05 September 2014

Consejos para la implantación de un ERP (3/3) (45)

El mayor factor de éxito en las implantaciones es la madurez de la organización

La experiencia previa, el conocimiento de sus propios procesos y la aplicación del sentido común en la estrategia de introducción de las TIC, en una palabra, la madurez tecnológica de una organización, es determinante para llevar a buen término un proyecto de estas características, independientemente del sector o tamaño de la empresa. Los datos del estudio nos indican claramente que las pymes tienen dificultad para saber lo que se quiere o se necesita, y que la visión estratégica de su negocio está poco desarrollada, por lo que la base de los proyectos en muchos casos es poco realista. Esto provoca la aparición de situaciones no previstas durante la ejecución, y constituye un serio factor de fracaso.

La falta de formación adecuada de las personas en las que reside la capacidad de decisión les lleva a confiar en exceso en argumentos comerciales y descuidar criterios que deberían tener mayor peso

El estudio revela que existe a nivel de dirección en las pymes cierto deslumbramiento por las características funcionales de determinados productos, y que pocas veces se realiza internamente un análisis adecuado de las tecnologías existentes y posibles formas de implantación, en relación directa con las necesidades /objetivos de la organización.

En este sentido, toma enorme importancia la figura del responsable o líder del proyecto como persona hipotéticamente conocedora tanto de la tecnología como de los objetivos de la organización, un mediador que coordine la actividad con capacidad de decisión, y un equipo de trabajo interno adecuado, pero los resultados del análisis indican que existen carencias a este nivel.

Con excesiva frecuencia se escogen tecnologías y proveedores poco conocidos por la pyme y técnicas de implementación excesivamente ambiciosas o poco graduales. Los problemas se traducen en fallos en la estrategia de la implantación, y necesidad de rediseño de procesos con alto nivel de impacto.

Las herramientas de gestión integral tienen un cierto nivel de desarrollo a título operacional, pero no pueden resolver cuestiones estratégicas o próximas al ámbito de la inteligencia de negocio

La importancia dada por las pymes a que las tecnologías sobre sistemas de gestión integral se adapten a sus necesidades o actividades es grande, tal y como ha quedado patente en el estudio realizado. Ello revela un deseo de que de alguna manera las herramientas se ajusten y sean útiles para resolver cuestiones estratégicas del negocio, muy especiales ya no sólo en cada sector de actividad, sino en cada empresa. El estudio nos ha indicado que sólo una tarea de diseño realizada desde el conocimiento de la propia empresa puede dar lugar a un sistema de gestión integral acorde con sus específicas necesidades y líneas de negocio, susceptible de ajustes y nuevas adaptaciones a la cambiante realidad.

Por lo general, la implementación de un ERP se hace por fases e inicia con el área administrativa contable, área en la cual se irán a reflejar las operaciones que se ejecutan en todas las demás áreas del sistema. A través del uso de un sistema ERP, las organizaciones logran ordenar los procesos fundamentales en su forma de operar, obteniendo grandes ventajas a través de llevar sus negocios con una integración completa de sus distintas áreas, de forma automatizada, optimizada y con los controles necesarios para poder guiar y percibir la forma en que se están desempeñando.

El máximo beneficio de la implantación de un ERP se obtiene cuando todas las áreas de la empresa están totalmente integradas y cuando esta integración se realiza en el menor plazo de tiempo posible y en forma óptima. Para lograr este beneficio, es esencial contar con una metodología adecuada, la cual garantice que el éxito del proyecto, y que tome en cuenta elementos tales como la idiosincracia del medio regional de la empresa, estructuración de equipos de trabajo de las partes involucradas en la implementación y que sea lo suficientemente flexible para que cada empresa marque el paso que más le convenga, según sus prioridades para alcanzar los objetivos y metas que se impusieron a la hora de adquirir el software.

Existen 2 variables principales implicadas entre el éxito total, el éxito parcial y el fracaso. Una es la razón por la cual e adopta el nuevo sistema en la empresa y la otra es si la compañía adopta el nuevo sistema el proceso de implementación en forma estructurada.

La tecnología suele ofrecer enormes oportunidades para remover estacas en el ámbito de los negocios, pero no siempre la introducción de una nueva tecnología viene acompañada de un replanteo de las reglas, de un cambio de nuestros hábitos y de liberar las posibilidades de ir más allá de los límites que nos fijaban las antiguas limitaciones.

El ERP es una poderosa herramienta para integrar los procesos de negocio, proveer información oportuna y segura, que contiene las mejores prácticas de administración de negocios, pero sin embargo no es suficiente para llevar adelante un proceso de transformación y obtener todos los beneficios que se podrían obtener de ella. La tecnología remueve restricciones pero no crea valor por si misma. El valor se obtiene diseñando procesos innovadores que permitan a las Empresas diferenciarse y crear verdaderas ventajas competitivas. Es en el proceso de cambio y no sólo en la herramienta donde está el verdadero desafío del empresario.

03 September 2014

Principles of Systems Thinking - SEBOK (21)

This topic forms part of the Systems Thinking Knowledge Area (KA). It identifies systems principles as part of the basic ideas of systems thinking. Some additional concepts more directly associated with engineered systems are described, and a summary of system principles associated with the concepts already defined is provided.

Systems Principles, Laws, and Heuristics

A principle is a general rule of conduct or behavior (Lawson and Martin 2008). It can also be defined as a basic generalization that is accepted as true and that can be used as a basis for reasoning or conduct (WordWeb 2012c). Thus, systems principles can be used as a basis for reasoning about systems thinking or associated conduct (systems approaches).

Summary of Systems Principles

Regularity (glossary): Systems science should find and capture regularities in systems, because those regularities promote systems understanding and facilitate systems practice. (Bertalanffy 1968)

Holism (glossary): A system should be considered as a single entity, a whole, not just as a set of parts. (Ackoff 1979; Klir 2001)

Interaction The properties, capabilities, and behavior of a system are derived from its parts, from interactions between those parts, and from interactions with other systems. (Hitchins 2009 p. 60)

Relations A system is characterized by its relations: the interconnections between the elements. Feedback is a type of relation. The set of relations defines the network of the system. (Odum 1994)

Boundary (glossary): A boundary or membrane separates the system from the external world. It serves to concentrate interactions inside the system while allowing exchange with external systems. (Hoagland, Dodson, and Mauck 2001)

Synthesis (glossary): Systems can be created by choosing (conceiving, designing, selecting) the right parts, bringing them together to interact in the right way, and in orchestrating those interactions to create requisite properties of the whole, such that it performs with optimum effectiveness in its operational environment, so solving the problem that prompted its creation” (Hitchins 2008: 120).

Abstraction (glossary): A focus on essential characteristics is important in problem solving because it allows problem solvers to ignore the nonessential, thus simplifying the problem. (Sci-Tech Encyclopedia 2009; SearchCIO 2012; Pearce 2012)

Separation of Concerns

A larger problem is more effectively solved when decomposed into a set of smaller problems or concerns. (Erl 2012; Greer 2008)

View (glossary) Multiple views, each based on a system aspect or concern, are essential to understand a complex system or problem situation. One critical view is how concern relates to properties of the whole. (Edson 2008; Hybertson 2009)

Modularity (glossary): Unrelated parts of the system should be separated, and related parts of the system should be grouped together. (Griswold 1995; Wikipedia 2012a)

Encapsulation Hide internal parts and their interactions from the external environment. (Klerer 1993; IEEE 1990)

Similarity/Difference

Both the similarities and differences in systems should be recognized and accepted for what they are. (Bertalanffy 1975 p. 75; Hybertson 2009). Avoid forcing one size fits all, and avoid treating everything as entirely unique.

Dualism (glossary): Recognize dualities and consider how they are, or can be, harmonized in the context of a larger whole (Hybertson 2009)

Leverage (glossary): Achieve maximum leverage (Hybertson 2009). Because of the power versus generality tradeoff, leverage can be achieved by a complete solution (power) for a narrow class of problems, or by a partial solution for a broad class of problems (generality).

Change Change is necessary for growth and adaptation, and should be accepted and planned for as part of the natural order of things rather than something to be ignored, avoided, or prohibited (Bertalanffy 1968; Hybertson 2009).

Stability/ Change Things change at different rates, and entities or concepts at the stable end of the spectrum can and should be used to provide a guiding context for rapidly changing entities at the volatile end of the spectrum (Hybertson 2009). The study of complex adaptive systems can give guidance to system behavior and design in changing environments (Holland 1992).

08 August 2014

Concepts of systems Thinking - SEBOK (20)

This article forms part of the Systems Thinking Knowledge Area (KA). It describes systems concepts (glossary), knowledge that can be used to understand problems and solutions to support systems thinking.

The concepts below have been synthesized from a number of sources, which are themselves summaries of concepts from other authors. Ackoff (1971) proposed a system of system concepts as part of general system theory (GST); Skyttner (2001) describes the main GST concepts from a number of systems science authors; Flood and Carlson (1993) give a description of concepts as an overview of systems thinking; Hitchins (2007) relates the concepts to systems engineering practice; and Lawson (2010) describes a system of system concepts where systems are categorized according to fundamental concepts, types, topologies, focus, complexity, and roles.

Wholeness and Interaction

A system is defined by a set of elements which exhibit sufficient cohesion (glossary), or "togetherness", to form a bounded whole (Hitchins 2007, Boardman and Sauser 2008).

According to Hitchins, interaction between elements is the "key" system concept (Hitchins 2009, p. 60). The focus on interactions and holism is a push-back against the perceived reductionist focus on parts and provides recognition that in complex systems, the interactions among parts is at least as important as the parts themselves.

An open system is defined by the interactions between system elements within a system boundary and by the interaction between system elements and other systems within an environment (glossary). The remaining concepts below apply to open systems.

Regularity

Regularity (glossary) is a uniformity or similarity that exists in multiple entities or at multiple times (Bertalanffy 1968). Regularities make science possible and engineering efficient and effective. Without regularities, we would be forced to consider every natural and artificial system problem and solution as unique. We would have no scientific laws, no categories or taxonomies, and each engineering effort would start from a clean slate.

Similarities and differences exist in any set or population. Every system problem or solution can be regarded as unique, but no problem/solution is in fact entirely unique. The nomothetic approach assumes regularities among entities and investigates what the regularities are. The idiographic approach assumes each entity is unique and investigates the unique qualities of entities, (Bertalanffy 1975). A very large amount of regularity exists in both natural systems and engineered systems. Patterns of systems thinking capture and exploit that regularity.

State and Behavior

Any quality or property of a system element is called an attribute. The state of a system is a set of system attributes at a given time. A system event describes any change to the environment of a system, and hence its state:

• Static - A single state exists with no events.

• Dynamic - Multiple possible stable states exist.

• Homeostatic - System is static but its elements are dynamic. The system maintains its state by internal adjustments.

A stable state is one in which a system will remain until another event occurs.

State can be monitored using state variables, values of attributes which indicate the system state. The set of possible values of state variables over time is called the "'state space'". State variables are generally continuous, but can be modeled using a finite state model (or, "state machine").

Ackoff (1971) considers "change" to be how a system is affected by events, and system behavior as the effect a system has upon its environment. A system can

• react to a request by turning on a light,

• respond to darkness by deciding to turn on the light

• act to turn on the lights at a fixed time, randomly or with discernible reasoning.

A stable system is one which has one or more stable states within an environment for a range of possible events:

• Deterministic systems have a one-to-one mapping of state variables to state space, allowing future states to be predicted from past states.

• Non-Deterministic systems have a many-to-many mapping of state variables; future state cannot be reliably predicted.

The relationship between determinism and system complexity, including the idea of chaotic systems, is further discussed in the Complexity article.

Function

Ackoff defines function as outcomes which contribute to goals or objectives. To have a function, a system must be able to provide the outcome in two or more different ways. (This is called Equifinality). This view of function and behavior is common in systems science. In this paradigm, all system elements have behavior of some kind; however, to be capable of functioning in certain ways requires a certain richness of behaviors.

The behavior of the resulting system is then assessed as a combination of function and effectiveness. In this case behavior is seen as an external property of the system as a whole and is often described as analogous to human or organic behavior (Hitchins 2009).

Hierarchy, Emergence and Complexity

System behavior is related to combinations of element behaviors. Most systems exhibit increasing variety; i.e., they have behavior resulting from the combination of element behaviors. The term "synergy", or weak emergence, is used to describe the idea that the whole is greater than the sum of the parts. This is generally true; however, it is also possible to get reducing variety, in which the whole function is less than the sum of the parts, (Hitchins 2007).

Complexity frequently takes the form of hierarchies (glossary). Hierarchic systems have some common properties independent of their specific content, and they will evolve far more quickly than non-hierarchic systems of comparable size (Simon 1996). A natural system hierarchy is a consequence of wholeness, with strongly cohesive elements grouping together forming structures which reduce complexity and increase robustness (Simons 1962).

Encapsulation (glossary) is the enclosing of one thing within another. It may also be described as the degree to which it is enclosed. System encapsulation encloses system elements and their interactions from the external environment, and usually involves a system boundary that hides the internal from the external; for example, the internal organs of the human body can be optimized to work effectively within tighly defined conditions because they are protected from extremes of environmental change.

Socio-technical systems form what are known as control hierarchies, with systems at a higher level having some ownership of control over those at lower levels. Hitchins (2009) describes how systems form "preferred patterns" which can be used to the enhanced stability of interacting systems hierarchies.

Looking across a hierarchy of systems generally reveals increasing complexity at the higher level, relating to both the structure of the system and how it is used. The term emergence describes behaviors emerging across a complex system hierarchy.

Effectiveness, Adaptation and Learning

Systems effectiveness is a measure of the system's ability to perform the functions necessary to achieve goals or objectives. Ackoff (1971) defines this as the product of the number of combinations of behavior to reach a function and the efficiency of each combination.

Hitchins (2007) describes effectiveness as a combination of performance (how well a function is done in ideal conditions), availability (how often the function is there when needed) and survivability (how likely is it that the system will be able to use the function fully).

System elements and their environment change in a positive, neutral or negative way in individual situations. An adaptive (glossary) system is one that is able to change itself or its environment if its effectiveness is insufficient to achieve its current or future objectives. Ackoff (1971) defines four types of adaptation, changing the environment or the system in response to internal or external factors. A system may also learn, improving its effectiveness over time, without any change in state or goal.