation management science aims to improve the control of autonomous social entities. Hence, multi-agent systems can be used to make software systems that are more intelligent and autonomous and workflow systems that control people’s activities; this is the first step to full high-level socio-technical system integration. Furthermore, rules can govern behaviour, and processes can organise activities in a systematic and structured manner. Quality alerts and dashboards can provide more insight by pointing out misconduct that can be handled in real time. At the same time, emergent behaviour could be necessary to handle completely new and unassessed situations for self- organising towards the organisational goal, so it is important for agents/actors to have an acceptable level of flexibility to solve emergent issues.

4.3.2.10 Principle 10 - Operation: Lower-level activities form the higher

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The activities of the lower-level employees or actors actually shape the enterprise structure. Networking, formal and non-formal relationships and knowledge flow among employees are what really define strategy. Accepting the fact that heterogeneity is natural, and can give the work its unique fingerprint is necessary for innovation and creativity. As stated in complexity theory, the concept of self-organisation aims to offer the agent autonomy and flexibility to change their behaviour to conform to a new status or objectives. Many self-organising agent models have been proposed in complexity science, reflecting social behaviour in society. Since business and IT design usually use the top-down approach, the management and adaptation is bottom-up and needs to emerge from existing factors. Mixture of both in design and operation time can enhance the performance.

In document ANEJO B DISPOSICIONES RELATIVAS AL MATERIAL DE TRANSPORTE Y AL TRANSPORTE (página 35-38)