Wisdom - Peter Russel View

What is wisdom? We hear the word a lot these days—the need for wisdom, the wisdom traditions, wisdom schools. We each would like to have more wisdom. And for others to have it as well. Too much human hurt and suffering comes from lack of wisdom. There is something about wisdom that we all aspire to. But what is this quality we hold in such high regard?

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http://www.peterrussell.com:80/SP/Wisdom.php

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Modelos Menatis

A nossa visão de realidade tem algo a ver com nossos modelos mentais. Há indícios de que em nossa mente construímos quadros que utilizamos a todo instante para interpretar e tirar algum sentido do que aconteceu, está acontecendo, ou supomos virá acontecer. Quanto maior for a compreensão de uma situação e da forma como se vê o mundo, mais se aumenta a chance de evitar equívocos como em "A Visita do amigo".

Há quem diga que o reconhecimento e a comunicação de nossos modelos mentais exigem reflexão e capacidade de investigação que poucos administradores possuem. Segundo Senge,[1] um dos conceitos-chave da disciplina que consiste em trabalhar com modelos mentais é a necessidade de contrabalançar inquérito e advocacia. A maior parte dos administradores agem como advogados, pois foram ensinados a atuar com vigor e coerência na defesa de seus pontos de vista. São poucos os casos em que se recompensa o inquérito feito com perguntas incisivas, desafiando práticas e políticas estabelecidas para melhor compreendê-las.

Ironicamente, Os problemas realmente importantes que se apresentam à alta-administração são ‘problemas divergentes’ que precisam ser contemplados sob diversos pontos de vista. Só assim é possível fazer opções, mantendo-se receptivo ao exame dos possíveis erros de raciocínio. Ocorre que os designados para resolver essas questões estão condicionados a serem rígidos advogados, não inquiridores incisivos e colaborativos.[1]

Notas de aula do professor Sérgio Lins. Curso MBKM RJ10 CRIE/COPPE/UFRJ

[1]SENGE, Peter. A quinta disciplina: caderno de campo. Rio de Janeiro: Editora QualityMark, 1994.

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Mudança de paradigma

O termo 'mudanças de paradigma' vem sendo muito utilizado na literatura empresarial. Muitos tentam rotular suas teorias como mudanças de paradigma pois essa conotação é muito bem aceita pelo mercado.

Mudança de paradigma é bem aceita pelo mercado pois reflete algo inovador, mostra algo que vem mudar antigas formas de atuar para tornar-nos mais competitivos. Porém, poucas dessas 'novas' teorias realmente são mudanças de paradigma. Antes de podermos entender o que são mudanças de paradigma precisamos entender o que é um paradigma.

Para Adam Smith, um paradigma é: "Suposições compartilhadas. O paradigma é a forma como nós percebemos o mundo; água para os peixes. O paradigma explica o mundo para nós e nos ajuda a prever o seu comportamento."

Para Barker, paradigma é: "um conjunto de regras e regulamentos (escritas ou não) que faz duas coisas: (1) estabelece ou define limites; (2) diz como devemos comportar dentro desses limites para sermos bem sucedidos."

Com isso, podemos concluir que uma mudança de paradigma é uma mudança de pressupostos básicos do campo de conhecimento, uma mudança nas 'regras do jogo', um novo conjunto de regras. Paradigmas diferentes diferem significativamente em seus pressupostos básicos.

Ver também:

http://en.wikipedia.org/wiki/Paradigm_shift

http://en.wikipedia.org/wiki/Paradigm

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Paradigma na Wikipédia

Paradigma é a representação do padrão de modelos a serem seguidos. É um pressuposto filosófico matriz, ou seja, uma teoria, um conhecimento que origina o estudo de um campo científico; uma realização científica com métodos e valores que são concebidos como modelo; uma referência inicial como base de modelo para estudos e pesquisas.

Filosofia
Na filosofia grega, paradigma era considerado a fluência de um pensamento, pois através de vários pensamentos do mesmo assunto é que se concluia a idéia, seja ela intelectual ou material, depois dela realizada surgiam outras idéias até chegar a uma conclusão final. Pensar que a idéia inicial, tanto a intelectual como a material, é o paradigma da conclusão final demonstra uma incoerência com o que de fato ocorre, pois não conta com a inspiração e os diversos fluxos de pensamento.

Lingüística
Em Lingüística, Ferdinand de Saussure define como paradigma o conjunto de elementos similares que se associam na memória e, assim, formam conjuntos. O encadeamento desses elementos chama-se sintagma.

Origem: Wikipédia, a enciclopédia livre.

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Cultura da Mudança

Existe um momento em que o sistema dá um salto para o novo e o diferente, procurando se reinventar sem compromisso com qualquer padrão estabelecido.

Programas mentais compartilhados orientam o foco dos interesses e indicam a maneira apropriada de agir, provocando reflexos nas realizações e caracterizando a cultura de uma organização.

A cultura organizacional também pode ser vista como um sistema de relacionamento dos seus colaboradores com espaço, tempo, dinheiro, tecnologia, e a natureza.Ressaltamos também que a cultura engloba valores, hábitos, crenças, preconceitos e paradigmas que o ser humano dissemina e compartilha no relacionamento com seus pares.

Dentro desta linha conceitual, no âmbito das organizações o ser humano se torna um catalisador de cultura, disseminando e compartilhando realidades, valores e pressupostos, enquanto se relaciona com seus pares, seus colaboradores e os diversos parceiros de negócios da organização.

O poder e o efeito da influência cultural desse catalisador é função do papel de cada indivíduo como Agente da Cultura Organizacional.
BlogBlogs.Com.Br

Visite http://aprendendocomamudanca.blogspot.com/

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Learning

First-hand learning

This is a slow process in which an organism finds a suitable response to a situation by trial and error.

A secretary finds out how her boss prefers his letters typed. A circus horse learns how to stand on its hind-legs. A cat learns to find its way home. A tennis player learns how to serve.

Learning involves doing something about a situation and then seeing what happens. The outcome may be good, bad or indifferent.

If you eat red berries the taste may be very nasty. If the circus horse stands on its hind-legs it gets rewarded with an apple.

Gradually one learns to shape the response so it produces only pleasure and no pain. Once it has been shaped in this way the response is elicited by special situations just as an instinct response might be.

Advantages

1. The advantage of leaming over instinct is that one can develop responses to new situations.
2. Responses can be exactly adjusted to a situation. Bad
   responses can be improved or abolished.
   

Disadvantages

1. Leaming is very slow as one has to mess around with tria! and error. This is especially so with long-range learning where the reward does not come at once but only after a long sequence ofresponses (so you cannot tell at once whether you are on the right track or not).
2. Direct leaening can be dangerous. It would be very dangerous if everyone had to find out about an electric socket for themselves by putting their fingers into it.

Second-band learning

This is a sort of artificial instinct. It involves acquiring immediate responses to situations without having had to go through the slow trial and error process for oneself. It is passed-on or second-hand learning. It comes from books, TV, school, parents, other people, etc. A child learns that a car is dangerous without having to find out for himself. A student learns that vitamin B12 can cure a certain type of anaemia because his medical textbook tells him so. A man learns that an investment is risky because bis broker tell him so.

Advantages

1. Second-hand learning is very much quicker and safer than first-hand learning.
2. Second-hand learning can apply in advance to situations which have not yet been met.
3. Second-hand learning can apply to situations which would never be encountered (for instance geography lessons about far-away lands).
4. Second-hand learning can be stored and passed on (books, etc.) so that the total body of learning grows and grows.
5. Lots of different minds (some much better than one's own) can get to work on a situation and produce a much better response than one could by direct first-hand learning.

Disadvantages

1. You depend entirely on the trustworthiness ofthe source that is passing on the learning. Since you do not encounter the situation directly you can only meet it through the possibly prejudiced eyes of the person who is handing on the leaming.
2. The second-hand response is a sort of average response suitable for everybody and not as finely tuned to individual requirements as a response leamed at first hand.
3. There may easily be conflicting responses passed on by different sources of second-hand learning (e.g. parents, teachers, pals). This can be confusing.
4. Since reward and punishment are less direct there is not so much keenness to leam as with first-hand learning.

EDWARD DE BONO. Practical Thinking. Penguin Books. New York, 1971

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lnstinct

This is a fixed reaction built into the organism so that a special situation will automatically elicit a special response. The response is pre-wired. It is as direct, automatic and unchanging as the illumination of a room if you switch on the light. The response is built into the organism just as the electric wires are built into a house. No learning is required.

Animals show instinct responses to situations which they could not possibly have encountered before. A particular black silhouette moved above naive nestlings will make them cower in fright because it suggests the shape of a hawk moving through the sky. Exactly the same shape moved backwards has no effect because it looks like a harmless swan.

Instincts are precise responses set off by precise situations. Young gulls open their mouths for food as soon as a beak-like shape with a red spot on it appears above them, because this is how the mother gull looks. A piece of wood bearing a red spot will produce the same response. This type of direct response has been beautifully worked out by Tinbergen.

Advantages

1. An instinct response is immediate and perfect and requires no learning at all.
2. An instinct response is predictable and its meaning does not change. This makes it useful for communicating with other animais.

Disadvantages

1. The instinct response is fixed and cannot be adjusted to suit the situation. Nor can it be abolished if the response is inappropriate.
2. The number of fixed inbuilt responses is limited so there is no way of coping with new situations for which there is no ready-made response.

EDWARD DE BONO. Practical Thinking. Penguin Books. New York, 1971.

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Understanding

An instinct is a, response fitted to a special situation. The smell of a female moth entices the male moth from miles away. In first- or second-hand learning responses are also fitted to special situations. These become 'familiar' situations because one knows what to do about them. But what about new situations? What about unfamiliar situations which do not have any ready-made responses?

A strange woman appears on the doorstep. Immediately you try and put the situation into a familiar category to which you know the response. Is she carrying out some sort of poll? Is she trying to sell you a flag for charity? Has her car broken down? Has she just lost her way? Is she an old acquaintance whose face you have forgotten?

Understanding is the process of changing an unfamiliar process into a familiar one so that you know what to do about it. This changing around takes place in the mind as you go from one idea to another until the unfamiliar situation is seen to resemble or be derived from familiar situations. This going from one idea to another is thinking. Understanding is thinking.

If you see a white sheet flapping in the night it is frightening because it is an unfamiliar situation, but as soon as you can see it as a sheet on a washing-line then you know what to do nothing. In a foreign restaurant you try and relate the strange words on the menu to words you already know in order to understand what dishes are available. In the end you find that some of the most exotic names refer to very familiar dishes.

Understanding is a very powerful process because it is the means by which man multiplies his knowledge. He can only learn responses to a few special situations but through understanding he converts any number of new situations into already familiar situations and thus knows what to do about them at once (without having to develop a response through first-hand learning or ask for one from second-hand learning).

Advantages

1. Understanding allows one to multiply learning by using old responses in new situations.
2. With understanding you can explain new situations to other people so that they can choose their own responses instead of having to accept second-hand responses blindly.

Disadvantages

1. Understanding is limited by the available old responses (or ideas) with which to explain the new situations.
2. In trying to understand a new unfamiliar situation in terms of old ideas one may leave out a lot or distort the actual situation to make it fit the available ideas.
3. It is usually possible to understand an unfamiliar situation in several altemative ways but one is apt to settle on the first way and believe this to be the only possible way.
4. Different people may understand the same situation in quite different ways and act accordingly.

EDWARD DE BONO. Practical Thinking. Penguin Books. New York, 1971.

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FLATLAND

Em 1884, um clérigo britânico, Edwin Abbott (1838, 1896) inventou uma forma de as pessoas perceberem melhor o que seria uma quarta dimensão: inventou um mundo de duas dimensões apenas para que nós, seres de três dimensões, percebêssemos o quanto faz falta uma coordenada a mais. “Flatland” (Terra Plana) acabou se tornando um clássico da Ficção Científica.

Na fantasia vitoriana Flatland (Terra Plana), os personagens são diferentes figuras geométricas vivendo em um mundo exclusivamente bidimensional.

Quando a história começa, o narrador, um Quadrado de meia-idade, tem um sonho perturbador em que visita um reino de uma única dimensão, Terra Linear, cujos habitantes só podem se mover de ponto a ponto. Com crescente frustração, Quadrado tenta explicar a si mesmo - que é uma Linha de Linhas, de um reino onde é possível mover-se não apenas de ponto a ponto, mas também de lado a lado. Os habitantes da Terra Linear, irritados, estão a ponto de atacá-lo quando ele acorda.

Mais tarde, naquele mesmo dia, ele tenta ajudar um de seus netos, um Pequeno Hexágono, em seus estudos. O neto sugere a possibilidade de uma Terceira Dimensão - um reino com alto e baixo do mesmo modo que lado a lado. O Quadrado classifica essa noção como tola e inimaginável. Naquela mesma noite, o Quadrado tem um encontro que mudaria sua vida: uma visita de um habitante do Espaço, o Reino das Três Dimensões.

A princípio, o Quadrado se sente apenas intrigado com o visitante, um círculo peculiar que parece se modificar em tamanho e até mesmo desaparecer. O visitante explica que é uma Esfera. Apenas parecia mudar de tamanho e desaparecer porque estava se deslocando na direção do Quadrado no Espaço e, ao mesmo tempo, descendo.

Percebendo que somente com argumentação não seria capaz de convencer o Quadrado quanto à Terceira Dimensão, a exasperada Esfera cria para ele uma sensação de profundidade. O Quadrado fica muito abalado.

Houve uma estonteante e enjoativa sensação visual que não era como ver; vi uma Linha que não era Linha; um Espaço que não era Espaço. Eu era eu mesmo e não era eu mesmo. Quando consegui recuperar a voz, gritei alto em agonia: "Ou é uma loucura ou é o Inferno." "Não é nada disso", respondeu a Esfera calmamente. "É o Conhecimento: são as Três Dimensões. Torne a abrir seus olhos e procure olhar firme."

Depois de ter uma percepção de outra dimensão, o Quadrado se torna um evangelista, tentando convencer seus amigos da Terra Plana de que o Espaço é algo mais do que uma desvairada noção de matemáticos. Por sua insistência, acaba sendo preso, a bem do público.

A partir de então, a cada ano, o mais alto sacerdote da Terra Plana, o Círculo Chefe, vai examiná-lo, a fim de ver se recobrou a razão, mas o teimoso Quadrado continua a insistir que existe uma Terceira Dimensão. Ele não consegue esquecê-la nem explicá-la.

Edwin A. Abbott ©1884

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Ethnovention

EthnoventionTM is a term coined by Work Frontiers InternationalTM to describe our rapid, iterative method of studying the behavior of an organization or community using organizational ethnography and archaeology, and in the same cycle, introducing innovative interventions to enhance their behavior.

This cycle is repeated until the desired outcomes are reached. Thus the term, ethnoventionTM has sprung from a combination of the main elements of this approach: ethnography, intervention, and invention.

These quick EthnoventionTM cycles typically produce rapid improvements in the work practices of the community. This is because the community gains deep insights into their behaviors and is given the opportunity to reflect on them and change them themselves. This is much more effective than the traditional brute force method of change - being forced to implement changes designed by others without the participation or intimate knowledge of the affected community.

They also learn the new approach more quickly and deeply because they designed it and they get to keep experimenting with it until they find just the right fit for themselves.

An example of how this works is a recent knowledge audit conducted by Work Frontiers for a large non-profit organization. The desired outcomes of the knowledge audit were:

- Seek answers to the following questions:

• What knowledge do staff need to do their jobs?
• Where/whom do they get it from?
• How do they use it?
• What do they do with it when they’re finished?
• What enhances the flow & sharing of knowledge/information?
• What impedes it?

- Avoid rehashing & repeating the same old messages about what’s wrong with the organization
- Instead, focus on what works & what can realistically be done
- Seek to leverage the organization’s existing strengths & intellectual assets

Using EthnoventionTM , we sought to not only observe and record the knowledge behaviors of the organization staff. We also were there to influence them as soon and as much as possible, without inflating their expectations beyond the ability of the organization to meet them.

Two Work Frontiers ethnoventors spent about two and a half months interacting with most parts of the organization, studying its knowledge behaviors and artifacts. By immersing ourselves in the organization for this period, we were able to not only do objective data collection, but also to accumulate subjective impressions of the organization which helped us to understand the essence and root causes of the data rather than just the form of it.

Extraído de EthnoventionTM
A Powerful Tool for Organizational Reflection and Transformation
by Arian Ward, Wednesday, July 28, 1999

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Environment suitable for knowledge sharing

...knowledge is best facilitated, not managed. In fact, more time should be spent on the design of an environment conducive to sharing...and less on the formalized capture of organizational knowledge. The environment has the greatest value.

Some components needed in a well-crafted environment suitable for knowledge sharing:

• Informal, not structured
• Self-forming connections - let members of the environment decide how to interact
• Tool-rich - members should have many options for connecting and dialoguing.
• Simple/single starting point...but multiple branches/exits
• Diversity of participants - very critical...people tend to form into groups of similar people. Knowledge sharing and innovation require smashing together ideas of contradictory or unrelated nature
• Time - facilitation is best viewed as a small spark that grows into a roaring flame over time. Most managers seem to prefer explosions that die out quickly...
• Trust - knowledge sharing is about people. Safety and security (face to face or online) lead to trust. General community rules should value individual contributions and personalities.
• User-shaped - most KM initiatives begin with the mindset of building a house and then telling employees to move in an basically only hang up pictures. Instead, they should be given tools and supplies...and then allowed to create what they really need.
• Community feel - communities of practice have gained a reputation as being effective means of sharing knowledge...because we are most likely to share what we know with people we know.
• Capturing and searching - these staples of KM are still important. Newcomers should be able to observe the trials others have walked...and if done right, a KM system could link into persformance support systems...resulting in up to date resources for people...when they are needed.
  

Extraído de elearnspace

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Knowledge Sharing Environment

"Most people have a hard time dealing with the sheer number of e-mails they receive," says Andrew Mitchell, a research associate with London-based British Telecommunications E-Government Division. "We need solutions to store and summarize all this, and that will enable us to collaborate."

"I'm concerned that people don't know how to find what they need," says Mike Turillo, chief learning officer at KPMG International in Boston. "And when they finally find it, they don't know how to use it. We spend a lot of our time just trying to manage it."

To manage e-mail more efficiently and productively, both Mitchell and Turillo are testing new web-based software: Mitchell is trying out his own company's Knowledge Sharing Environment (KSE); at KPMG, Turillo is using Palo Alto, CA-based Tacit Knowledge Systems KnowledgeMail. In addition to helping people manage their e-mail, the software tracks a user's work, alerts users to important information and even notifies them that someone else in the company is doing similar work. This way, the software brings people (like A and B) together to share information and solve problems.

KnowledgeMail and KSE share similar technology, vernacular and features. KSE in particular can be traced directly to Yenta, software agent technology developed by Lenny Foner, a doctoral student at Massachusetts Institute of Technology in Cambridge, Mass.

Extraído de Feb. 15, 2000 Issue of CIO Magazine

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The Dark Side of Tacit Knowledge

Tacit knowledge by its very nature actually ‘emerges’ from the people’s heads.

The various mental processes that shape and construct certain knowledge are very difficult to comprehend. This sort of knowledge is a key behind exercising judgment in human decision-making and employing intuition or ‘gut-feeling’.

It is seen in experienced managers; because of their tacit knowledge and expertise based on this sort of knowledge, they are able to make better-informed and effective intuitive decisions. However, there is also a probability of these managers making a wrong judgment ending up in wrong decisions.

This paper was inspired by the authors’ experience when delivering presentations on knowledge management issues. In several cases members of the audience responded by observing that some tacit knowledge is inaccurate, incorrect or inappropriate.

Therefore, it is a possibility that the tacit knowledge that we are trying to capture may not be useful. Their objection seems valid when we find out various examples of big judgmental mistakes made by managers that risk and jeopardize a whole project. Through this short paper we acknowledge this fact and endeavor to explain the factors that affect the effectiveness of the tacit knowledge.

The paper also examines what can be done to make sure that tacit knowledge stays effective when captured and used in decision-making.

Extraído de Biases and Heuristics in Judgment and Decision Making: The Dark Side of Tacit Knowledge

Tayyab Maqsood, Andrew D. Finegan, Derek H. T. Walker

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Varieties of Tacit Knowledge

The distinction between tacit knowledge and explicit knowledge has sometimes been expressed in terms of knowing-how and knowing-that, respectively (Ryle 1949/1984, pp. 25-61), or in terms of a corresponding distinction between embodied knowledge and theoretical knowledge.

On this account knowing-how or embodied knowledge is characteristic of the expert, who acts, makes judgments, and so forth without explicitly reflecting on the principles or rules involved. The expert works without having a theory of his or her work; he or she just performs skillfully without deliberation or focused attention.

Knowing-that, by contrast, involves consciously accessible knowledge that can be articulated and is characteristic of the person learning a skill through explicit instruction, recitation of rules, attention to his or her movements, etc. While such declarative knowledge may be needed for the acquisition of skills, the argument goes, it no longer becomes necessary for the practice of those skills once the novice becomes an expert in exercising them, and indeed it does seem to be the case that, as Polanyi argued, when we acquire a skill, we acquire a corresponding understanding that defies articulation (Polanyi 1958/1974).

But the distinction between knowing-how and knowing-that breaks down upon examination. As Dretske has pointed out (Dretske 1988, p. 116), knowing-how involves more than just a certain technical or physical "know-how"; it also involves knowing how to obtain desired end-states, knowing what to do in order to obtain them, and knowing when to do it.

Implied in all this is that knowing how to perform action _A_ means knowing that certain things are the case regarding, for example, tools, the situation in which _A_-ing takes place, and so forth. If, as seems likely, this is the case, then knowing-how would seem to be closely bound up with, if not dependent on, some variety of knowing-that. Even if we are able to isolate the know-how that goes into _A_-ing, it isn't clear that the processes, involved -- which narrowly understood may amount to little more than automatized physical sequences or muscular reflexes -- count as cognitive in any interesting way.

Note, though, that in rejecting the distinction between knowing-how and knowing-that we are not thereby denying the existence of tacit knowledge per se; rather, we are denying its exclusive identification with procedural operations that may in the end have little to do with knowledge as such.

What is rejected is not the idea that skillful (or other) activities may rely on content states that are inaccessible to consciousness (or that conscious attention is not necessary for the exercise of a given skill), but rather the notion that a given behavior or performance stands as the proper criterion for possession of the tacit knowledge in question. Certainly there is no reason to suppose that the knowing-that which would seem to come into play even in expert performance cannot be tacit.

That an exhaustive equation of tacit knowledge with pretheoretical, skilled expertise cannot be maintained becomes particularly clear when we consider that one widely accepted paradigm of tacit knowledge is to be found in language competence (e.g., Chomsky 1986, pp. 263-273; 1980, pp. 69-70; 1972, pp. 103-104). In contrast to the variety of tacit knowledge described above, knowledge of language is not understood to constitute a skill, and thus to consist in a capacity to do something -- and consequently to have possession predicated on the appropriate behavioral criteria -- but rather is a properly cognitive capacity, and therefore defined in terms of mental states and structures that are not always or reliably manifested in behaviors or performances (Chomsky 1986, pp. 9-10; 1980, p. 48).

We might point to a third kind of tacit knowledge, which consists in what might be thought of as the presuppositions or stances many of our actions and behaviors commit us to.

Such stances are not occurrent beliefs, although they may be expressed as occurrent beliefs under the appropriate circumstances. Rather, they constitute a kind of cognitive background or disposition to believe that certain things are the case (cf Searle 1995, 1992, 1983; see also entry on The Background).

An example of this kind of tacit knowledge is that objects are rigid, a bit of knowledge few people ever bother to formulate, but which is evidenced in such basic everyday actions as sitting in a chair. Because such knowledge is expressible as a propositional content, it would seem to be a case of tacit knowing-that. (It is tacit knowledge of this sort that may ultimately explain the cognitive dimension at work in those cases held up as examples of embodied knowledge or knowing-how.) These tacit stances or presuppositions are perhaps best described as tacit beliefs or hypotheses that can be falsified under the appropriate conditions.

While the kinds of tacit knowledge underlying skills or expert performances on the one hand, and cognitive competences like knowledge of language on the other, appear to be domain-specific, this third type of tacit knowledge would appear to be more generally applicable. It seems to be the case that the cognitive content associated with tacit beliefs of this sort comes into play across a diverse set of activities and domains. Much, though by no means all, of the heterogeneous set of biological and cultural stances and capacities that Searle refers to as The Background (see entry on The Background) may be thought of as consisting in a generally applicable tacit knowledge of this sort.

Although the three conceptions of tacit knowledge outlined above differ from each other in significant ways, they do have one central feature in common, and that is the postulation of content states that are at once causally efficacious and inaccessible to (or not ordinarily accessed by) consciousness.

Extraído de tacit knowledge

Daniel Barbiero

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Five Challenges for the Next Five Years

1. Speed

The speed of business has changed a lot. We can buy almost anything on the web, and people expect to have the ability to buy things 24/7, 365 days a year because computers hum all the time. E-mail messages fill up overnight even after you deleted all messages the night before.

Business is where the buyer and seller meet. The way you do business is changing rapidly. Amazon.com is an example of this rapid movement. Capital moved away from Asia very fast when financial problems started there. The whole economy is moving faster, creating pressure on executives and employees; and decisions have to be made faster than before and globally. The speed mandates a large strategy to convey to the frontline employees on how to bring value, not just lip-service.

• KM has to deliver value, not just talk. For example, corporate yellow pages need to be developed, and communities need to move faster. Taxonomy became very important to deal with unstructured knowledge.
• KM can help Executives make better decisions, provide decision support for employees, social network support and taxonomy.

The best we can do for customers is to save them time. Business moving faster means allowing more decisions to be made at the lower level. We need intellectual working data on the desktops. We need to link to strategic imperative, which is customers' imperative

2. E-Commerce

E-Commerce is fuzzying (blurring) the boundaries. It's hard to know where one business ends and another begins. Before the fall of .com business, a survey was taken and showed that 1/3 predicted .com will prevail, 1/3 predicted that the traditional business will prevail, and 1/3 said "don't know." This year the internet commerce created $3 trillion.

E-commerce changes the fundamental ways to do business where sellers and buyers meet. It reduces error and provides real-time market data, which allows better use of the capital.

Dell can see the market real-time, so they can use that knowledge as the power to compete. When you buy something from the web, the seller knows where you came from: Google, Frederick, etc. -

This is tremendous knowledge for business. "Buyer and seller" are like conjoined twins and are interwoven. John Hagel calls this "Fuzzy Boundary of Business." Databases used to be guarded and were never shared with customers. Impact of KM can be seen in how Cisco helps customers configure their network and mediates the knowledge with their customers.

3. King Customer (Growing Power of Customer)

Automobile dealers are now faced with different negotiations with buyers because the buyers have more information about the dealer collected from the web. It became very hard to keep the price, and their profit margin was lowered from 11% to 6%.

Business has been taken over by consumers, such as decreasing telephone rates. Customer Power cannot be changed, but customer knowledge can be worked with. We have to offer customers better experiences. Therefore, Customer Relations Management becomes more important than ever before.

Customers do not like to be manipulated. You don't manage your wife. What you need to do is to make sure what you do is really valuable for customers. We need to identify unique and valuable selling.

CEO needs to ask "Why do people buy from us, not from others?" Three answers, a) cheaper, b) better quality, and c) we are innovative and responsive.

An organization needs to have cohesiveness, and how to be innovative and responsive depends on intellectual capital. We need to use intellectual assets where it matches.

Human capital is important when the talent is important, such as when you go to a certain restaurant because of the talent of the chef. When you go to McDonald's, it is predictive, cheap and fast with set recipes; this is Structural Capital McDonald's has. When you go to a restaurant because the waitresses are very friendly and you feel welcome, then you are going there for the Customer (Social) Capital. When you hire McKinsey as a consultant, you are buying their IQ, the talent - Human Capital.

When you hire Accenture, you are buying their formula, which is Structural Capital. When you are a customer for one bank, you have a long relationship with that bank - Customer (Social) Capital.

Any organization needs to have at the top level, at a minimum, one of 3 Intellectual Capitals - Human, Structural, and Customer. A beer company in Colorado is depending on structural capital and customer/social capital, when truck drivers for that beer company know to which bars to deliver beers and schmooze with workers at the bar. Customer Value proposition implies that you need to map your talent with those values.

4. Low Cost Worrier (Competition)

CEOs are struggling on how to deal with low-cost worriers, like Wal-Mart, Dell, Ameritrade, etc., that provide marginal quality service with low cost. To compete against low-cost worriers is to sell experience, such as Starbucks, to sell continuous innovation, to sell quality services, or become niche player. We need to find the competitive advantage.

5. Uncertainty on Decision Making

Management used to work with predictability since the scientific management started by Frederick Taylor. Then TQM promoted reduction of variances and control, "Execution" always matters.

We believed that people are rational. Now non-linearity and unpredictability are more common in the networked global environment. We talk about futility of forecasting, because you don't know how to plan under this environment where there exists ambiguity of outcome.

The relationship between cause and effect is obscure and the decision making model we used to use is not very helpful. We used to examine, evaluate, review options and decide--different kinds of decisions for different problems; There are four different kinds of problems (environment):

• a) Cause-effect well connected,
• b) Complicated problems,
• c) Complex Systems, and
• d) Chaos.

KM is currently helping with two problem areas. When there is a cause and effect relationship and this relation is knowable, then we can find an expert. KM can facilitate finding the expert. When we have a complicated problem, such as an airplane built by Boeing, if you disassemble the plane, you can re-assemble again because connections are fixed, knowable and predictable. KM can be useful here.

However, with complex systems, when you dissemble it and put it back together, they don't look the same. Different patterns emerge and communities are organic.

For example, an employee goes to another country to work for a year and returns to the same office. He/she will find that the organization is not the same any more. Even though it's the same office, the same people, but they don't use the same approach. We don't know how KM can help here.

Then there is Chaos, where there is no known cause and a random pattern. It's like you are lost on a mountain and are using a wrong map, then you will not be able to find a way out. It is important to know what kind of decision is needed. When you don't know the question, how do we know who needs to know what? It is a fundamental question for KM.

Thomas Stewart "Five Challenges for the Next Five Years"

Extraído de NINETEENTH KNOWLEDGE MANAGEMENT ROUNDTABLE CONVENED ON SEPTEMBER 24, 2004 AT MITRE WASHINGTON.

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Knowledge acquisition technique glossary

Card Sorting
Knowledge acquisition technique in which a collection of concepts (or other knowledge objects) are written on separate cards and sorted into piles by an expert in order to elicit properties (attributes and values).

Commentary
Knowledge acquisition technique in which the expert provides a running commentary of their own or another’s task performance. A valuable method for acquiring process knowledge. Includes various types such as self-reporting, imaginary self-reporting, self-retrospective, shadowing and retrospective shadowing.

Ladder
A ladder is a hierarchical (tree-like) network diagram. A ladder can comprise a single type of relationship throughout or have multiple relationships.
Important types of ladder include a taxonomy (aka concept ladder) which uses the "is a" relationship and a composition ladder that uses the "part of" relationship.

Laddering
Laddering is a knowledge acquisition technique that involves the construction, modification and validation of ladders. It is a valuable method for acquiring knowledge of concepts. For more information, click here.

Lessons Learnt Review
Knowledge Management technique whereby a structured group discussion takes place just after the end of a project to provide recommendations for future projects.

Peer Assist
Peer Assist is a knowledge management technique whereby a person (or team) experienced in a particular type of project helps a person (or team) unfamiliar with the same, or a similar type, of project.

Repertory Grid
Knowledge acquisition technique used to elicit properties (attributes and values) for a set of knowledge objects, rate them on a scale, and use cluster analysis to arrange and group similar properties and objects. Useful for acquiring detailed object knowledge and tacit knowledge. For more information, click here.

Extraído de Glossary

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Knowledge acquisition technique glossary

Card Sorting
Knowledge acquisition technique in which a collection of concepts (or other knowledge objects) are written on separate cards and sorted into piles by an expert in order to elicit properties (attributes and values).

Commentary
Knowledge acquisition technique in which the expert provides a running commentary of their own or another’s task performance. A valuable method for acquiring process knowledge. Includes various types such as self-reporting, imaginary self-reporting, self-retrospective, shadowing and retrospective shadowing.

Ladder
A ladder is a hierarchical (tree-like) network diagram. A ladder can comprise a single type of relationship throughout or have multiple relationships.
Important types of ladder include a taxonomy (aka concept ladder) which uses the "is a" relationship and a composition ladder that uses the "part of" relationship.

Laddering
Laddering is a knowledge acquisition technique that involves the construction, modification and validation of ladders. It is a valuable method for acquiring knowledge of concepts. For more information, click here.

Lessons Learnt Review
Knowledge Management technique whereby a structured group discussion takes place just after the end of a project to provide recommendations for future projects.

Peer Assist
Peer Assist is a knowledge management technique whereby a person (or team) experienced in a particular type of project helps a person (or team) unfamiliar with the same, or a similar type, of project.

Repertory Grid
Knowledge acquisition technique used to elicit properties (attributes and values) for a set of knowledge objects, rate them on a scale, and use cluster analysis to arrange and group similar properties and objects. Useful for acquiring detailed object knowledge and tacit knowledge. For more information, click here.

Extraído de Glossary

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DIKW - Russell Ackoff's view

According to Russell Ackoff, a systems theorist and professor of organizational change, the content of the human mind can be classified into five categories: Data, Information, Knowledge, Understanding and Wisdom.

Ackoff adds another level i.e., understanding between knowledge and wisdom. He indicates that the first four categories relate to the past; they deal with what has been or what is known.

Only the fifth category, wisdom, deals with the future because it incorporates vision and design. With wisdom, people can create the future rather than just grasp the present and past.

But achieving wisdom isn't easy; people must move successively through the other categories. A further elaboration of Ackoff's definitions follows:

• Data... data is raw. It simply exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. It does not have meaning of itself. In computer parlance, a spreadsheet generally starts out by holding data.
• Information... information is data that has been given meaning by way of relational connection. This "meaning" can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it.
• Knowledge... knowledge is the appropriate collection of information, such that it's intent is to be useful. Knowledge is a deterministic process. When someone "memorizes" information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, an integration such as would infer further knowledge. For example, elementary school children memorize, or amass knowledge of, the "times table". They can tell you that "2 x 2 = 4" because they have amassed that knowledge (it being included in the times table). But when asked what is "1267 x 300", they can not respond correctly because that entry is not in their times table. To correctly answer such a question requires a true cognitive and analytical ability that is only encompassed in the next level... understanding. In computer parlance, most of the applications we use (modeling, simulation, etc.) exercise some type of stored knowledge.
• Understanding... understanding is an interpolative and probabilistic process. It is cognitive and analytical. It is the process by which I can take knowledge and synthesize new knowledge from the previously held knowledge. The difference between understanding and knowledge is the difference between "learning" and "memorizing". People who have understanding can undertake useful actions because they can synthesize new knowledge, or in some cases, at least new information, from what is previously known (and understood). That is, understanding can build upon currently held information, knowledge and understanding itself. In computer parlance, AI systems possess understanding in the sense that they are able to synthesize new knowledge from previously stored information and knowledge.
• Wisdom... wisdom is an extrapolative and non-deterministic, non-probabilistic process. It calls upon all the previous levels of consciousness, and specifically upon special types of human programming (moral, ethical codes, etc.). It beckons to give us understanding about which there has previously been no understanding, and in doing so, goes far beyond understanding itself. It is the essence of philosophical probing. Unlike the previous four levels, it asks questions to which there is no (easily-achievable) answer, and in some cases, to which there can be no humanly-known answer period. Wisdom is therefore, the process by which we also discern, or judge, between right and wrong, good and bad. I personally believe that computers do not have, and will never have the ability to possess wisdom. Wisdom is a uniquely human state, or as I see it, wisdom requires one to have a soul, for it resides as much in the heart as in the mind. And a soul is something machines will never possess (or perhaps I should reword that to say, a soul is something that, in general, will never possess a machine). It has been contended that the sequence is a bit less involved than described by Ackoff . It is understanding that support the transition from each stage to the next. Understanding is not a separate level of its own.

ACKOFF, Russell. From Data to Wisdom, Journal of Applies Systems Analysis, 16, 3-9, 1989.

Extraído da wikipedia

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Corporate Culture

What is Corporate Culture?

Culture refers to an organization's values, beliefs, and behaviors. In general, it is concerned with beliefs and values on the basis of which people interpret experiences and behave, individually and in groups.

Cultural statements become operationalized when executives articulate and publish the values of their firm which provide patterns for how employees should behave.

Firms with strong cultures achieve higher results because employees sustain focus both on what to do and how to do it.

Vadim Kotelnikov

Corporate Culture: Surface, Middle and Deepest Levels

• Surface Level: At this level, culture is both enacted and reinforced through visible appearances and behaviors, such as physical layouts, dress codes, organizational structure, company policies, procedures and programs, and attitudes.
• Middle Level: Here, culture is manifested through our beliefs and values.
• Deepest Level: At this level, culture is manifested through basic assumptions - our long-learned, automatic responses and established opinions.

By Edgar Schein

Extraído de Corporate Culture
Achieving Higher Results Through Sustaining Employees' Focus on What To Do and How to Do It
By Vadim Kotelnikov, Founder, Ten3 BUSINESS e-COACH – Innovation Unlimited!, 1000ventures.com

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Aquisição do Conhecimento

Knowledge acquisition includes the elicitation, collection, analysis, modelling and validation of knowledge for knowledge engineering and knowledge management projects.

Issues in Knowledge Acquisition
Some of the most important issues in knowledge acquisition are as follows:

• Most knowledge is in the heads of experts
• Experts have vast amounts of knowledge
• Experts have a lot of tacit knowledge
• They don't know all that they know and use
• Tacit knowledge is hard (impossible) to describe
• Experts are very busy and valuable people
• Each expert doesn't know everything
• Knowledge has a "shelf life"

Extraído de Knowledge Acquisition

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Typical Use of KA Techniques

How and when are the many techniques described above used in a knowledge acquisition project? To illustrate the general process, a simple method will be described. This method starts with the use of natural techniques, then moves to using more contrived techniques. It is summarised as follows.

1. Conduct an initial interview with the expert in order to (a) scope what knowledge is to be acquired, (b) determine what purpose the knowledge is to be put, (c) gain some understanding of key terminology, and (d) build a rapport with the expert. This interview (as with all session with experts) is recorded on either audiotape or videotape.
2. Transcribe the initial interview and analyse the resulting protocol. Create a concept ladder of the resulting knowledge to provide a broad representation of the knowledge in the domain.
3. Use the ladder to produce a set of questions which cover the essential issues across the domain and which serve the goals of the knowledge acquisition project.
4. Conduct a semi-structured interview with the expert using the pre-prepared questions to provide structure and focus.
5. Transcribe the semi-structured interview and analyse the resulting protocol for the knowledge types present. Typically these would be concepts, attributes, values, relationships, tasks and rules.
6. Represent these knowledge elements using the most appropriate knowledge models, e.g. ladders, grids, network diagrams, hypertext, etc. In addition, document anecdotes, illustrations and explanations in a structured manner using hypertext and template headings.
7. Use the resulting knowledge models and structured text with contrived techniques such as laddering, think aloud problem-solving, twenty questions and repertory grid to allow the expert to modify and expand on the knowledge already captured.
8. Repeat the analysis, model building and acquisition sessions until the expert and knowledge engineer are happy that the goals of the project have been realised.
9. Validate the knowledge acquired with other experts, and make modifications where necessary.

Extraído de Knowledge Acquisition

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Inteligência segundo Sternberg

Intelligence

The conventional view of intelligence is that it is some relatively stable attribute of individuals, which develops as an interaction between heredity and environment.

Conventional tests of intelligence and related abilities measure achievement that individuals should have mastered several years before.

Tests such as those of vocabulary, reading comprehension, verbal analogies, arithmetic problem solving, and the like are, in part all tests of achievement.

Even abstract reasoning tests measure achievement in dealing with geometric symbols, which are skills taught in Western schools.

(...)Developing expertise is defined here as the ongoing process of the acquisition and consolidation of a set of skills needed for a high level of mastery in one or more domains of life performance.

Extraído de "Practical Intelligence in everyday life" Robert J. Sternberg (p1)

Sternberg proposes three intelligences in human cognition.

• Analytical intelligence is the ability to analyze and evaluate ideas, solve problems and make decisions.
• Creative intelligence involves going beyond what is given to generate novel and interesting ideas.
• Practical intelligence is the ability that individuals use to find the best fit between themselves and the demands of the environment.

The three intelligences, or as he also calls them three abilities, comprise what Sternberg calls Successful Intelligence: "the integrated set of abilities needed to attain success in life, however an individuals defines it, within his or her sociocultural context."

Sternberg's attempts to establish the validity of practical intelligence as a construct have yielded significant empirical work and criticism. As such, it provides a window on the issues and ideas at the core of this debate.

Practical Intelligence

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Inteligência Prática

What is Practical Intelligence?

To do well in any everyday endeavor, whether the endeavor pertains to school, work, or play, requires practical intelligence.

Although intelligence as conventionally defined maybe useful in everyday life, practical intelligence is indispensable. It is the ability to adapt to, shape, and select every day environments.

Practical intelligence, like most abilities can be viewed as a form of developing expertise. Individuals who have developed the knowledge, skills, and abilities needed to succeed in a particular domain generally are characterized as experts.

Therefore, understanding expertise and how it develops provides a method of insight into practical intelligence.

So how do we come to characterize practical intelligence as a form of developing expertise? We begin with a distinction between viewing abilities as relatively stable attributes and viewing them as developing expertise.

Extraído de "Practical Intelligence in everyday life" Robert J. Sternberg (p1)

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Innovation Process: Diversion and Conversion of Ideas

"The process of innovation is a rhythm of search and selection, exploration and synthesis, cycles of divergent thinking followed by convergence".2

Divergence, or creative synthesis, is the interlocking of previously unrelated skills, or matrices of thought. The creation of such intellectual ferment is important to innovation - the more options offered, the more likely that an out-of-the-box perspective will be available for selection.

Just hearing a very different perspective challenges the mindset of others sufficiently that they will search beyond what initially appears to be an obvious solution.

This is a reason that intellectually heterogeneous cross-functional teams are more innovative than homogenous functional ones.

As soon as a sufficient choice of innovative ideas has been generated, a solution - convergence upon acceptable action - needs to be defined and agreed upon.

Confining the discussion here to managing the tacit dimensions of knowledge three types of tacit knowledge - overlapping specific, collective, and guiding - need to be managed.

2. "The Role of Tacit Knowledge in Group Innovation", Dorothy Leonard and Silvia Sensiper, 1998
Extraído de Managing Tacit Knowledge - a Tremendous Resource for Innovation
by Vadim Kotelnikov and Ten3 East-West

Veja também "Do gelo natural à indústria da refrigeração"

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Divulgar

Diffusion (anthropology)
From Wikipedia, the free encyclopedia
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The term diffusion is used in cultural anthropology to describe the spread of cultural items — such as ideas, styles, religions, technologies, etc. — between individuals, whether within a single culture or from one culture to another.

The diffusion of innovations within a single culture applies, for example, to the acceptance of new technological products like the wristwatch and the personal computer, foods like tomato sauce and California sushi, music styles like opera and bossa nova, dressing styles like the top hat and blue jeans, ideals like democracy or feminism, and so on.

Diffusion across cultures, too, is a well-attested and uncontroversial phenomenon. For example, the practice of agriculture is widely believed to have diffused from somewhere in the Middle East to all of Eurasia, less than 10,000 years ago, having been adopted by many pre-existing cultures.

Other established examples of diffusion include the spread of the war chariot and iron smelting in ancient times, and the use of cars and Western business suits in the 20th century.

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Transferir

Knowledge transfer
From Wikipedia, the free encyclopedia
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Knowledge transfer in the fields of Organizational development and organizational learning, is the practical problem of getting a packet of knowledge from one part of the organization to another (or all other) parts of the organization.

It is considered to be more than just a communications problem. If it were merely that, then a memorandum, an e-mail or a meeting would accomplish the knowledge transfer.

Knowledge transfer is more complex because (1) knowledge resides in organizational members, tools, tasks, and their subnetworks (Argote & Ingram 2000) and (2) much knowledge in organizations is tacit or hard to articulate (Nonaka & Takeuchi 1995).

Argote & Ingram (1999) define knowledge transfer as "the process through which one unit (e.g., group, department, or division) is affected by the experience of another" (p 151). They further point out the transfer of organizational knowledge (i.e., routine or best practices) can be observed through changes in the knowledge or performance of recipient units.

The transfer of organizational knowledge, such as best practices, can be quite difficult to achieve (Szulanski 1996).

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Compartilhar

Sharing
From Wikipedia, the free encyclopedia
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Sharing is the joint use of a resource. In its narrow sense, it refers to joint or alternating use of an inherently finite good, such as a common pasture or a timeshared residence. In a broader sense, it can also include the free granting of use rights to a good that is capable of being treated as a nonrival good, such as information. Still more loosely, "sharing" can actually mean giving something as an outright gift: for example, to "share" ones food really means to give some of it as a gift.

Sharing figures prominently in gift economies, but also can play a significant role in market economies, for example in car sharing.

The issue of handling shared resources figures prominently in computer science: for example time-sharing is an approach to interactive computing in which a single computer is used to provide apparently simultaneous interactive general-purpose computing to multiple users by sharing processor time.

Sharing is a key feature in the developing field of free software and open source software, with implications for economics. This is leading to a need to review licensing, patents and copyright, and to controversy in these areas, as well as new approaches like creative commons and the GPL.

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New Ways to Work

Let’s pause for a moment. Whereas tacit knowledge is the bedrock of craft, as firms gain experience with work under craft, additional learning occurs. This isn’t just craft workers becoming better craft workers.
A new type of knowledge, an important by-product of craft work, is generated: articulated knowledge. Leveraging articulated knowledge can propel a firm toward mass production.

Ignoring it (intentionally or not) means that a firm will remain in craft work. We see this pattern again and again on the right path.

One type of knowledge is the foundation for each of the four types of work. This foundation knowledge has to be managed for a firm to excel, be it in craft, mass production, process enhancement, or mass customization. Under each type of work, learning occurs and a by-product of work is generated: additional learning and knowledge, the key ingredients for firms taking the right path.

As firms capture and codify the by-product of articulated knowledge generated under craft, the story of the right path unfolds. We call the activities underlying the codification of articulated knowledge the development transformation, and it leads to mass production work.

Through development, a firm gleans, then begins to reuse the best ways to do the work. Development, in short, is a transformation that mines the rich veins if articulated knowledge and builds a machine like organization that mass-produces.

Using tools such as time and motion studies, process engineering, and automation, development captures the best approaches discovered in craft and applies them across the company.

Development instills discipline through processes, procedures, or automation so that work can be replicated anywhere, at any time, in any amount. Mass production is characterized by repeatable tasks, hierarchical control systems, functional structures, standardized routines and processes, automation, and division of labor.

Invented Here: Maximizing Your Organization’s Internal Growth and Profitability
Bart Victor
Andrew C. Boynton
harvard business school press
Boston, Massachusetts

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Tacit knowledge is far less tangible

Explicit knowledge is what you find in computer data banks, textbooks, and academic journals; once created, it is easily captured, distributed, and used by people other than the creator.

While explicit knowledge can create a competitive advantage- as in the case of a patent for a new technology- its half-life is increasingly brief. Once we know something can be done, much less time and money is required to imitate, reverse engineer, or clone it than was needed to demonstrate its initial viability.

For example, after Intel spent $1 billion and more than a year to create its 486 microprocessor, Cyrix was able to produce a clone in approximately 18 months for just $10 million.

A second type is tacit or implicit knowledge, which you may think of as personal and context-specific "know-how." Tacit knowledge is far less tangible and so deeply embedded into an organization's operating practices that it's often nearly invisible, being described broadly as just "the way we do things around here."

For individuaIs, it's often referred to as experience or intuition; in organizations, we often call it culture. What we refer to as intuition, though, are really bits of knowledge that we've gained and combined with other bits in ways that are not easily traced or described.

Tacit knowledge includes relationships, norms, values, and standard operating procedures. Because tacit knowledge is much harder to detail, copy, and distribute, it can be a sustainable source of competitive advantage.

Extraído de MEYER, Christopher. Relentless Growth: How Silicon Valley Innovation Strategies can work in your Business. New York: The Free Press, 1998.

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