Technology support net

Last updated
Structure of technology Structure of technology.PNG
Structure of technology

A Technology Support Net (TSN) is the required physical, energy, information, legal and cultural structures that support the development of technology core. In order to function effectively, the technology core (hardware, software and brainware) needs to be embedded in its support structure (TSN). Changes in the core then trigger requisite changes in TSN. Any core and its TSN co-evolve in a symbiotic way of mutual strengthening. At certain stage, TSN starts dictating acceptable changes in the core and ultimately becomes an effective barrier to further innovation. At such point, a time for new, disruptive technology emerges.

Contents

The entire structure of the technology core and its support network of requisite flows are sketched in Figure 1. It is clear that the architecture of the Technology Support Net functions as the main determinant of technology use, change and the rate of innovation. Milan Zeleny in his book Human Systems Management, has laid down the foundation of modern technology management, innovation and change. [1]

Technology support network (TSN) is the necessary condition for continued technology core innovation. Without matching the support network, any new technology has little chance of succeeding. The infrastructure of technology support net, when fully established, could present significant barriers to significant innovation. The process of innovation is no longer open and autonomous, but often technically and politically subservient to the “holders and owners” of the support net.

Technology, through its requisite support net, limits and predetermines the flows and types of innovation. Nowadays the processes of invention and innovation are not limited only by lack of knowledge or too narrow business criteria, but by the defenders of the existing support network (including infrastructure). The focus is not so much on hardware (which is becoming commoditized), nor software or brainware, but on the boundaries and architecture of the support net itself. [2]

Components of technology

Any technology can be divided into four key components:

Hardware

The physical structure or logical layout, plant or equipment of machine or contrivance. This is the means to carry out required tasks of transformation to achieve purpose or goals. Hardware therefore refers not only to particular physical structure of components, but also to their logical layout.

Software

The set of rules, guidelines, and algorithms necessary for using the hardware (program, covenants, standards, rules of usage) to carry out the tasks. This is the know-how, [3] which means how to carry out tasks to achieve purpose or goals.

Brainware

The purpose (objectives and goals), reason and justification for using or deploying the hardware/software in a particular way. This is the know-what and the know-why of technology. [4] That is, the determination of what to use or deploy, when, where and why.

These three components form the technology core. The components of the technology core are co-determinant, their relations circular and mutually enhancing.

The interdependence among the three components is well illustrated in the example of automobile as technology: A car consists of its own physical structure and logical layout, its own hardware. Its software consists of operating rules of the push, turn, press, etc., described in manuals or acquired through learning. The brainware is supplied by the driver and includes decisions where to go, when, how fast, which way and why to use a car at all. Computers, satellites or the Internet can be defined in terms of these above three dimensions. Any information technology or system should also be clearly identifiable through its hardware, software and brainware.

Technology Support Net

TSN is a network of flows: materials, information, energies, skills, laws, rules of conduct that circulate to, through and from the network in order to enable the proper functioning of the technology core and the achieving of given purpose or goals. Ultimately, all the requisite network flows are initiated, maintained and consumed by people participating in the use and support of the use of a given technology. They might similarly and simultaneously participate in supporting many different technologies through many different TSNs.

Sameer Kumar wrote that TSNs can be intermeshed into larger hyper networks, thereby revealing important complementary, competing and collaborating technologies. The relationship between the technology core and its requisite TSN is that of mutual enhancement and codetermination. [5]

Every unique technology core gives rise to a specific and requisite TSN and thus to a specific set of relationships among people. Ultimately, the TSN can be traced to and translated into the relationships among human participants: initiators, providers and maintainers of the requisite flows in cooperative social settings. [6] In this sense, every technology is a form of a social relationship brought forth from the background environment.

The following example describes the various social relationships among people caused by technology support net. [7] As for the automobile technology, its TSN consists of an infrastructure of roads, bridges, facilities and traffic signals, but also of maintenance and emergency services, rules and laws of conduct, institutions of their enforcement, style and culture of driving behavior, etc. A large number of people have to be organized in a specific and requisite pattern in order to enable cars to function as technology. Moreover, technology and its four components could also be defined from the vantage point of its own user or observer, not in a context-free or absolute sense. In other words, roads, bridges and traffic signals can be technologies themselves, with their own hardware, software, brainware and support nets. For example, traffic lights are a part of the TSN of an automobile, but their own hardware can be driven by their own software (a computer-controlled switching program or schedule) and brainware (purposes of safety, volume and flow control, and interaction with pedestrians). This technology core has its own support net of electricity, signal interpretations and car traffic. So the traffic light is a technology of its own. Similarly, a piece of software from some technology can itself become viewed as technology, in order to achieve specific business purposes or goals with its own hardware, software, brainware and TSN.

Functions of technology

At its most fundamental, technology is a tool used in transforming inputs into output (products) or, more generally, towards achieving purposes or goals. For example, the inputs can be material, information, skills or services. [8] The product can be goods, services or information. Such a tool can be both physical (machine, computer) and logical (methodology, technique). Technology as a tool does not have to be from steel, wood or silica, it could also be a recipe, process or algorithm.

The nature of technology has changed in the global era during the development of human history: it is becoming more integrative and more knowledge-oriented, it is available globally and it includes also logical schemes, procedures and software, not just tools and machinery. It tends to complement or extend the user, not to make him a simple appendage. In order to utilize technology efficiently and effectively, it should be viewed as a form of social relationship, with hardware and software being enabled by brainware and the requisite support network.

This is the view from Joseph Stiglitz, the recipient of the Nobel Memorial Prize in Economic Sciences (2001) on technology transfer:

" History teaches us that transferring hardware is insufficient and ineffective. Codified technical information assumes a whole background of contextual knowledge and practices that might be very incomplete in a developing country. Implementing a new technology in a rather different environment is itself a creative act, not just a copied behavior. Getting a complex technical system to function near its norms and repairing it when it malfunctions are activities drawing upon a slowly accumulated reservoir of tacit knowledge that cannot be easily transferred or ‘downloaded’ to a developing country. " [9]

Stiglitz's emphasis is on the insufficiency of information (or codified “knowledge”) and the hardware-software mindset. Information can always be “downloaded”, knowledge cannot. Knowledge has to be produced within the local circumstances and structural support.

In recent times, technology refers to a package of hardware, software, brainware – and primarily, the requisite support net which fixates, limits and predetermines the flows and types of innovation. In many modern technologies, the hardware is becoming a commodity, the least decisive component, a mere physical casing for the real power of effective knowledge contents. The enabling technology support network is often becoming the most important component of technology:

Charu Chandra described that technology organizations aim at achieving total system productivity, not task. In order to achieve this, workflow within and between departments must be integrated. This is achieved by organizing a project with interconnected tasks of activities that use inputs to produce output(s) according to common objectives and goals. One of the ways to do this is managing its effects on the support net of requisite relationships. [10] In the near future it will not be the number of computers per capita, but the density and capacity of their network interconnectedness which will determine their effective usage.

Related Research Articles

<span class="mw-page-title-main">Disruptive innovation</span> Technological change

In business theory, disruptive innovation is innovation that creates a new market and value network or enters at the bottom of an existing market and eventually displaces established market-leading firms, products, and alliances. The term, "disruptive innovation" was popularized by the American academic Clayton Christensen and his collaborators beginning in 1995,, but the concept had been previously described in Richard N. Foster's book "Innovation: The Attacker's Advantage" and in the paper Strategic Responses to Technological Threats.

<span class="mw-page-title-main">Data model</span> Model that organizes elements of data and how they relate to one another and to real-world entities.

A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner.

A management information system (MIS) is an information system used for decision-making, and for the coordination, control, analysis, and visualization of information in an organization. The study of the management information systems involves people, processes and technology in an organizational context.

<span class="mw-page-title-main">Information system</span> System that supports business decisions

An information system (IS) is a formal, sociotechnical, organizational system designed to collect, process, store, and distribute information. From a sociotechnical perspective, information systems are composed by four components: task, people, structure, and technology. Information systems can be defined as an integration of components for collection, storage and processing of data of which the data is used to provide information, contribute to knowledge as well as digital products that facilitate decision making.

Windows Management Instrumentation (WMI) consists of a set of extensions to the Windows Driver Model that provides an operating system interface through which instrumented components provide information and notification. WMI is Microsoft's implementation of the Web-Based Enterprise Management (WBEM) and Common Information Model (CIM) standards from the Distributed Management Task Force (DMTF).

<span class="mw-page-title-main">Business process modeling</span> Activity of representing processes of an enterprise

Business process modeling (BPM) in business process management and systems engineering is the activity of representing processes of an enterprise, so that the current business processes may be analyzed, improved, and automated. BPM is typically performed by business analysts, who provide expertise in the modeling discipline; by subject matter experts, who have specialized knowledge of the processes being modeled; or more commonly by a team comprising both. Alternatively, the process model can be derived directly from events' logs using process mining tools.

Enterprise software, also known as enterprise application software (EAS), is computer software used to satisfy the needs of an organization rather than individual users. Such organizations include businesses, schools, interest-based user groups, clubs, charities, and governments. Enterprise software is an integral part of a computer-based information system.

<span class="mw-page-title-main">Extended Enterprise Modeling Language</span>

Extended Enterprise Modeling Language (EEML) in software engineering is a modelling language used for Enterprise modelling across a number of layers.

<span class="mw-page-title-main">Profinet</span> Computer network protocol

Profinet is an industry technical standard for data communication over Industrial Ethernet, designed for collecting data from, and controlling equipment in industrial systems, with a particular strength in delivering data under tight time constraints. The standard is maintained and supported by Profibus and Profinet International, an umbrella organization headquartered in Karlsruhe, Germany.

A configuration management database (CMDB) is an ITIL term for a database used by an organization to store information about hardware and software assets. It is useful to break down configuration items into logical layers. This database acts as a data warehouse for the organization and also stores information regarding the relationships among its assets. The CMDB provides a means of understanding the organization's critical assets and their relationships, such as information systems, upstream sources or dependencies of assets, and the downstream targets of assets.

Knowledge Discovery Metamodel (KDM) is a publicly available specification from the Object Management Group (OMG). KDM is a common intermediate representation for existing software systems and their operating environments, that defines common metadata required for deep semantic integration of Application Lifecycle Management tools. KDM was designed as the OMG's foundation for software modernization, IT portfolio management and software assurance. KDM uses OMG's Meta-Object Facility to define an XMI interchange format between tools that work with existing software as well as an abstract interface (API) for the next-generation assurance and modernization tools. KDM standardizes existing approaches to knowledge discovery in software engineering artifacts, also known as software mining.

<span class="mw-page-title-main">DIKW pyramid</span> Data, information, knowledge, wisdom hierarchy

The DIKW pyramid, also known variously as the DIKW hierarchy, wisdom hierarchy, knowledge hierarchy, information hierarchy, information pyramid, and the data pyramid, refers loosely to a class of models for representing purported structural and/or functional relationships between data, information, knowledge, and wisdom. "Typically information is defined in terms of data, knowledge in terms of information, and wisdom in terms of knowledge".The DIKW acronym has worked into the rotation from knowledge management. It demonstrates how the deep understanding of the subject emerges, passing through four qualitative stages: "D" – data, "I" – information, "K" – knowledge and "W" – wisdom

<span class="mw-page-title-main">Function model</span>

In systems engineering, software engineering, and computer science, a function model or functional model is a structured representation of the functions within the modeled system or subject area.

<span class="mw-page-title-main">View model</span>

A view model or viewpoints framework in systems engineering, software engineering, and enterprise engineering is a framework which defines a coherent set of views to be used in the construction of a system architecture, software architecture, or enterprise architecture. A view is a representation of the whole system from the perspective of a related set of concerns.

<span class="mw-page-title-main">Core architecture data model</span>

Core architecture data model (CADM) in enterprise architecture is a logical data model of information used to describe and build architectures.

<span class="mw-page-title-main">NIST Enterprise Architecture Model</span> Reference model of enterprise architecture

NIST Enterprise Architecture Model is a late-1980s reference model for enterprise architecture. It defines an enterprise architecture by the interrelationship between an enterprise's business, information, and technology environments.

In digital communications networks, packet processing refers to the wide variety of algorithms that are applied to a packet of data or information as it moves through the various network elements of a communications network. With the increased performance of network interfaces, there is a corresponding need for faster packet processing.

Software-defined networking (SDN) technology is an approach to network management that enables dynamic, programmatically efficient network configuration in order to improve network performance and monitoring, in a manner more akin to cloud computing than to traditional network management. SDN is meant to address the static architecture of traditional networks and may be employed to centralize network intelligence in one network component by disassociating the forwarding process of network packets from the routing process. The control plane consists of one or more controllers, which are considered the brain of the SDN network, where the whole intelligence is incorporated. However, centralization has certain drawbacks related to security, scalability and elasticity.

Network functions virtualization (NFV) is a network architecture concept that leverages IT virtualization technologies to virtualize entire classes of network node functions into building blocks that may connect, or chain together, to create and deliver communication services.

A software-defined wide area network (SD-WAN) is a wide area network that uses software-defined network technology, such as communicating over the Internet using overlay tunnels which are encrypted when destined for internal organization locations.

References

  1. ↑ Zeleny, Milan (2005). Human Systems Management. World Scientific. doi:10.1142/4929. ISBN   978-981-02-4913-7.
  2. ↑ Zeleny, Milan (2012). "High Technology and Barriers to Innovation: From Globalization to Localization". International Journal of Information Technology & Decision Making . World Scientific. 11 (2): P 441. doi:10.1142/S021962201240010X.
  3. ↑ Zeleny, Milan (June 2002). "Knowledge of Enterprise: Knowledge Management or Knowledge Technology?". International Journal of Information Technology & Decision Making. 01 (2): P 181–190. doi:10.1142/S021962200200021X.
  4. ↑ Zeleny, Milan (June 2002). "Knowledge of Enterprise: Knowledge Management or Knowledge Technology?". International Journal of Information Technology & Decision Making. 01 (2): P 190–207. doi:10.1142/S021962200200021X.
  5. ↑ Kumar, Sameer (2000). "Supply chain management in theory and practice: a passing fad or a fundamental change?". Industrial Management & Data Systems. MCB UP Ltd. 100 (3): P 100–114. doi:10.1108/02635570010286168.
  6. ↑ Blahová, Michaela; Zeleny, Milan (July 2013). "Effective strategic action: Exploring synergy sources of European and Asian management systems". Human Systems Management. 32 (3): P 150–170. doi:10.3233/HSM-130792.
  7. ↑ Chui, Michael (July 2012). "The social economy: Unlocking value and productivity through social technologies". McKinsey Global Institute.
  8. ↑ "Public's Knowledge of Science and Technology". Pew Research Center. April 2013.
  9. ↑ Stiglitz, Joseph (1999). "PUBLIC POLICY FOR A KNOWLEDGE ECONOMY" (PDF). London, U.K.: The World Bank Department for Trade and Industry, Center for Economic Policy Research.
  10. ↑ Chandra, Charu (January 2001). "On object modelling for technology management in enterprise". Human Systems Management. 20 (1): P 37. doi:10.3233/HSM-2001-20106.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.