English Translation of Notes on Lessons Learned

Original document in Spanish can be downloaded here: Lecciones Aprendidas.

Notes on Lessons Learned

Background

The IDB’s ability to support the development of knowledge, policies and institutions will define the extent to which it will remain a relevant partner for the countries of the region. For this, it is necessary that it be strengthened as an institution that continuously learns from its experience and from contact with its clients, deepening the link between knowledge production and the operations program.

In response to this challenge, the IDB Institutional Knowledge and Learning Strategy 2008–2010 (GN-2479), aims to promote the creation, dissemination, exchange and use of knowledge necessary to increase development effectiveness.

This strategy stipulates that the mandate of the Knowledge Management Division (KNL / KNM) is to facilitate and improve, both within the Bank and with clients and counterparts in the Region, the flow and use of knowledge from operational experience from the bank. Part of this operational experience is manifested in Lessons Learned and Good Practices.

The purpose of this document is: (i) to share a definition of Lessons Learned and Good Practices, and ii) to propose an appropriate analysis and reflection framework for its identification, documentation and dissemination through Notes of Lessons Learned.

What do we understand by Lessons Learned?

The documentation of Lessons Learned helps convert tacit knowledge (that which is in the mind and derives from the experience of people), in explicit knowledge (that contained in documents, electronic files or objects), facilitating its dissemination.

The Lessons Learned can be defined as the knowledge or understanding gained through reflection on an experience or process, or a set of them. This experience or process can be positive or negative (eg, strengths and weaknesses in the design or implementation of a project).

For the Lessons Learned to be relevant and useful, they must be:

  • Applicable, because they have real or potential impact on operations or processes
  • Valid, because they are based on true facts
  • Significant, because they identify processes or decisions that reduce or eliminate failures or reinforce a positive outcome

These Lessons can be extracted from loan operations, technical cooperation or knowledge products and capacity building aimed at borrowing member countries, or from corporate initiatives in the areas of organizational management, operational policies and procedures and staff training, among others. The Lessons Learned allow one to:

  • Identify success factors (effectiveness, efficiency, sustainability)
  • Identify shortcomings in policies, strategies, programs, projects, processes, methods and techniques
  • Identify and solve problems through new courses of action
  • Improve future decision making and serve as a model for other interventions.

Good Practices can be defined as efficient solutions to solve a problem. These practices have been validated by its extensive use and obtaining positive results in diverse contexts, which are confirmed by evaluations. In short, Good Practices are those that:

  • have been executed with proven effectiveness
  • can be replicated and applied in other contexts yielding similar results
  • have met or exceeded the objectives set, and delivered the expected products
  • are sustainable over time

The documentation of Lessons Learned is a first step in the identification and validation of Good Practices. While the Lessons Learned can originate in

One or several projects or initiatives, Good Practices arise from the knowledge and lessons accumulated in multiple practices, in order to give rise to standards.

What do other international organizations learn from lessons learned?

For the Asian Development Bank (ADB) lessons learned are “concise descriptions of knowledge based on the experience that can be communicated through methods and techniques such as storytelling or brief reports or systematized in databases. These lessons often reflect what was done well, what should have been done differently, and how the process should be improved to be more effective in the future. ”

According to the OECD / DAC, these are “generalizations based on the experiences of evaluating projects, programs or policies in specific circumstances, which apply to broader situations. Often, the lessons highlight the strengths or weaknesses in the preparation, design and implementation that affect the performance, results and impact of projects, programs or policies. ”

How to identify Lessons Learned?

There are several methodologies that can be used to identify Lessons Learned, which allow a systematic and collective reflection. The purpose of this reflection process is to make practical recommendations, in order to improve the present or future experience and identify the new contributions made by that experience, and that advance on the existing knowledge.

Among the methodologies proposed by KNL for this purpose, they include:

  • After Action Review
  • Case Studies
  • Experience Observatories

The choice between various methodologies will depend on the purposes to be achieved, the target audience, the analytical complexity and the time and resources available.

The common and fundamental characteristic of all these methods lies in the collective nature of their reflection process. In general, the process of collecting data and perceptions to propose lessons learned should involve the various relevant actors.

It is important that the lessons identified be validated by peer review opinions of experts on the subject, before a wider dissemination.

How to document Lessons Learned?

To document Lessons Learned it is important to define:

  • What is the knowledge or lesson learned that you want to document
  • To whom do you want to transmit and for what purpose?
  • What evidence supports the new knowledge or lesson learned
  • How this new knowledge or lesson learned contributes to existing knowledge on the subject and to what extent it validates, complements and / or refutes
  • Under what specific context this new knowledge or lesson learned is relevant

There are several ways to document the Lessons Learned: the Memory Help of After Action Review; the narration and analysis of the Case Study and the Experience Observatory Report, by way of examples.

In order to consolidate a friendly and accessible set of Lessons Learned, KNL proposes a series of Notes of Lessons Learned that can be published in printed and electronic format and collected in a searchable database.

The Note of Lessons Learned that is proposed consists of a brief analytical document, which presents the lessons derived of a collective reflection process in which those involved in the experience or set of experiences analyzed participate.

KNL recommends that the Lessons Learned Note include the following sections:

Background (brief description of the experience analyzed and the context in which it takes place)

  • Results achieved (outputs, outcomes and impact achieved to date)

Costs and other financial and non-financial resources involved

Lessons identified and critical factors for obtaining results (ex: elements that facilitate and hinder, identified risks and attention strategy)

  • Assumptions for the implementation of these lessons in other contexts
  • References (contact details, project bibliography, similar experiences)

In addition, it is important to:

  • Prepare the Note in conversational language, using active verbs
  • Minimize the use of acronyms
  • Include citations and references whenever
  • Costs and other financial and non-financial resources involved
  • Recognize the participation and effort of relevant teams that made possible the analysis and documentation of their experience

A Note of Lessons Learned should not exceed 5 pages (2500 words).

KNL proposes to support the Bank’s organizational units and the executing units in the preparation, publication and dissemination of the Lessons Learned Notes. We invite interested personnel to contact any of the KNL / KNM Officers identified in this text as contact points.

Notes on Eight Factors for Collaborative Work Success

Eight Factors for Collaborative Work Success
Harvard Business Review
by Lynda Gratton, Professor of Management Practice at the London Business School, and  Tamara J. Erickson, one of the top 50 global business thinkers in 2015.

Notes

  • Investing in signature relationship practices.
  • Modeling collaborative behavior.
  • Creating a “gift culture.”
  • Ensuring the requisite skills.
  • Supporting a strong sense of community.
  • Assigning team leaders that are both task- and relationship- oriented.
  • Building on heritage relationships.
  • Understanding role clarity and task ambiguity.

***

In assembling and managing a team, consider the project you need to assign and whether the following statements apply:

__ The task is unlikely to be accomplished successfully using only the skills within the team.

he task must be addressed by a new group formed specifically for this purpose.

__ The task requires collective input from highly specialized individuals.

__ The task requires collective input and agreement from more than 20 people.

__ The members of the team working on the task are in more than two locations.

__ The success of the task is highly dependent on understanding preferences or needs of individuals outside the group.

__ The outcome of the task will be influenced by events that are highly uncertain and difficult to predict.

__ The task must be completed under extreme time pressure.

If more than two of these statements are true, the task needs revision.

***

new teams, particularly those with a high proportion of members who were strangers at the time of formation, find it more difficult to collaborate than those with established relationships.

…when 20% to 40% of the team members were already well connected to one another, the team had strong collaboration right from the start.

One important caveat about heritage relationships: If not skillfully managed, too many of them can actually disrupt collaboration. When a significant number of people within the team know one another, they tend to form strong subgroups— whether by function, geography, or anything else they have in common. When that happens, the probability of conflict among the subgroups, which we call fault lines, increases.

Collaboration improves when the roles of individual team members are clearly defined and well understood—when individuals feel that they can do a significant portion of their work independently. Without such clarity, team members are likely to waste too much energy negotiating roles or protecting turf, rather than focus on the task.

Strengthening your organization’s capacity for collaboration requires a combination of long-term investments—in building relationships and trust, in developing a culture in which senior leaders are role models of cooperation—and smart near-term decisions about the ways teams are formed, roles are defined, and challenges and tasks are articulated. Practices and structures that may have worked well with simple teams of people who were all in one location and knew one another are likely to lead to failure when teams grow more complex.

Notes from Cracking the Code of Sustained Collaboration

Executive Education at Harvard Business School

Notes from Cracking the Code of Sustained Collaboration
November–December 2019 Issue of Harvard Business Review

By Francesca Gino, a behavioral scientist and the Tandon Family Professor of Business Administration at Harvard Business School and author of the
books Rebel Talent: Why It Pays to Break the Rules at Work and in Life and Sidetracked: Why Our Decisions Get Derailed, and How We Can Stick to the Plan.

Notes

What’s needed is a psychological approach to collaborative work.
Leaders think about collaboration too narrowly: as a value to cultivate but not a skill to teach.

…widespread respect for colleagues’ contributions, openness to experimenting with others’ ideas, and sensitivity to how one’s actions may affect both colleagues’ work and the mission’s outcome.

Businesses have tried increasing collaboration through various methods, from open offices to naming it an official corporate goal. While many of these approaches yield progress—mainly by creating opportunities for collaboration or demonstrating institutional support for it—they all try to influence employees through superficial or heavy-handed means, and research has shown that none of them reliably delivers truly robust collaboration.

the company’s best collaborators—those known for adding value to interactions and solving problems in ways that left everyone better off— are adept at both leading and following, moving smoothly between the two as appropriate. That is, they’re good at flexing. Because flexing requires ceding control to others, many of us find it difficult.
While listening and empathizing allow others more space in a collaboration, you also need the courage to have tough conversations and offer your views frankly.
By balancing talking (to express your own concerns and needs) with asking questions and letting others know what your understanding of their needs is, you can devise solutions that create more value. With a win-win mindset, collaborators are able to find opportunities in differences.
respect, my research shows, fuels enthusiasm, fosters openness to sharing information and learning from one another, and motivates people to embrace new opportunities for working together.
But this dynamic must be set in motion by those in charge. Many leaders—even ones steeped in enlightened management theory—fail to consistently treat others with respect or to do what it takes to earn it from others.

6 Keys Tools

1. Teach People to Listen, Not Talk
a) Ask expansive questions.
b) Focus on the listener, not on yourself.
c) Engage in “self-checks.”
d) Become comfortable with silence.
2. Train People to Practice Empathy
a) Expand others’ thinking.
b) Look for the unspoken.
3. Make People More Comfortable with Feedback
a) Discuss feedback aversion openly.
b) Make feedback about others’ behavior direct, specific, and applicable.
c) Give feedback on feedback.
d) Add a “plus” to others’ ideas.
e) Provide live coaching.
4. Teach People to Lead and Follow
a) Increase self-awareness.
b) Learn to delegate.
5. Speak with Clarity and Avoid Abstractions
6. Train People to Have Win-Win Interactions

Translation of Brief Inventory of Models for Knowledge Management in Organizations

Brief Inventory of Models for Knowledge Management in Organizations

by Lic. Marlery Sánchez Díaz.
Departamento de Docencia e Información Científico-Técnica.
Centro Nacional de Biopreparados.
La Habana , Cuba.

SUMMARY

Knowledge, an intangible asset of the organization, has been identified as a key element of organizations and society to achieve competitive advantages. Given this reality, a new approach has emerged within business management: knowledge management. As a tool to represent this phenomenon in a simplified, summarized, symbolic, schematic way; delimit any of its dimensions; allow approximate vision; describe processes and structures, orient strategies; provide important data; Knowledge management models appeared. Some of the models developed for knowledge management are reviewed and its principles and contributions are presented.

Keywords: Knowledge management, models.

ABSTRACT

The knowledge, an intangible asset of organization, has been identified as a key item of the organizations and the society to achieve competitive advantages. Facing this reality, a new approach within the entrepreneurial management, knowledge management, has arisen. The knowledge management models appeared as a tool to represent this phenomenon in a simplified, summarized, symbolic and schematic way; to define some of their dimensions; to allow an approximate vision; to describe processes and structures, to orient strategies; and to contribute with important data. Some of the models developed for the management of knowledge are reviewed and its principles and contributions are exposed.

Knowledge, an intangible asset of an organization, has been identified as a key element for achieving competitive advantages, even above the tangible ones. This has led to the emergence of a new approach within business management: knowledge management.

As a tool to represent this phenomenon in a simplified, summarized, symbolic, schematic way; delimit any of its dimensions; allow approximate vision; describe processes and structures, orient strategies; provide important data; Knowledge management models appeared.

It is appropriate to point out that in the literature there are as many models as authors have studied the subject; all with common elements and differentiators, from their own contributions.

Next, some of the main models for knowledge management in the literature on the subject will be reviewed.

Methods

With the objective of obtaining a coherent and integral vision of the different existing models of knowledge management, the accessible literature on the subject under study was reviewed. In order to locate the relevant works available on the Internet, the well-known Google search engine, the journal Information Sciences, was published by the Institute of Scientific and Technological Information (IDICT) of Cuba; as well as other unpublished sources of information such as diploma work carried out at the Faculty of Communication of the University of Havana.

KNOWLEDGE MANAGEMENT

According to the documents consulted, there are two ways to approach knowledge management in the different models because some are based on the measurement of intellectual capital and others on the management of knowledge itself.

This makes it necessary to address knowledge management and intellectual capital first, because both concepts are ambiguously defined in the literature and it is difficult to recognize their differences.

From the concepts offered by different authors: Artiles, 1 Ugando, 2 (Ponjuán Dante G.. Information Management. 2001. Unpublished observations), it can be said that intellectual capital is the sum of human, structural and relational capital. They are all those elements and forces, not tangible, including tacit and explicit knowledge (brands, patents, software, etc.), that within a specific strategic framework, lead to the creation of value of physical, tangible assets, and influence directly in the added value of organizations. It is the capital that resides in people’s heads. Try to convert explicit knowledge of the organization into measurable monetary benefits.

The resources of an organization can be classified as tangible or intangible. Intangible assets are those that have value without being material or physical and are located in human beings or are obtained from the processes, systems and culture of the organization.

Intellectual capital is composed of the knowledge of the organization and represents the intangible assets of a company, namely:

  • Human capital: is the value of knowledge created by the people who make up the organization; in this, the tacit and explicit knowledge of the organization resides. The combination of knowledge, experience, skills, education, skills, learning, values, attitudes, and ability of members of an organization to perform the task they handle. Understands the skills and potential of workers. It includes the values ​​of the organization, its culture and its philosophy. They are not owned by the company, because they belong to the workers, when they go home they take them with them. It is the basis of the generation of other types of intellectual capital, but if the organization does not own it, it cannot buy them, only rent them for a period of time. Talking about human resources means identifying with the bearer of certain knowledge and with a potential value. At the moment in which this resource is put in function of the organization, the potential value that it had accumulated can say that it is transformed into a true human capital, it transfers its value to that of the organization to which it belongs.
  • Structural capital: it is the value of knowledge created in the organization. It is determined by the culture, standards, processes and formed by programs, databases, patents, brands, work methods and procedures, models, manuals, management and management systems. It is all that is left in the organization when its members go home. It is owned by the organization. It is the systematized knowledge, explicit or internalized by the organization. It is the result of intellectual activities and, when solid, facilitates an improvement in the flow of knowledge, as well as an improvement in the effectiveness of the organization.
  • Relational capital: it arises through the exchange of information with external parties, it is the organization’s relations with the agents in its environment, it refers to the client portfolio, relations with suppliers, banks and shareholders, cooperation agreements and strategic, technological, production and commercial alliances, to trademarks and to the image of the company, media and alliances. These assets are owned by the company and some of them can be legally protected, as is the case with trademarks. Depending on a relationship with third parties, it cannot be completely controlled by the organization.

Knowledge management on the other hand, is the set of processes and systems that make the intellectual capital of the organization grow.

To manage intellectual capital, knowledge management is necessary in its two dimensions:

  • Hard. Harder or formalizable aspects. Within this, there are those included in intellectual capital with possible quantification: structural capital and relational capital.
  • Soft. Softer or non-formalizable aspects. Within this, there is the fundamental variable of intellectual capital: human capital, that is, the treasured knowledge in the brains of employees as a result of learning.

Based on the contributions of Edvinsson, 3 Torrado del Rey, 4 and Wiig, 5 common elements and differences between knowledge management and intellectual capital management can be established.

Knowledge Management

  • It relates to people, intelligence and knowledge. Human concepts.
  • Try to formalize and systematize the processes of identification, administration and control of intellectual capital.
  • Presents a tactical and operational perspective.
  • It is more detailed.
  • It focuses on facilitating and managing those knowledge related activities, as its creation, capture, transformation and use.
  • Its function is to plan, implement, operate, direct and control all activities related to knowledge and the programs that are required for effective capital management.
  • It is done with the objective of acquiring or increasing the inventory of intangible resources that create value in an organization and therefore, is a part of the more global concept of intangible assets management – the intangible resources of an organization generally grow due to flows of information or knowledge and tangible resources grow by money flows.
  • Seeks to improve the potential of creating values ​​in the organization, through the more efficient use of intellectual knowledge.

Intellectual Capital Management

  • It relates to people, intelligence and knowledge. Human concepts.
  • Has a strategic and managerial business perspective with some tactical derivations.
  • It focuses on the construction and management of intellectual assets.
  • Its function is to consider the entire intellectual capital of the company as a whole.
  • Knowledge management is located within this framework, but intellectual capital management covers much more space than knowledge management.
  • Try to level human and structural capital.
  • Seeks to improve the value of the organization, from

of the generation of potentialities through the identification, capture, leveling and recycling of intellectual capital. This includes value creation and value extraction.

SELECTION OF MODELS FOR KNOWLEDGE MANAGEMENT

Knowledge creation process (Nonaka and Takeuchi, 1995) distinguishes two different types of knowledge (tacit and explicit). It is the movement and transfer of information between one and the other that explains the generation of knowledge – tacit knowledge is one that is not physically palpable, but is internal and property of each individual and explicit knowledge is that which can be expressed or represented by physically storable and transmissible symbols. The dynamic and constant mechanism of relationship between tacit knowledge and explicit knowledge is the basis of the model. It announces the processes of knowledge conversion:

– From tacit to tacit (socialization process): Individuals acquire new knowledge directly from others, from sharing experiences, learning new skills through training through observation, imitation and practice.

Try to incorporate into the traditional measurement systems for management, some non-financial aspects that condition the obtaining of economic results. It offers a conceptual framework to know if the appropriate processes and people are used to obtain a better business performance. It provides a list of intangible resources that can be managed and treated from the point of view of knowledge. It proposes two fields of reflection: one of them based – strategic pretension of training – and the other operative – how to establish the hierarchy of training gaps.

It introduces into the information system available to those who make decisions, strategic variables to consider beyond the conventional ones and which may indicate substantial training gaps before forgotten or difficult to justify. The model integrates the financial indicators (from the past) with the non-financial (from the future), and integrates them into a scheme that allows understanding the interdependencies between its elements, as well as coherence with the company’s strategy and vision. Within each block, two types of indicators are distinguished: driver indicators (conditioning factors of others) and output indicators (result indicators).

The model has four blocks:

  • Financial perspective: it considers the financial indicators as the final objective; He believes that these should not be substituted, but complemented with others that reflect business reality.
  • Customer perspective: identifies values ​​related to customers. For this, it is necessary to previously define the target market segments and perform an analysis of their value and quality.
  • Perspective of internal business processes: Analyzes the adequacy of the internal processes of the company in order to obtain customer satisfaction and achieve high levels of financial performance. To achieve this objective, an analysis of the internal processes from a business perspective and a predetermination of the key processes through the value chain are proposed. Three types of processes are distinguished: 1.- Innovation processes (difficult to measure). 2.- Operations processes. They are developed through quality analysis and reengineering. 3.- After-sales service processes. Criticize the conception of training as an expense, not as an investment.
  • Learning perspective and improvement Classifies the assets related to learning and improvement in: Capacity and competence of people (employee management); Information systems; as well as Culture-climate- motivation for learning and action (fig. 2).

The model is based on the revision of a list of qualitative issues. It affects the need to develop a methodology to audit information related to intellectual capital. Intangible assets are classified into four categories, which constitute intellectual capital:

– Market assets: These are those that derive from a beneficial relationship of the company with its market and its customers and therefore provide a competitive advantage in the market. They are the cause of some companies being acquired, at times, for amounts greater than their book value. Its indicators are: brands, customers, company name, order book, distribution, collaboration capacity …

– Human assets: The importance of people in organizations for their ability to learn and use knowledge is emphasized. The third millennium worker will be a knowledge worker, who will be required to participate in the company’s project and a capacity to learn continuously. Indicators: generic aspects, education (knowledge base and general skills), professional training (skills needed for the job), specific knowledge of the job (experience), skills (leadership, teamwork, problem solving, negotiation, objectivity , thinking style, motivational factors, understanding, synthesis, …

– Intellectual property assets: These are property rights that come from the intellect. They grant an additional value that supposes for the company the exclusivity of the exploitation of an intangible asset. Its indicators are patents, copyright, design rights, trade secrets …

– Infrastructure assets: Includes the technologies, methods and processes that allow the organization to function. It includes: business philosophy, organizational culture or ways of doing things in the organization – it can be an asset or a liability depending on the alignment with the business philosophy – information systems, existing databases in the company (knowledge infrastructure extensible to the entire organization (fig. 3).

Study the relationship between intellectual capital and its measurement, as well as organizational learning. Knowledge capital is composed of a holistic system of three elements: human capital, structural capital and client capital (fig. 4).

Study the cause-effect relationships between the different elements of intellectual capital, as well as between it and business results. In this model, the three blocks that are common to most models are established: human capital, structural capital and relational capital (fig. 5).

It is not structured in types of capital but consists of five areas of focus. It provides a balance between: the past (financial approach); the present (customer approach – a different type of intellectual capital), the human approach – in the center, the first half of the intellectual capital model – and the process approach – measures a large part of the structural capital; as well as the future – the innovation and development approach – the other part of structural capital (fig. 6).

It is based on the importance of intangible assets. Identify:

  • People’s competences: Includes the competencies of the organization such as planning, producing, processing or presenting products or solutions – which would be human capital).
  • Internal structure: It is the structured knowledge of the organization such as patents, processes, models, information systems, organizational culture, the people who are responsible for maintaining this structure – which would be the structural capital.
  • External structure: Includes relationships with customers and suppliers, trademarks and the image of the company – which would be the relational capital. These intangible assets, form what is known as the invisible balance.

For the measurement and evaluation of these, three types of indicators are proposed within each of the three blocks: – growth and innovation indicators: they reflect the future potential of the company; – efficiency indicators: they inform the extent to which intangibles are productive (assets) and stability indicators: they indicate the degree of permanence of these assets in the company (fig. 7).

It emerged as a result of the need to have a model for the management of intangible assets. It is a methodology for the classification, valuation and management of the company’s patent portfolio, as a first step, which extends to the measurement and management of other intangible assets of the company – with a high impact on financial results. The model interferes the forms of capital to generate value to the company. The structure of intellectual capital would be formed by human capital, organizational capital and the organization’s capabilities to codify and use knowledge – including culture, norms and values ​​- and client capital (fig. 8).

It responds to a process of identification, selection, structuring and measurement of assets so far not evaluated in a structured way by companies. It aims to offer managers relevant information for decision making and provide information to third parties about the value of the company. The model, therefore, aims to bring the value of the company closer to its market value, as well as to inform about the organization’s ability to generate sustainable results, constant improvements and long-term growth. Link intellectual capital with the company’s strategy; It is a model that each company must customize, it is open and flexible, it measures the results and the processes that generate them; It is applicable, relates all components, combines different units of measurement. It presents blocks based on the grouping of intangible assets according to their nature (human capital, structural capital and relational capital). Locate elements, such as the intangible assets considered, within each block. Each company, depending on its strategy, will choose specific elements and indicators to measure and evaluate the elements where the definition of indicators must be adjusted to each particular organization (fig. 9).

The concept of intellectual capital is the center of Professor Bueno’s argument, whose model is based on strategic direction through competencies. The evidence that intangible assets and assets are increasingly important for economic reality has motivated the idea of ​​knowing as much as possible the intangible capital that a company can have. In this way, this intellectual capital is estimated in the following way: it is the difference obtained between the value that the market gives to the company and the value that exists for that company.

Also, intangible capital is the valuation of intangible assets created by the company’s knowledge flows. In addition, this means that the proposal for a greater vision of the future for a company is to enrich intangible capital as much as possible, to create what has come to be called a “Strategic Management by competencies”. To structure these ideas, attitudes or values ​​are used, that is, what the company wants to be, of knowledge based on what the company does and, finally, of capabilities, which is an estimate of what it is capable of doing ( fig. 10).

It exposes the factors that condition the learning capacity of an organization, as well as the expected results. One of the essential characteristics of the model is the interaction of all its elements, which are presented as a complex system in which influences occur in every way. The organizational structure, the culture, the leadership, the learning mechanisms, the attitudes of the people, the ability to work in a team, etc., are not independent, but are connected to each other (fig.11).

It aims to measure and manage intellectual capital in organizations. This model is useful for any company, regardless of its size. He proposes to divide the intellectual capital into four blocks:

  • Human capital: Includes knowledge assets (tacit or explicit) stored in people – technical knowledge, experience, leadership skills, personal stability.
  • Organizational capital: It covers the assets of systematized knowledge, explicit or internalized by the organization, whether in: explicit ideas object of intellectual property (patents, trademarks); materializable knowledge in infrastructure assets that can be transmitted and shared by several people – description of inventions and formulas, information and communication system, available technologies, documentation of work processes, management systems, quality standards-; internalized knowledge shared within the organization in an informal way – ways of doing the organization: routines, culture, etc.).
  • Share capital: Includes the knowledge assets accumulated by the company as a result of its relations with agents in its environment – knowledge of the relevant clients, strategic alliances of the company with customers, suppliers, universities, etc.
  • Innovation and learning capital: Includes knowledge assets capable of expanding or improving the portfolio of knowledge assets of other types, that is, the company’s potential or innovative capacity. The model has a dynamic character, insofar as it also seeks to reflect the transformation processes between the different blocks of intellectual capital. Static and dynamic are integrated in the same model. A differential characteristic of this model with respect to the others studied, is that it allows calculating, in addition to the variation of intellectual capital that occurs between two periods of time, the effect that each block has on the remaining ones – human, organizational, social and social capital of innovation and learning – that is, the variation of intellectual capital, the increase or decrease of capital between each of the blocks and the contribution of a block to the increase / decrease of another block. To obtain the necessary indicators to measure human, organizational, social and innovation and learning capital, these blocks are divided into different groups according to the nature of intangible assets (fig. 12).

It recognizes the need to accelerate the flow of information that has value, from individuals to the organization and back to individuals, so that they can use it to create value for customers. Its novelty is that, from the individual perspective, there is a personal responsibility for sharing and making knowledge explicit for the organization and from the organizational perspective it also implies a responsibility with the creation of the support infrastructure for the individual perspective to be effective, Develop processes, culture, technology and systems that allow capturing, analyzing, synthesizing, applying, valuing and distributing knowledge (fig. 13).

It is an instrument of evaluation and diagnosis. The model proposes four facilitators: leadership, culture, technology and measurement; that favor the process of managing organizational knowledge (fig. 14).

Although it was created in 1988, it is a year later that it was modified to include aspects related to knowledge management, which underline the importance of innovation and learning. In the criteria Collaborating agents and resources, the management of information and knowledge was included, and in the Processes criterion the improvement and innovation were emphasized such as leadership, strategy, structure, processes, people, results and the measurement (fig. 15).

It is at the same time, a new method and strategic management tool that allows companies to benchmark their essential competencies or their intellectual capital with the best competitors in business activity. It is built around the key factors and criteria of competitiveness in the context of global markets. When used in an orderly and systematic way, competitive balances are obtained that complement and refine the economic-financial balance sheets and lead companies to obtain the maximum benefit from existing intellectual capital (fig. 16).

It allows companies to “Benchmarking” their essential innovation capabilities or their intellectual innovation capital with the best competitors in business activity. It is built around the key factors and criteria of competitive innovation in the context of global markets. When used in an orderly and systematic manner, innovation competitiveness balances are obtained that complement the economic-financial balance sheets and lead companies to obtain the most out of the intellectual capital of innovation (fig. 17).

It makes it possible to use the intellectual capital of the companies, organizations and institutions of the nearby geographical environment (clusters, microclusters or territory) to build the best possible organization in the form of a network that needs a specific business model, thus complementing the internal intellectual capital with this capital external intellectual of a relational nature. It serves to select and evaluate the different alternative locations that a given company chooses to develop its activities in order to maximize the intellectual capital of the environment in the process of building the organization in the form of a network. It shows how the intelligent company that is organized in the form of a network builds its essential competences thanks to the relationships that allow it to access the competencies and resources of other companies, organizations and institutions; some of them located within a specific cluster and others outside it. Part of the principle that relations with companies, organizations and institutions located in the cluster have a primary character because they allow joint or complementary operations with the intelligent company in question, as well as the transmission of tacit knowledge that provide a higher value (fig .18).

It constitutes a first scientific and therefore systematic approach to the professionalized management of intangible assets in cities. It is a model of management of the intellectual capital of cities that has a double focus. On the one hand, generalizing, which seeks to measure and manage the intellectual capital common to all microclusters of economic activities of the city and on the other, particularist, which aims to measure and manage the intellectual capital of each relevant microcluster of the city.

FINAL CONSIDERATIONS

There are common aspects among the exposed models, for example, the parts in which they make up the intellectual capital or the definitions that are made of each of the parties, but there are also a large number of differentiating elements. However, the particular importance of each model lies precisely in the concepts on which each one relies, the new ideas that are proposed, the organizational and business changes they entail. Thus, the models of Kaplan and Norton and Navigator Skandia treat in an excellent way the identification of needs and decision-making, an aspect considered as fundamental within the knowledge management system; Bueno, Canadian Imperial Bank and Andersen models work very well in the internal development of knowledge, an essential issue for knowledge management in an organization; and how the Nonaka and Takeuchi and Artur Andersen models develop the capitalization of knowledge, one of the most difficult processes in an organization.

Bibliography

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Ugando Peñate M. La gestión del conocimiento y la utilización de las tecnologías de la información y de las comunicaciones en la creación de valor en los proyectos de innovación. En: Memorias del Congreso Internacional de Información, INFO’ 2004, abril 12-16, 2004 [CD ROM]. La Habana : IDICT, 2004. Edvinsson L. Developing Intellectual Capital at Skandia. Long Range Planning 1997;30(3):372.

Torrado del Rey G, Carrascosa Ramírez F, Sevillano Tinaquero R, Silva Perucha C, Sanz Jiménez C, Vaquero Badillo C, et. al. Modelos de capital intelectual. [en línea]. Disponible en: http://www.uam.es/ personal_pdi/economicas/pomeda/docs/modelos_grupo1.doc[Consultado: 15 de julio del 2005].

Wiig KM. Integrating Intellectual Capital and Knowledge Management. Long Range Planning 1997; 30 (3):372.

Nonaka I, Takeuchi H. La organización creadora de conocimiento. Cómo las compañías japonesas crean la dinámica de la innovación. México DF: Oxford University Press, 1999.

Kaplan RS, Norton DP (1996) “Using the Balanced Scorecard as a Strategic Management System” Harvard Business Review 1996;(1):76.

Brooking A. Intellectual Capital. Core Asset for the Third Millennium Enterprise, 1a ed. London: International Thomson Business Press, 1996.

Davenport T, Prusak L. Conhecimento Empresarial: como asorganizações gerenciam o seu capital intelectual. Rio de Janeiro: Campues, 1998.

Edvinsson L, Malone MS. El capital intelectual: Cómo identificar y calcular el valor de los recursos intangibles de su empresa. Barcelona: Ediciones Gestión 2000, 1999.

Sveiby KE. The new organisational wealth: managing and measuring knowledge based assets. San Francisco: Berrett-Koehler Publishers Inc., 1997.

Centro Valenciano para la Sociedad de la Información. La gestión del conocimiento en la sociedad de la información [en línea]. Disponible en: http://genesis.ovsi.com/icons/cevalsi/cevalsi.swf[Consultado: 10 de julio del 2005].

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Bueno Campos E. El capital intangible como clave estratégica en la competencia actual. Boletín de Estudios Económicos 1998;LIII(164):207-29.

Modelo de gestión del conocimiento de KPGM Consulting [en línea]. 1998. Disponible en: http://www. gestiondelconocimiento.com/modelos_kpmg [Consultado: 25 de junio del 2005].

Sabater Sánchez R, Meroño Cerdán AL. Creación de valor empresarial a través del capital intelectual y la gestión del conocimiento [en línea]. Disponible en: http://www.um.es/eempresa/inves/GC-CI.pdf[Consultado: 1 de julio del 2005].

Pérez Rodríguez Z. Un enfoque sobre la gestión del conocimiento desde la perspectiva de la calidad [en línea]. Disponible en: http://www.gestiopolis.com/canales/gerencial/articulos/70/gesconperscal.htm[Consultado: 5 de agosto del 2005].

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Viedna Marti JM. IICBS Innovation Intellectual Capabilities Benchmarking System [en línea]. Disponible en: http://www.intellectualcapitalmanagementsystems.com/publicaciones/IICBS.pdf[Consultado: 28 de julio del 2005].

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Viedna Marti JM. CICBS: Cities Intellectual Capital Benchmarking System. Una metodología y una herramienta para medir y gestionar el capital intelectual de las ciudades. Aplicación práctica de la metodología en la ciudad de Mataró [en línea]. Disponible en: http://www.intellectualcapitalmanagementsystems.com/ publicaciones/CICBStrad.pdf [Consultado: 5 de agosto del 2005].

 

Translation of Design of a Knowledge Management Model for Improving the Development of Computer Projects’ Teams

Design of a Knowledge Management Model for Improving the Development of Computer Projects’ Teams

by Naryana Linares Pons, Yadenis Piñero Pérez, Elizabeth Rodríguez Stiven, Liset Pérez Quintero
University of Computer Science, Cuba.

How to cite this article / Citation: Linares Pons, N .; Piñero Pérez, Y .; Rodríguez Stiven, E .; Pérez Quintero, L. (2014). Design of a Knowledge Management model to improve the development of computer project teams. Spanish Journal of Scientific Documentation, 37 (2): e044. doi: http://dx.doi.org/10.3989/redc.2014.2.1036

Abstract: There is a real need for elevating knowledge management activities and integrating them into the management of development projects in order to improve IT project teams. It is also necessary to retain the knowledge of professionals, to capture and share best practices, and to provide organizational training and learning. The present work aims to present a Knowledge Management Model for improving IT project teams, as expressed mainly through the teams’ scientific results. A survey was conducted on trends presented by leading authors and institutions in project management and on experience in the use of knowledge management, in order to achieve a proposal whose results are supported by current theoretical results.

Keywords: Development of project teams; knowledge management; project management; scientific results; scientific production.

 

  1. INTRODUCTION

With the arrival of the 21st century, humanity faces the growing establishment of the knowledge society. The permanent development of Information Technology and Communications (ICT) has brought about the emergence of new business cultures. This era is characterized by great technological, organizational transformations, by permanently linked networks and requires high professional preparation, continuous training, the development of new ways of linking universities, research institutions and the business environment. It is accepted, both in academic forums and among those responsible for regional economic development, that research and development (R&D), innovation and technology transfer are essential elements in the competitiveness of countries and regions (Andersen and Ponte, 1999; Adell, 2000).

Strategies to enhance talent are a characteristic of the knowledge society. People are the ones who give competitive advantages to companies today. Hence, the emergence of several managerial paradigms centered on the human factor is observed. The distinctive element today has become the talent that is capable of managing the company, the ability to innovate and to get ahead of the market. That is why, from various points of view, talent management must be adopted as an organizational philosophy and not as a management model. In this work a knowledge management model (GC) “ISECO” will be presented to improve the development of computer project teams measured from the management of competencies, communications and the scientific results of said project teams. In Section 2 the content will be presented taking into account the materials and methods that have been used in the research, the analysis of development of project teams according to scientific production, as well as concepts and models of GC most referenced in the reviewed bibliography. The results are shown in Section 3 of the paper based on the presentation and explanation of the Knowledge Management model proposed. Finally, the conclusions, recommendations and the consulted bibliography are listed.

 

  1. BACKGROUND

2.1. Methods and materials

 

In this section, the state of the art is reviewed, taking into account several types of scientific analysis techniques:

The logical historical method was used for the critical study of previous works. We also review the evolution of the investigated phenomenon and its behavior in temporary sequences. On the other hand the hypothetical-deductive allows investigation from the general to the particular, as well as the definition of specific criteria and concepts of the investigated phenomenon. The analytical-synthetic method was used to break down the research problem into separate elements and deepen the study of each of them, and to then synthesize them in the solution of the proposal. The measurement made it possible to make estimates and quantitative comparisons of the magnitude of a result or the consideration of prevailing and relevant characteristics of the phenomenon being studied. In addition, surveys and interviews were used. The surveys aimed to obtain the proper dimensions of the phenomenon studied. The interview were designed to obtain an assessment of the state of the management processes for the development of project teams.

 

2.2. The development of computer project teams and their impact on scientific production

The scientific article, as defined by UNESCO, is one of the methods inherent in the work of science, whose essential purpose is to communicate the results of research, ideas and debates in a clear, concise and reliable manner. UNESCO has also ruled that it is necessary to establish well-developed publication strategies to facilitate the exchange between scientists from all countries and reduce the increase in the volume of publications to reasonable proportions (Cué et al., 2008).

 

In studies carried out by Artiles, (1995) and Nuñez, (2003), the scientific article is defined as “a written and published report describing original research results. According to Vázquez, (2010), it is considered that the scientific production of a team is an indicator that allows to measure the scientific maturity and the development that it has been acquiring. For this reason, the stimulation of organizational learning, communication, socialization and research capacity that promotes work on projects and direct their performance towards the development of all team members must be constant.

Scientific research is an activity aimed at obtaining new knowledge and occasionally resolving problems or questions of a scientific nature. The work also assumes that scientific research is one of the spaces that professionals have to do science based on their development of topics of interest. It is the way to contribute with theoretical and practical contributions to the improvement of their activity in the work environment, to the increase of intellectual production, to the timely resolution of social problems or to the sum of all these.

 

2.3. Knowledge management in the development of computer project teams

Managing knowledge has become a scientific necessity. To the extent that the members of an organization understand the processes, they feel part of the solutions, cultivate their experiences and reframe to optimize results while documenting what they have learned and socializing it to the rest, the team as a whole will be more developed and talented (Well, 2000). Knowledge management is an alternative that, with synergistic integration to the management of appropriate skills, improves the development of project teams.

Reflections by Ponjuán, (1999) and Estrada, (2010), ensure that the knowledge management integrates in a single process the areas of creativity and innovation, knowledge, best practices, the development of learning and skills, research – investigation and development, intellectual knowledge, capital accounting with radically new communication technologies. Similarly, it is added that knowledge management has among its main objectives: to contribute to the understanding of how to achieve more competitive and adaptable organizations, as well as to create processes and management mechanisms that accelerate learning, creation, adaptation and dissemination of knowledge, both in the organization as between the organization and its environment.

In studies carried out by Nieves, (2001), it has been indicated that knowledge is information analyzed and organized. According to Simeón (2002), “knowledge management has been identified as a new management approach that recognizes and uses the most important value of organizations: the knowledge that humans possess and contribute to the organization. One of the main values ​​of knowledge management is its complete coherence with other techniques such as quality management, reengineering and strategic planning that are also based on knowledge” (Pavez, 2000); (León et al., 2006). In full concurrence with them – Serradell and Juan, (2003) and Nieves and others, (2009) state that the identification of knowledge is closely related to the acquisition, development, sharing, use, creation and retention of knowledge – other processes of knowledge management. The aforementioned authors agree that knowledge management processes occur cyclically. On the other hand, in the works of Adell, (2000) and Vásquez, (2010) it is added that the transformation of information into knowledge is a process of human intelligence that plays a fundamental role in the generation of added value. Knowledge is an ideological construction based on understanding and reason.

 

In the definitions, the authors agree that for there to be knowledge, there must be a transformation of the information. The authors of the research agree that from the management of any center or project the knowledge management must align with processes such as strategic planning, project management, human resources among others whose objective is to improve. The concepts reviewed lead to the assumption that the group of processes that allow the accumulation of experiences and capital is tangible. It is also understood that these processes must be aimed at facilitating the management of communications in the entities. These processes must provide methods, techniques and tools to develop specific actions focused on ensuring that an entity does not duplicate efforts, achieving a climate of improvement, exchange and continuous communication.

 

In addition, a cyclical character is perceived in all the descriptions that are addressed, which leads to the perfect coincidence between what is documented or recorded in computer systems with the processing and assimilation of that information. Knowledge management must contribute to the organizations to gain time, cost and quality in the commitments that they must face. The competences that the teams must develop will be taken into account as part of  knowledge management concept that is assumed. Based on the arguments addressed by the different authors and the bibliography studied until now; the assessment made about knowledge management as a proposal to improve the development of computer project equipment is considered valid.

 

2.4. Review of a selection of the main Knowledge Management models

For the explanation of each selected model, the operability of the elements raised by their authors was taken into account. In each case, a critical position is assumed from which the contribution of each model is highlighted and in the same measure it is indicated what does not contribute to the objectives of the study in question.

The Nonaka Takeuchi model establishes tacit (subjective) knowledge as the primary focus, although it also addresses the explicit (objective). It proposes four forms of knowledge conversion, one in which, from the interaction of groups of people (socialization), knowledge moves from tacit to tacit. Externalization is when knowledge is transformed from tacit to explicit. By combining or distributing knowledge, it is generated from explicit to explicit. After the internalization or association of learning through practice and the reception of experiences, the knowledge is transformed from explicit to tacit again (Nonaka and Takeuchi 1999). Nonaka and Takeuchi (1995) modeled the process of generating, accumulating and integrating knowledge of companies as a circular, cumulative cause and effect process of continuous interaction. The interactions between these kinds of knowledge lead to represent such a model through a spiral architecture, known as the “spiral of knowledge” as shown in Figure 1.

The main contribution offered by the Nonaka and Takeuchi model is the definition of the four modes of knowledge transformation for the organization. Its greatest application is in how organizations can create and promote knowledge. The greatest limitation is its failure to describe the activities involved in the transformation of said knowledge. From this model knowledge is obtained via processes from the appropriate form of knowledge management that one wishes to implement, leading to the internalization, combination, externalization and socialization of knowledge. It is a generic model that does not detail the activities that make up each process, nor does it reference the inputs, outputs, techniques and tools that should be used to support it. However, processes are used (socialization, externalization, internalization and combination of knowledge).

The Wiig or Kim model, as it is also known, is an integral model that encompasses the process of creating, coding and applying knowledge to solve problems using existing practical experiences (Wiig, 1994). It describes the content, location, process of collection, distribution and use of knowledge. Define three forms of knowledge: public, expert-shared and personal. Wiig describes the effective, conceptual, exceptional and methodological knowledge as the basis for the development of its model.

Among the contributions of the Wiig model that are considered in this proposal is: to reinforce the use of knowledge, describe its content, location, distribution and use from the implementation of a website where much of the volume of knowledge generated in projects can be intentionally managed. In addition, this model collects, formalizes and codifies knowledge. The most important thing about Wiig is the creation of an organizational structure for the project, which can be understood from the assignment of specific roles.

The fundamental disadvantage it has is that it does not distinguish between cognitive and real knowledge. It also does not detail the tools or techniques that should be used in the implementation of the processes. It does not delve into any specific area. The most valuable aspect of this conception of knowledge management is that it aims to identify knowledge needs in order to reinforce them.

For its part, Andersen’s model (Andersen and Ponte, 1999) aims to create an organizational infrastructure in order to gain wisdom by favoring invention and learning from an individual perspective. It has the responsibility of sharing and creating processes and systems that allow the capture, analysis and distribution of these skills. In essence, it proposes that two types of tools be implemented. On the one hand is packaged knowledge, which includes the generalization of good practices, the use of indicated methodologies and tools and the creation of a library of proposals and reports. On the other hand, are the exchange networks, which include the creation of communities of practice (virtual forum) and the shared learning environment.

In balance with Wiig, the main disadvantage is that it does not distinguish between cognitive and real knowledge. However, it is considered useful and will take into account the characteristic that it proposes to develop in terms of promoting learning and implementing the creation of systems capable of capturing knowledge and experiences that must be explicit for the organization so that no mistakes are repeated Do not duplicate processes. Andersen will apply the need to raise different invention factors in the individuals who are in the projects with little relationship between the number of innovations they produce and the scientific results. To this end, the establishment of a network of experts is more than an institutional goal, it is a healthy practice that works with the experience of those who obtain the best results and the best research results.

The KPMG Consulting model (Tejedor and Aguirre, 1998) has a relationship approach between organizational structure, culture, leadership, learning mechanisms, people’s attitudes and the ability to work in teams. Its objective is to focus on the aspects that define learning and the short and long term results they offer for the organization. It has among its missions the work with factors such as organizational structure, culture, leadership, learning mechanisms, attitudes, knowledge, and the ability to work in a team. They emphasize the need for orderly interaction of these factors. The main contribution of the KPMG Consulting model, which will be referenced in the proposed solution, is the coherence that the model shows the system of competencies defined in the university. In this way, culture, leadership, learning mechanisms, attitudes and capacity for teamwork are identified as the first skills and / or competencies that have beneficial points of contact.

The analysis of knowledge management models in general has made it possible to assimilate and establish the conversion of tacit knowledge into explicit. All models agree that, based on the data, a climate of information is generated that demands proper management. The relationship between the knowledge management models analyzed with the different bodies of knowledge regarding project management is unquestionable. From these it will always be useful to manage communications and enhance individual and collective development based on knowledge and experience managed by fields. Thus, the proposal obtained as a result must contain as primary processes those defined in the Nonaka Takeuchi model (internalization, combination, externalization and socialization). It is understood to use the Wiig model the description, location, distribution and use of the data that exist in the project and that improve the GC. According to Andersen, the techniques and tools that adapt to the characteristics of the environment must be established. Finally, it is expected that the proposal will contribute to improving the low GC that is carried out in the projects. It is also expected that with the application of the model, the development of project teams can be improved.

  1. RESULTS

3.1. ISECO Knowledge Management Model

The knowledge management model presented below is explained through the relationship established between its nodes. There is a central core, formed for five processes that run cyclically. Coinciding with the literature analyzed, the processes were determined as model processes: internalization, socialization, externalization and combination of knowledge, but being necessary to verify the status of the processes, monitoring and control is also incorporated as another of its processes (Figure 2).

In the node that defines the techniques and tools that are explained in section 3.1.6, a collection of data for case-based reasoning, a website for the capture of experiences and the socialization of information are proposed, among others.

The projects

The definition of a network of experts by thematic areas of research linked to the development of scientific seminars and workshops whose main mission is to put collective intelligence in function of individual scientific production. At the core of activities are the selection, capture, generation, filtering, dissemination, presentation, and combination of information and knowledge. The following describes each of the processes that make up the model based on inputs, activities and outputs that are generated, highlighting in each case the techniques and tools that support the activities and generic competences most linked to the process in question.

During the description that follows of the model processes, we work with inputs, activities and outputs that are important  to be managed are defined in certain. The following are the positions assumed in the investigation with respect to each of them:

Data

Understood as the smallest units of information. Data, for example, includes the date of publication of a scientific article, software requirements, and the duration of the project. They are important elements that help develop the knowledge that a person has about certain aspects of information.

Explicit information

It is assumed as the data set with a relationship of close coherence that is capable of transmitting a message. Information for the proposed model is considered: requirements specification artifact, use case specification, art states; the definition of models, methodologies, procedures, strategies, processes to which established scientific methods and techniques are applied.

Explicit knowledge

It is the one that is reflected or documented and in which tools, methods or techniques have been applied to generate it. For example, the specifications of business and system use cases, the different estimation metrics that are implemented in the project, among others. Explicit knowledge gives the possibility to review and learn from what exists, and then consider new lines of research.

Tacit knowledge

The tacit knowledge that is obtained as an output is understood as the assimilation of all the data, information and explicit knowledge that exists at the entrance of the process. To the extent that the person processes the volume of tickets and adds their experiences and knowledge, they will be able to generate new tacit assets.

Experiences

They are the result of the maturity of knowledge, the assimilation and understanding of different branches or the combination of several of them. As an effect, they have an incalculable value because they possess know-how and maturity of knowledge. The experiences constitute an important entrance to every process because they form a product of the intellectual development of each member of the project team.

Information

It is the set of data under a relationship of close coherence and capable of transmitting a message. The information is considered to have high value, as it constitutes one of the starting points of the exchange that is generated between the participants of the project team. It is an entry that demands the ability to work in teams to obtain the desired results in the process.

 

3.1.1. Internalization Process of Knowledge in Computer Project Teams

It is understood as the conversion of explicit knowledge to tacit. It is the process by which the person is able to capture much of the volume of information and data that surrounds them to process them and add value according to their experience, thus converting the data and information into new knowledge. In the teams to the extent that progress is made to more efficient solutions, the results are investigated and documented. All this generates information that when processed and incorporated by each of its members becomes knowledge. Figure 3 shows the activity diagram of the analyzed process.

It is of high importance especially in the activity of scientific research, because the accumulated experience and the need to study to the frontier of converged knowledge. It is proposed to use seminars, workshops, conceptual maps as techniques and tools that support the process. As entries you have the information and explicit knowledge that exists about what is being investigated. The main activities consist of capturing, processing and generating tacit knowledge. As outputs, tacit knowledge must be obtained (Figure 4).

The main competencies are the research capacity developed by each team member. The ability to communicate in a second language that allows access to information in other languages, as well as the ability to search, process and analyze information from different sources together with the capacity for analysis and synthesis.

 

3.1.2. Socialization process of Knowledge in Computer Project Teams

Understood as the moment in which explicit knowledge (good practice) or tacit knowledge (knowledge) is shared. This is when the members of the organization learn and acquire new knowledge. It is proposed to carry out this process fundamentally through training plans, discussion workshops on certain topics and other group activities in which the members of the project share their experiences with the objective of complementing the knowledge they possess. In this sense the possession of a website in the organization, in addition to sealing the difference, helps to socialize the information and knowledge that is generated during the software development process. Figure 5 shows the activity diagram of the process being studied.

In order to achieve success in this process, there are competencies that the members of the project team must have. For example, the ability to communicate orally and in writing makes it possible to clearly and coherently transmit experiences on a given topic. The creative capacity gives relevance to tacit knowledge based on the innovative results that are exposed. Figure 6 shows the process architecture from its entrances, activities and exits.

 

The competence of teamwork allows collaborating to achieve organizational goals and facilitates the learning of those involved in the milestones that the organization must achieve. The research capacity offers the culture and arguments that will be defended in the workshops or trainings planned as part of the process. With the social responsibility and the principle of professional ethics, the commitment to be authentic is assumed while at the same time having the capacity to reference relevant contributions offered by other authors.

3.1.3. Externalization Process of Knowledge in Computer Project Teams

Externalization consists in converting tacit knowledge to explicit through the use of techniques and tools that facilitate its understanding. Knowledge can be externalized from the exchange or debate that is generated with the realization of techniques such as workshops, preparation of guides for self-learning and training manuals. The use of concept maps is suggested as a tool. This process enables the exchange of productive experiences in the project team. As a result of the process, new knowledge and experiences are generated that, being documented, can be used to consult the team at any time. Figure 7 shows the flow of activities of the process being analyzed.

Among the competences that most affect this process is the capacity for oral and written communication that makes it easier for team members to transmit and share their best experiences. The critical and self-critical capacity makes it possible, following a scientific position, to establish significant arguments for the foundation of one’s own projection or that of another and to adopt a position according to the debates that are promoted and the techniques that are applied. Figure 8 shows the architecture of the process according to main entrances, activities and exits with social responsibility, the team member assumes a full commitment to transmit their best experiences taking care of professional ethics when referring to issues addressed by other authors. To the extent that there is capacity for abstraction, analysis and synthesis, only the information that is really useful and of interest to the team members can be externalized. At the same time that commitment is assumed with the quality of what is externalized, greater efficiency will be achieved in the process analyzed.

3.1.4. Combination Process of Knowledge in Computer Project Teams

The combination process is that the members of the project team generate explicit knowledge by gathering experiences from their research and scientific contributions or from other sources such as publications and interviews with experts. This process is often confused with that of socialization, however its difference is that it refers to the generation of knowledge from the fusion of good practices or experiences, while socialization only seeks to share existing knowledge. At this time, knowledge is combined through work meetings, round tables, meetings of research groups, exchanges with experts and interviews. It offers as a result an easy to understand knowledge to use in the generation of new experiences. Among the techniques that are recommended to apply are the realization of workshops and the exchange with networks of experts. Figure 9 shows the flow of activities of the process of knowledge combination.

As competences more linked to this process, teamwork allows the exchange to reach proposed goals and facilitate the organization’s learning. The ability to communicate orally helps team members so that the rest understand exactly what needs to be transmitted. If communication in a second language is not taken into account as an important element, proposals are no longer valued, thereby limiting the possibility of reaching the frontier of knowledge. Figure 10 shows the process architecture according to its main entrances, activities and exits.

Research capacity is another essential competence to combine good practices and experiences. From the ease of learning that the team shows, more flexible solutions can be obtained that contribute to the desired results. Similarly, the commitment to quality aims to ensure that the members of the work team assume seriousness with the results they present.

3.1.5. Monitoring and Control Process

The monitoring and control process is defined with the intention of being able to review the state of application of the proposed model. The competencies closest to this process are the ability to work in a team, the commitment to quality, as well as the responsibility and the principle of the ethics of the profession. It is considered that following and controlling partial results from the beginning of the project, can advance the project the effects of implementing certain processes of the proposed model. The flow of activities defined for the Monitoring and Control Process is shown in Figure 11.

3.1.6. Techniques and Tools to support the solution

The following are among the techniques and tools that are proposed to support the proposed solution:

Proposal of a data collection for case-based reasoning

Data collections allow for studies of high importance. It is agreed that from a data collection, decision making can be guided. This research proposes the use of the WEKA tool, used for data experimentation by applying, analyzing and evaluating the most relevant techniques in data studies. Its use in this case is recommended as it is estimated that it can help with studies on the most developed project teams.

 

Design of a network of experts by areas of knowledge

Expert networks make it possible to identify the people who have the greatest know-how in activities such as writing scientific articles and publications. To organize the network of experts, take into account: the scientific degree; number of publications as first or second author in provincial, national and international events or magazines; number of times it has been cited in articles or works of his contemporaries. The network is then implemented as part of the website facilitating online interactions.

 

Website Design

As part of the research, we worked on the design of a website that is aimed at the selection-capture, filtering, presentation-dissemination and use-generation of information. In the development of the site, interactive systems have been used to define surveys and forms to make them accessible through a Web browser. In addition, the site must support the implementation of a network of experts that support the scientific activity of the center where the solution is implemented.

 

Workshop System for Knowledge Capture and Socialization

The workshops constitute the space that the members of the project have to exchange the experiences obtained in their research lines. They are proposed as a technique because they greatly support the processes of externalization, socialization and combination of knowledge.

For the diagnosis of knowledge management in computer projects there is a system of indicators

that apply the ISECO model.

 

The system of indicators to diagnose the knowledge management in projects allows managers to review which are the indicators that they should promote to achieve better results in their management. In this way, a weighting is defined for each indicator that, in the author’s opinion, is estimated to influence the success of the project teams. Finally, a qualitative evaluation of the project is obtained in relation to the GC processes that it has implemented. This system is defined in an additional file to the job.

 

3.1.7. Analysis of the Application of the Model in a Case Study

To apply the proposed model, 15 software projects from one of the largest development centers that the university has are chosen as a population. Experiments are framed in the “development of computer project equipment” processes and their behavior is observed in the selected project teams. For a better analysis of the variable “development of computer project teams”, it is proposed to break it down into indicators as shown below and carry out the relevant studies taking into account in each case the results before and after applying the object model of the proposal.

 

Analysis of the Generic Competence Indicator

At first, the competencies were measured only of the professionals who are the greatest contributors to the productive activity. The competencies that most impact on the development of computer project teams were selected in response to scientific results and quality in communications. To diagnose the status of the selected competencies, the 360 method was used, with which a qualitative result was achieved in the criteria of High, Medium and Low granted by the team leader, project manager and three teammates. Each team member. The results were processed using a descriptive statistical technique, with which significant variations were obtained.

Secondly, six competencies selected for their level of impact on scientific results were evaluated. The results by competency are described below (figure 12)

  • Ability to work in a team: Its satisfactory evaluation and variation is due to the development of workshops and seminars proposed by the ISECO GC model.
  • Research capacity: Its satisfactory evaluation and variation is due to the increase in scientific results, participation in events and the incorporation into programs of scientific improvement.
  • Skills to process and search for information from different sources: Its satisfactory variation is due to the increase in the publications made by the team members that is improved with the network of experts proposed by the GC ISECO model.
  • Oral and written communication skills: Its satisfactory variation is mainly due to the development of group work techniques such as workshops and seminars. In addition to the increase in scientific activity as publications.

 

The skills ability to work autonomously and the capacity for abstraction, analysis and synthesis have little change as shown in Fig. 12. This is because these competences are more related to elements that range from personality characteristics to neuropsychological factors that the proposed model does not cover. In general, it is considered that with the application of the model, some of the competencies defined in the university framework are promoted.

 

Analysis of the Communications Management Indicator

 

To analyze the Communications Management indicator, an initial diagnosis was made that made it possible to know the status of activities such as the distribution of information, location and knowledge socialization, among others. It consisted of a survey using an online tool LimeSurvey (2012) that allowed a quick statistical analysis on the data set that was obtained. The sample was selected using the non-probabilistic sampling technique, intentional sampling. It was applied to 18 developers, 14 analysts, 5 project managers, 16 designers, and 10 architects for a total of 63 respondents.

Once the diagnosis has been applied (figure 13), the results of the Communications Management indicator are shown. 76.79% of the sample reported “not knowing any mechanism implemented in their project that would contribute to the development of the project team”. 62.50% consider that “the information in their project is not organized and available to team members”. Similarly, 67.07% voted because “the publication of the information was through a website created for the project and information meetings respectively”. On the other hand, 87.50% of the respondents considered that establishing processes to manage the knowledge generated in their project is a practice that contributes a lot. Likewise 87.50% indicated that the implementation of a network of experts to improve the development of the equipment is a technique that contributes a lot.

Figure 14 shows a graph that explains the importance and relevance that some elements of communications management acquire for the members of the sample studied at the first and second moments.

From the previous graph, a discrete increase in the level of importance that professionals attach to some elements that are proposed to improve the development of project teams, in terms of quality in communications management, is obtained at this second moment. The understanding of the main artifacts by project management area has had a medium level of importance but little relevance for those involved in the project. Among other reasons, it may be due to the volume of artifacts that have been defined to document for each phase of the project and constantly undergo updates.

 

Theoretical Validation of the Model

To theoretically validate the ISECO model, it is proposed to use the expert method in its Delphi variant, with the aim of developing long-term forecasts, taking into account the systematic use of intuitive assessments by a group of experts to obtain a consensus of opinions that, in perfect agreement between the parties, reinforce the validity of the proposal.

 

Twenty experts with experience in software production and GC, respectively, participated in the validation of the GC model. Of them 15 doctors and five masters. All were selected because they had a high and medium proficiency coefficient.

 

To carry out the evaluation of the model, the indicators or attributes (A) that will be evaluated by the experts are defined. From these, a questionnaire with questions (P) is prepared so that the experts express their assessment in relation to the model. The defined attributes were:

 

A1: Scientific Value.

P1-Need to implement a GC model that allows to improve the development of computer project teams.

A: Reliability. two

P2, P5, P7-Consistency of the structure of the GC model.

A3: Clarity.

P3, P4, P6- Linking the model with computer project management processes.

A4: Generality of the proposed model.

P8- Independence of the model in productive environments.

The final result of the evaluation of the model by the experts, where the aspects under consideration were evaluated as “Very Acceptable MA” and “Acceptable A”, demonstrating the degree of acceptance of the proposal and being equally viable from the theoretical point of view.

After applying the initial diagnosis, a set of actions are generated for the implementation of the GC-ISECO model. Then the second measurement is made with the objective of being able to check the results of applying said model. For this, the behavior of the communication management of the project is observed after applying the GC model and attending to the identification, understanding and appropriation observed during the first diagnosis. As an instrument, the survey carried out initially was used using the Lime Survey tool that allows statistical analysis and comparisons between the first and the second measurement. 

  1. CONCLUSIONS AND RECOMMENDATIONS

The following is concluded from the development of the solution and its implementation:

About the proposed model:

  • The ISE-CO Knowledge Management model has the principle of improving the development of computer project equipment expressed from the competence management and communications management of said equipment.
  • The description of the model is based on processes, activities, artifacts, techniques and tools. 

About the results obtained:

The proposed model achieved discrete improvements in the development of computer project teams expressed from the skills management and communication management achieved by team members.

On innovation and novelty of work:

  • The novelty of the research is summarized in the proposal of a Knowledge Management Model to improve the development of computer project teams based on indicators such as: scientific results, communications management and generic competencies of the members of the project team
  • The proposal defined in this research has a considerable practical contribution that is explained with the elements described below:
  • System of indicators to diagnose knowledge management in computer project teams. (Additional file to work)
  • Metrics to evaluate the knowledge management in processes of the Communications Management Area in computer projects. (Additional file to work)
  • Guides for the implementation of the model in the area of ​​Communications Management in software projects. (Additional file to work)

It is recommended for future work:

  • Direct the activities of the model with greater emphasis on increasing the scientific results of the project team.
  • Design a knowledge management -based integrative strategy to improve other project management indicators.

 

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English Translation of Design and Implementation of Knowledge Management Projects

Design and Implementation of Knowledge Management Projects

by Montserrat Garcia Alsina
Professor in the Studies of Information and Communication Sciences Member of the research group KIMO (Knowledge and Information Management in Organizations)
Universitat Oberta de Catalunya

Knowledge management is an organizational practice that has been increased in the last 30 years, although the recognition of its intangible value goes back many more years (Penrose, 1959 cited in Spender, 1996). Since the 1990s there has been an increase in literature on the subject, and as of the current century, researchers have more specifically worked on norms, rules and methodologies that contribute to the progress of knowledge management as a discipline (Serenko et al. , 2010).

On the other hand, management systems in organizations are implemented and certified in a good part of organizations, with a focus on continuous improvement and excellence. Examples are the Quality Management System (ISO 9001, or the EFQM model of the European Foundation for Quality Management), or the Environmental Management System (ISO 14001), or the Information Security System (ISO 27001) , the R + D + I management system (UNE 166000) or the document management system (ISO 30300).

All these systems involve the study of organizational processes, within the framework of which the activities are carried out – both those common to any organization, as well as those specific to business activities. In these processes documents, information and knowledge are generated. The documents, beyond fulfilling their function of being evidence of compliance with the system requirements, gather knowledge about the organizational processes. Thus, considering that knowledge is the main raw material of the knowledge economy (Lisbon Council, 2000), and a basis for innovation (Garcia and Cobarsí, 2013; Serrat, 2010; OECD, 2005; Etzkowitz and Leydesdorff, 2000 ), knowledge management, and the integration of management systems in knowledge management processes, would contribute to extracting value and generating competitive advantages (du Plessis, 2007; Diakoulakis et al., 2005; CEN 2004). Taking these reflections into account, it is of interest to include in them some methodological considerations on the design and implementation of knowledge management projects in organizations.

This article collects, first, the rules related to knowledge management. Second, it exposes the components of a knowledge management project and some of the frameworks developed. Finally, this article describes the phases and guidelines recognized as keys for an effective implementation of actions aimed at managing knowledge, highlighting the framework developed by the European Committee for Standardization (CEN) in 2004, as an example of systematics to be applied in the knowledge management

RULES RELATED TO KNOWLEDGE MANAGEMENT

In the last decade, various national and international organizations have made efforts to systematize the design and implementation of knowledge management projects. An example is the wide range of standards developed by standardization bodies such as those of the British, German, Austrian, European, as well as the International Standards Organization worldwide (Table I – not included). Even some of these models are aimed at more specific sectors such as public administration, health, or construction, or small and medium-sized companies. It is also worth noting the interest to take into account: aspects that can influence – as facilitators or innovators – in knowledge management practices, the competences that knowledge management professionals must gather, and the measurement of the actions carried out.

COMPONENTS OF KNOWLEDGE MANAGEMENT AND METHODOLOGICAL FRAMEWORKS

A knowledge management project must take into account four components: people, processes, content and technology (Table II).

Taking these components into consideration, there are many frameworks designed to manage knowledge in organizations. Some partially incorporate the aforementioned facets, while others encompass them more holistically (Table III – not included).

Holistic frameworks are recommended to design and implement knowledge management projects in organizations, since they facilitate eliminating ambiguities, and achieve more creation and better exploitation of knowledge for strategic planning and development. decision making (Diakoulakis et al. 2004). Among the holistic frameworks, two stand out: that of Diakoulakis et al. (2004) and the aforementioned CEN (2004). The first, based on the knowledge management framework proposed by Rubenstein-Montano et al. (2001), offers a framework that covers different aspects: the organizational ones, those of their environment, and those of knowledge. The central elements of the framework are measurement, processes, objectives and environmental factors, connected by a cause-effect relationship platform. The second framework (CEN 2004) is the result of reflection work carried out by different institutions and companies belonging to various European countries. This framework integrates the business processes with the core activities of knowledge (identify, create, store and use), which includes the facilitating elements of management constituted by people and the knowledge capabilities of the organization in order to Integrate the actions. The CEN (2004) also contemplates the management measurement and the fulfillment of the objectives indicated in the actions.

KEY PHASES IN THE DESIGN AND IMPLEMENTATION OF KNOWLEDGE MANAGEMENT PROJECTS
Broadly speaking, managing knowledge in organizations requires a set of specific processes and procedures in which the knowledge management phases are contemplated: identifying, creating, storing, sharing and using knowledge, taking into account account of the administrative and business processes of any organization (CEN, 2004). For this, we have a series of instruments that we can include in three groups, corresponding to the three stages in which a knowledge management project must be addressed:

1) knowledge audit
2) knowledge map organizational
3) creation of spaces and tools that support the knowledge management phases mentioned above (Raghu and Vinze, 2007; CEN 2004)

The knowledge audit serves as a starting point to design a knowledge management project, since it makes it easy to identify and collect: a) the information and knowledge resources existing in the organization and those required, for the performance of their duties; b) in which organizational processes knowledge is generated or what knowledge is required, and c) what structures are in the organization through which knowledge can be stored, distributed and managed (Levantakis et al., 2008 ; Garcia ‐ Alsina, 2004; Liebowitz et a. 2000). It is done through surveys and interviews with experts who participate in different organizational processes To this end, it is recommended to start from an interview script or form, in case the audit is carried out through questionnaires (García-Alsina, 2004). It is recommended to start with a pilot program that addresses a key area of the organization, in order to see the results clearly.

Once the audit has been carried out, a map of the knowledge of the organization, representing the intellectual capital of the organization (Figure 2) (Watthanan and Mingkhwan, 2012; Driessen et al., 2007; Huijsen et al. ., 2004, Kim et al, Wexler, 2001), both human, structural and relational (Table IV).

The type of content that the maps should collect depends on where they are oriented, although it is recommended that you collect the activities and knowledge necessary to carry them out, as well as your current location (inside or outside the
organization), how it is used and shared and how is that knowledge (tacit or explicit). In addition, there are different means to represent this knowledge, as well as various software to create maps and facilitate their visualization (Driessen et al., 2007; Eppler and Burkhard, 2007; Kim et al., 2003). In order to keep the map updated, it is advisable to establish periodic procedures for knowledge audits in the organization.

Finally, in the light of the knowledge map, the organization must analyze how the different phases of the knowledge cycle are developed, how are the existing information flows, what information needs are detected to reach the factors Critics of the organization’s success, consistent with its mission and vision, and the strategic objectives of the organization. In short, what are the strengths and lacks of strategic knowledge required in key processes of the organization. Aspects to consider in each phase are:

In the first phase, the knowledge needs that each member of the organization has to carry out the activities assigned in their responsibilities must be identified. It is important for this phase that each member knows the processes in which he participates and with which he relates in a transversal way in order to identify the flows of knowledge. It is also relevant to know where the necessary knowledge is located.

In the phase of creating knowledge, employees must start from the knowledge previously identified in the organization or outside it, and that which they already possess in their tacit or explicit form. In this phase, in addition to individual intellectual work, collective actions such as joint work sessions play an important role. Therefore, this phase is closely linked to the actions that take place in the knowledge sharing phase. An ideal instrument for creating knowledge, as well as sharing, are the practical communications.

The third phase, storing the knowledge created, is at the service of the other phases, since it has as its objective is to prepare the means so that knowledge can be identified, shared and reused in the future. In this phase it is important to have information systems that facilitate saving and retrieving information in a friendly way and in accordance with the defined information profiles, in order to preserve confidential knowledge. Likewise, in order to store and recover knowledge efficiently in storage systems, the definition of taxonomies is paramount.

In the fourth phase, sharing the knowledge created, the actions designed should facilitate the dissemination of existing knowledge in the organization and the creation of new ones. In order that this dissemination if done informally and exceeds the level of tacit knowledge generation, the creation of socialization spaces, either face-to-face or virtual, is used to be able to explain the shared and generated knowledge. At the time of carrying out the analysis of the maps, the type of knowledge created must be observed, and if there are already spaces to socialize tacit knowledge.

Finally, in the fifth phase, actions must be designed to use knowledge existing in the organization, created in it, or captured from the outside. It is the activity that justifies the effort made in the other phases. Examples of this use are obtaining the necessary knowledge to make decisions, design actions, or outline strategic plans.

In the light of the analysis made, the necessary actions must be designed so that knowledge is managed efficiently in each of the phases of the cycle, paying special attention to those phases where deficiencies have been detected.

Some of these actions for the different phases are (Figure 3):


Identify: maintenance of the knowledge map and process map, and definition of taxonomies to label the knowledge produced unequivocally, regardless of synonyms and polysemy.
Creating knowledge: creation of spaces for social interaction such as internal training courses, learning by doing, joint problem solving, collection of lessons learned, brainstorming, communities of practice (CoP), expert recruitment, Purchase of other companies with concrete know-how, attendance at congresses or fairs, etc.

Store: capture tacit knowledge through forms, reports, lessons learned from projects or communities of practice, yellow pages, forums, documentary or relational databases, compilation of frequent questions, etc.

Share: periodic distribution of newsletters, bulletin board, intranet, reports; established procedures to feed databases created for this purpose (repository, document manager, portals, CRM, ERP, yellow pages …), and transfer of tacit knowledge (workshops, training courses, CoP, job rotation…).
Use: when applying it to decision making, or designing new products or services, or in the development of activities, we apply value to the organization, and in turn we detect new knowledge gaps, that lead us to acquire new knowledge and restart the cycle.

CONCLUSIONS

Knowledge management requires a system that addresses its design and implementation according to the characteristics of each organization. To do this, knowledge managers in organizations, before planning specific actions, must audit organizational knowledge in order to obtain a picture of how knowledge is being managed. This allows to detect strengths, potentialities and deficiencies. To do this, the knowledge maps that capture the situation at all times must be carried out and act as a roadmap that guides the design and implementation of the actions decided to identify, create, store, share and use knowledge efficiently.

Of the existing frameworks, those that incorporate the components of knowledge management (people, processes, content and technology) are revealed as the most efficient for designing and implementing knowledge management projects in organizations.

The integration of documentary techniques such as information auditing, taxonomy design or documentary languages such as thesauri, information architecture that facilitates information retrieval, design of document management systems, data management contents, maintenance of information resources and training in information skills are knowledge and skills that professionals who manage knowledge in organizations must have.

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English Translation of Locating Expert Knowledge: Yellow Pages

Locating Expert Knowledge: Yellow Pages
by Noel Angulo Marcial
Mexico National Polytechnic Institute
Educational Innovation Magazine
September 2007

Summary

The concepts of expert and yellow pages are described in the context of knowledge management and their relevance in the framework of shared knowledge and access to tacit knowledge within intelligent organizations is highlighted.

Keywords

Yellow Pages; Directory of experts; Shared knowledge; Tacit knowledge; Experts; Expert knowledge; Communities of experts; Knowledge management; Smart organizations

Introduction

At the beginning of this new century, some organizations have realized that their physical infrastructure and financial resources are no longer sufficient to generate sustainable advantages over time and focus their attention on intangible assets as potential sources of value. However, other organizations have become aware of the potential that human talent represents and its forms of expression and transmission as its intellectual production and the modes of interaction that extend its benefits to the entire organization.

Lorenzo Chiquero (2007) questions why companies do not know the potential of their workers and warns that they may not be aware of what they are losing, the value they stop contributing and adds:

The fear of not knowing what to do with people with high potential, with talent, overwhelms them and slows down any decision to fully know their potential.

Knowledge management makes visible and channels intangible assets that generate value for the organization through the identification, acquisition, structuring and transmission of knowledge, although strictly speaking, what is transmitted is only data and information, which are documented, contextualized and In an enabling environment they contribute to promoting learning and generating knowledge, always with different levels of achievement due to particular experiences and differences in the way of perceiving and processing the data by the different members that make up the organization (cf. Castilla la Mancha 2006 ).

Knowledge management deals with the volume and flow of knowledge in organizations, as a support for their activities and incorporates the form of their organization to give added value and enable their rational exploitation. Its main objective is to convert information into knowledge and knowledge into results, articulating the different sources of information and knowledge, internal and external; thus avoiding unnecessary duplication and underutilization of information, in addition to identifying the structural and relational resources of knowledge and human potential of experts, with the key knowledge that the organization needs, activity that relies on the application of methods and strategies to make that knowledge sharable, while the knowledge of the critical mission of the organization resides primarily in the memory of its experts (Coffey, 2002; Hernández and Martí, 2006; Pernas, 2000; University of Amsterdam, 2007).

Javier Martínez Aldanondo establishes a clear association between knowledge of the organization and the quality of experts as carriers of knowledge:

Knowledge is not an object or a content. We can talk about gigabytes of information, thousands of pages of information, hundreds of websites with information but we cannot speak in the same terms of knowledge. In general, the knowledge is accumulated by the experts and therefore the organizations have it inside, although they do not know how to identify it and even less exploit it.

Despite the widespread belief that access to knowledge sources is sufficient for appropriation, knowledge is not transmitted in the same way as water in communicating vessels, and access to the same data does not necessarily match the levels of Information and knowledge. A component that operates as a catalyst to advance organizational knowledge is the figure of the expert. It is said that an intelligent organization is the one who knows who has the expert competence and where it resides; However, it is necessary to create the conditions to access and share that knowledge internally, at the time and place where it is needed. The expert person, if he has the right environment, can contribute through interaction, knowledge that can be documented, filtered and categorized to put them at the service of the organization (cf. Meta4 2001)

Expert knowledge management implies the incorporation of tools and methods to identify, locate, represent and organize the domains of knowledge available and the profiles of experts to enable any person in the organization with specific information or knowledge needs to interact with the person more qualified to help you solve problems. The introduction of such tools creates the conditions of infrastructure for the exchange of knowledge and enables access to undocumented knowledge, which contributes to increasing human capital.

With the purpose of knowing the experiences of other institutions that have been in charge of identifying the expert knowledge and making it available to its members, different websites were consulted that show the yellow pages as the tool indicated within the operation management scheme of the knowledge, although also, the lack of clarity and understanding of this term and others as an expert and expertise or expert competence is notorious, so it is considered pertinent to address its meaning and application coverage in an integral manner in order to specify some concepts and contribute to the culture of knowledge and information management.

Who are the experts?

Niels Bohr, the famous atomic model creator scientist, proposed the following definition:

An expert is a person who has made all possible mistakes that can be made in a certain field of knowledge (Bohr 2005).

His position, although of a reductionist nature, shows the components of experience and practice in the characterization of expert competence.

However, it is necessary to define the term expert, which is derived from the Latin expertus, which means experienced; referring to the connoisseur of some subject or matter; In addition, it is used as a qualifying adjective of practical, skillful or experienced.

Experience, in turn, is a word derived from the Latin experient refiereaand refers to the fact that someone had felt, known or witnessed something. Closer to the purpose of this article is the meaning of prolonged practice, which refers to a certain person with the knowledge or ability to do something (cf. Royal Spanish Academy).

The words expertise and expertise are frequently used to refer to the condition of gathering expert knowledge; however, these do not appear in the dictionary of the Spanish language. The word expert, derived from the Latin perit pera, which means wisdom, practice, experience and skill in a science or art and from this expert, which some use as a synonym for expert, although sometimes the words expert and expert have the particular connotation, associated with the legal field, expert, which in this context means experienced wise, practical in a science or art or a person who holds this quality in some matter through a title conferred by the state, and that by possessing special theoretical and practical knowledge, they inform the judge under oath about litigious points (Orta, 2003).

For Robert R. Hoffman (1998), an expert is:

The experienced person who stands out or stands out from their peers, considered as such by their peers, due to their reliable performance, which makes evident the possession of skills and effort economy and that operates effectively with infrequent cases. An expert is also someone who has specialized skills and knowledge, derived from extensive experience and practice in an activity or knowledge.

Andrés Pérez Ortega (2006), proposes as a distinctive characteristic of experts, the domain of a discipline and its ability to communicate it in a clear and understandable way. In addition, he warns that this domain is achieved with a combination of experience, education and research and not necessarily as a result of extraordinary creativity but learning with the technique of trial and error, specializing and dealing with the same problems on a recurring basis until they reach shape a repertoire of solutions for 90% of the situations that you might face in your field of competence.

Philip E. Ross (2006), notes that:

Without a demonstrable superiority over others, there can be no true experts and warns that only through considerable and continuous effort is it possible to achieve mastery of a field of knowledge or skill (be it the game of chess, the interpretation of a musical instrument or the practice of a sport). One aspect in which all theorists of expert knowledge agree is the fact that great effort is required to build these structures in the mind.

Several authors propose a decade of training and practice with a certain particular domain before a person can be considered an expert and this position is based on the idea that processes are automated with practice, so that they require less effort and they become faster and autonomous and less accessible at the conscious level. Another theory establishes that deliberate practice constitutes an important factor in the acquisition of conduct and expert competence (cf. Guilar, 2003; p. 207-212)

Chase and Simon (1973), coined a law known as the 10-year rule, which states that, it takes approximately 10 years to acquire mastery in some field or activity, and even prodigy children like Gauss in mathematics, Mozart in music and Bobby Fischer in chess, should have made an equivalent effort.

John R. Hayes (1989), investigated the time needed to reach a perfect level of execution, examining the development of a career in different fields that require creative thinking, among others, music, painting and poetry and found the behavior consistent and demonstrated that even the most talented individuals require many years of preparation before producing the work that accredits them as deserving of great reputation.

On the other hand, practice and experience are necessary but not sufficient components, according to Mario López de Ávila (2006), who states that:

The recognition of the quality of expert is not always deserved and is not always recognized to those who in justice deserve it, therefore, in the absence of quantitative measures or objective criteria to specify what an expert is.

López de Ávila proposes:

[…] consider expert only to those who demonstrate it with their judgments and, most importantly, with the results of their practice on each occasion when their expertise is tested.

How do you recognize an expert?

For María Alejandra Ochoa (2004), an expert is:

Someone capable of solving a type of problem that other people, including their profession or specialty, cannot solve effectively and efficiently.

The author proposes as characteristics of an expert those who have expertise, a dimension linked to their high performance to solve problems of their competence successfully and quickly; to those who have the capacity to manipulate symbols and solve problems of a knowledge domain; that solve complex problems and with a certain degree of difficulty; that have the capacity to reformulate or reuse their knowledge; that reason about themselves and their own processes and their own decisions, that they have the capacity to build their own chain of reasoning and that they perform a particular task; that is, they interpret, diagnose, monitor and predict.

For José Portillo Rodríguez (2005), an expert is:

That individual who has recognized specific skills and knowledge about a certain field of activity of knowledge; that is, that it holds a large share of cultural capital but also of social capital, a condition that allows it to state competent propositions, demonstrate specific skills, or impose socially a point of view recognized as transcendent in relation to individual and singular points of view.

According to Mario López de Ávila Muñoz (2006), a Spanish consultant, the expert is recognized for his ability to:

  1. Provide a non-trivial definition of a problem in their field of knowledge.
  2. Develop a non-trivial solution for that problem that produces a result far superior to that

I would give the solution of a non-expert person.

  1. Perform the above actions efficiently, in a minimum time, with resource savings.

Raquel Guilar Corbi (2003, p.326) suggests that:

A fundamental characteristic of experts is their best memory for aspects that are significant due to the greater knowledge they have in their domain. However, their quality of experts is not based on the quantity but on the quality and relevance of their knowledge, which allows them a direct interpretation of the facts. The expert has a well organized structure of specific knowledge; and it is that qualitative organization that exerts a major influence on the acquisition of cognitive skills and expert competence.

Several authors agree to point to the competition in information as an attribute of the true experts by noting that they are more selective in the information they acquire and are able to obtain it in less structured situations, because they focus on the relevant information and can quantify it and categorize the problems, based on the solution procedures that lie in their long-term memory.

In addition, they have the ability to accumulate new reusable information, with the possibility of obtaining access to it when necessary. To this must be added their ability to search, retrieve or generate information depending on the needs, purpose and context of application. The expert knows how to organize and make intelligent use of information, unlike ordinary people, who, despite having more and more information and tools to access it, is unable to process it and give it added value to convert it into useful knowledge. (Guilar, 2003; Pérez, 2006; Sternberg and Frensch, 1992; University of New England, 2004)

Susan R. Goldman, et al. (2003), establish the following characteristics to identify experts:

A well-developed knowledge in their domain fields, with important implications for what they perceive, represent and remember when they process information, and for the flexibility with which they adapt to different tasks and learning situations in their field. The knowledge of the experts is nourished by rich mental representations and, coherent and consistent mental models about the relationships between events or parts of a phenomenon, have self-monitoring skills that allow them to evaluate and resolve relationships between different sources of information, in addition of a high level of competence in the interpretation of facts and procedures for their transfer and application to other situations.

Communities of Experts 

Although characteristics and distinctive attributes of the expert have been cited, Harold Jarche (2006), questions the permanence of the expert competence, noting that:

Knowledge workers are like actors, who will only be as good as their last performance has been and therefore, they are experts only for a fleeting moment.

The above can be expressed as the difficulty of maintaining the status of expert individually in the face of the increasing volume of knowledge available, which is derived from the author’s textual comment:

Perhaps the individual expert competition is gradually being replaced by the collaborative expert competition […]. Collaboration allows individuals with expertise in certain exclusive areas to obtain better results in less time.

Organizations are increasingly complex, while the interdependence of the disciplinary fields as well as the volume of information and knowledge are increasing, so that the figure of the expert working in isolation is no longer sufficient, it is necessary to encourage meetings, dialogue and peer collaboration to maintain expert competence and derive benefits from it.

Virtual communities provide this space of interrelation and knowledge between experts and organizations specialized in various thematic areas and allow fluid and confidential communication between the parties, with the consequent added value (cf. Alonso).

The networks make possible the intercommunication of experts working on the same subject, regardless of time and physical space, to access information, advice or help. Collaborative work among peers is based on the communication and exchange of information and the interaction that supports the collective construction of knowledge. In the virtual space it is possible to access a great diversity of services, which constitute sources of knowledge, not accessible by conventional means such as those indicated (cf. Salinas 1998):

  • Specialized information services of interest to each academic and professional field.
  • Exchange of new knowledge arising from both basic and applied research and the
  • professional practice through digital magazines, electronic conferences and discussion forums.
  • Collaboration to increase the capacity of organizations to solve complex problems. In addition to the exchange of information, the exchange of ideas, experiences and discussion about possible solutions to the difficulties that occur in common spaces or fields considered related.
  • Collaboration to create new knowledge. Different people work together for long periods to achieve shared goals, such as writing a common article, or conducting research and innovation projects by teams of teachers from different centers or institutions.

Yellow Pages 

The usual tendency at the time of structuring the directory of an organization consists, most of the time, in representing its hierarchical structure; which is still in force and allows to locate the personnel and the management cadres with relative ease; However, when it comes to locating and sharing the information and knowledge of an organization, the design of the board of directors must consider a structure that reflects human capital broken down by categories of knowledge and determined by the different areas of expertise and mainly by their experience and expertise (1) and not because of its grouping into addresses, sub-directorates and departments.

Organizations that exploit knowledge rationally and intensively to solve their problems on a daily basis and improve their products and services, will become intelligent organizations, organizations that learn from mistakes as well as from their own and others’ successes. A learning organization is able to create or acquire knowledge and use it to modify its behavior and reflect new interpretations or new thought patterns that give it advantages (cf. Nieves and León 2001). A condition for accessing the quality of intelligent organization is to have fully identified its internal resources and capabilities in terms of knowledge and experience. Before looking outside, introspective analysis is appropriate to detect competencies, specialized knowledge, domains of expertise and forms of relationship that allow socializing and increasing that knowledge.

The term yellow pages refers to a directory of experts, its name is due to its analogy with the yellow section of the telephone directory that lists organizations by the type of service they offer. The learning organization needs to accurately locate the expert knowledge available within its performance space, this is the function of the yellow pages that transcend the traditional structures of the directories to offer the possibility of bringing peers closer and identifying opportunities for have assistance and advice within the organization itself. This function is emphasized by Graciela Perrone and Andrea Masri (2005), pointing out that knowledge management is key in making informed decisions, so it is necessary to have instruments that allow each member of the organization to know where to find knowledge, and in that sense, you should not only know what work to refer to, but know who to ask.

The yellow pages should not be confused with the concept of curriculum vitae, the yellow pages form a continuously updated directory of the organization’s know-how, José Luis Molina and Monserrat Marsal Serra (2001), indicate that:

Through the yellow pages the people of the organization are obliged to reconsider and reflect on professional knowledge, so that at the same time they serve to press and calibrate the dynamism of the organization ”, the same authors summarize in three lines the construction of the yellow pages: establish a base file, install an intelligent search engine and start up a tracking and recognition system.

The organization’s directory of experts can be considered as a type of knowledge map (2). While the key knowledge is dispersed throughout the organization, the directory of experts helps to overcome the limitations in the identification of knowledge based on formal organizational charts, hierarchical ranks, titles or jobs. The main objective of the directory is to locate and individualize people who have tacit knowledge relevant to the organization. These maps provide the “location coordinates” of the knowledge, although they do it in a referential way, they constitute the basis for contacting and interacting with those who have the knowledge and make it accessible to a large number of people, encouraging collaboration, dialogue and organizational learning (cf. Falivene and Silva 2003).

The yellow pages constitute an accessible online tool that records, in addition to the basic contact data, a description of the knowledge that people have, professional interests and the successful projects or good practices in which they have participated, highlighting their experience and competence expert More than a repertoire of knowledge is a list of who are carriers of knowledge. They are designed to identify the sources of knowledge within an organization. At the same time that they are useful to show the available knowledge they also contribute to identify gaps, that is, the knowledge that must be obtained from external sources. The yellow pages allow to identify, precisely, sources and networks of experience, so they are used to manage knowledge, grouping them into categories, areas of expertise or specialization throughout the organization. (Ponce and Falcon 2005; Lara 2002; Macedo 2000b; Meroño 2003).

 

Creating the yellow pages

When deciding to create a repertoire of expert knowledge should be considered some recommendations (cf. Cosude, 2007):

Establish your objectives clearly and precisely: what purpose will the yellow pages serve?

  • Share the responsibility for its construction and updating with the users of the yellow pages
  • Balance formal and informal information. Personal information, complemented by a photograph, will help build contacts.
  • Incorporate name, job position, team, job description, current projects, professional qualifications, curriculum vitae, areas of knowledge and specialization, areas of interest, important contacts (internal and external), intellectual production, membership in professional associations, belonging to knowledge networks or communities of practice and contact information.
  • Incorporate mechanisms for immediate interaction through the network.
  • Design registration formats to facilitate capture and recovery.
  • Maintain your update continuously and define the update periods.
  • Implement actions aimed at motivating people’s curiosity and promoting their consultation.

Tacit and Explicit Knowledge

In the knowledge management environment two types of knowledge have been established, (3). Explicit knowledge refers to a susceptible form of document and relatively easy to disseminate through digital libraries or full-text databases (such as instructions, books, articles, guides, essays or patents). On the other hand, tacit knowledge, which because it is intimately linked to the experiences, experiences, beliefs and values ​​of those who own them, is difficult to transfer, since it requires human contact between those who have and those who want to access it.

Strategies for managing tacit knowledge revolve mainly around the yellow pages, which should be designed to foster organizational culture and informal contacts between members of an organization. With this resource we can expedite the knowledge needs, for example, if we need at any given time knowledge of programming on a server or learning objects, we can find in the yellow pages the experts in the subject, along with their number telephone and email to contact them (cf. Canals and Pérez, 2001).

Due to the nature of its content, the yellow pages also operate as a support tool in the management of collaborative communities, by identifying common interests and peer affinity, allowing cohesion and trust among participants in virtual communities, fostering cross-sectional exchange. of knowledge and intensive dissemination of information in specialized fields of knowledge and, fundamentally important, identify who can lead and guide collaborative networking.

Final Comments: Human Component

Having people and equipment, technically and mentally prepared to generate and use knowledge better than other organizations, is a necessary but not sufficient condition, in addition to the attitude and competence, the development and availability of logical mechanisms and instruments for creation, recruitment, is required. Storage, location, selective access, transmission and interpretation of knowledge and information to become an organization that learns from its past experiences and intensive interaction with the bearers of knowledge either with people or with work teams. But it is not enough for people to learn, it is necessary that they convert the acquired knowledge into a useful asset for the organization, only if this condition is met we will face a real process of organizational learning (cf. Macedo, 2000a).

The success of a knowledge management system undoubtedly requires the figure of the expert, who in addition to providing information to the organization as a whole knows where to find knowledge and helps to ensure the flow of information and socialize knowledge in a way that it is available, easy to locate and accessible at all times, regardless of location. But physical access is not enough, it is necessarily required of the interaction of the expert with his peers and the possession of skills for the analysis and reworking of knowledge in such a way that it becomes action or innovation. It also requires the willingness and attitude to share knowledge, (4) as well as a climate of trust and collaboration that encourages everyone to explain and share their ideas and what can be useful to improve the results of their work (Rosa, 2000).

The mere fact of having an expert registry does not necessarily imply that it will be used by the community to which it is intended, nor does it solve the problem of the relevance of the data. Yellow pages should be kept updated periodically. People are constantly changing location, assuming different functions and incorporating new knowledge and skills. It is convenient that these are articulated with the human resources system, which ensures that work details and contact information are updated automatically, otherwise, if people have the responsibility to update their records, a Reminder process in the system, such as an email sent to users who have not updated their records since a certain date (cf. Cosude, 2007).

Having the infrastructure to share and redistribute information and knowledge does not favor organizational learning unless there is an attitude and will. In this context, the advantage of having technology is unavoidable as seen in the conditions suggested in the book by Rudy Rugles (2000), Advantages of knowledge management, text that I have adapted to highlight the relationship between action human and computer support:

Technology constitutes a decisive part in the access to internal and external information, but the most important is the human component, so that the importance of intellectual capacity is estimated at 80% and the importance of information technology only 20% is assigned.

Gathering information, synthesizing it, reflecting on it, discussing it, reworking it and transforming it into knowledge is the fundamental contribution of the human component, an essential activity for knowledge management; technology has to support that human activity but in its quality as a tool and not as an objective; However, the articulation of human activity with technology makes it possible to:

  • Have a taxonomy to categorize, organize and place tacit and explicit knowledge in an extensive knowledge base.
  • Have a person with whom to interact, to answer questions and help transfer information and generate organizational knowledge.
  • Access to a technological platform to move and share ideas, information and knowledge and relatively easy to disseminate through digital libraries or databases with full texts within the organization.

For Hernando Zorrilla (1998), organizations aimed at an effective management of their knowledge, require a high dose of human effort, which is costly but better suited in some aspects of knowledge management. When one seeks to understand knowledge, interpret it in a broad context, combine it with other types of information, or synthesize various unstructured forms of knowledge, humans are the best choice, while computers and communication systems are good for other tasks such as the capture, transformation and distribution of highly structured knowledge.

The introduction of knowledge management in organizations causes the revaluation of the figure of the expert and calls them to share their specialized knowledge and contribute their experience beyond what had traditionally been achieved. The directory of experts contributes precisely to that experience and know-how to transcend the individual level and expand throughout the organization, thereby fostering its full use and moving towards an intelligent organization; that is, in which its members, by sharing information and knowledge, synergistically and symbiotic increase their ability to solve problems and generate the results that support the objectives of the organization.

With expert knowledge management, it is proposed that:

  • One should Identify and revalue the talents of the organization and incorporate them in the management of knowledge and information, not as an end in itself but as a strategy to support the fulfillment of its objectives.
  • Active participation of the experts of the organization be motivated by their explicit recognition in the promotion system, and stimuli.
  • Incorporation of expert knowledge in the processes of integrated knowledge and information management with effects on increasing the intellectual capital of the organization and the quality and innovation of its products or services.
  • Strategic articulation of people, knowledge, processes and tasks
  • Rational introduction of information technology to enhance the action of experts and
  • extend its impact throughout the organization.

Who decides what expert knowledge we should recover?

This is a tough question. For example, speaking of education, regardless of the expert competence in a subject or in an area of ​​research or educational management, every educational institution requires competence in different fields, whether in object programming, design and operation of instruments evaluation, information analysis, environmental monitoring, strategy games, competitive intelligence, folk dance, standardization, quality management, document management, online form design, critical thinking, information management, interface design, moderation of virtual forums, etc.

Although there is a need to narrow down the topics of interest and define categories of required or desirable knowledge, the variety of possible areas of expertise is abundant, and potentially any member of the organization can be an expert in some activity or specialized knowledge capable of providing value to the organization Rather than thinking about discarding knowledge we should think about incorporating strategies to take full advantage of expert competition.

In a broad sense, we all have an area of ​​expert competence and we all need help at some time or circumstance of work. However, confusion between discipline or specialty with the concept of expertise is frequent; Being an expert does not necessarily imply being “wise” in the subject or subject, but knowing a little more about the subject, which is recognized by the peers and therefore, is being able to contribute to the objectives of the organization. (cf. All experts 2006)

Although a review of the literature available on the web has been made, there are many pending, so that this is not the end of a necessary reflection but the beginning of a shared work. These lines are intended to contribute to the debate aimed at specifying concepts and motivating interest in the development of better tools to share knowledge, without forgetting that the best tool available, will be completely useless if the environment does not exist and the willingness to share

Starting from the premise proposed by José Luis Lara (2002): […] for organizations to be driven to innovate, they must be subjected to a variable degree of incitement to change, then this proposal is opened as an open provocation to collaboration and intensive knowledge management.

 

Endnotes

 

  1. In the colloquial language there is talk of expertise or expertise to refer to the condition of being a shower or experienced in a certain matter or subject, however in both cases consultations were made in dictionaries and it was confirmed that these terms do not appear registered, there is Expertise word but its meaning is that of expert evidence. The word expertise that denotes wisdom, practice, experience and skill in some subject was found useful, while expert is also the adjective to signify the condition of being wise, skilled, skilled, skilled, practical in some subject.
  2. Knowledge maps are graphical representations that allow identifying what knowledge is available in the organization, where they are located and who are the bearers of them. They represent the flows of knowledge, subjects and relationship nodes, facilitators and barriers that explain the processes of creation, distribution, application and reuse of knowledge in an organization
  3. The term knowledge should not be confused with data or information. Data is the representation of a fact so that it can communicate, while information is the significance acquired by the data when they are placed in an appropriate context and according to an application purpose. Knowledge is the result of processing information and incorporating the intelligence and structure required to allow action and problem solving. The knowledge so that it can be documented requires its conversion into information and structured data that can be represented, stored in print or as a digital record.
  4. Knowledge grows when we share it, unlike the capital that runs out if we share it.

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Knowledge Management

Notes On Designing an Integrated Methodology for Knowledge Management Strategic Planning: The Roadmap Toward Strategic Alignment

Notes on European Guide to Good Practice in Knowledge Management – Part 1: Knowledge Management Framework

Notes from European Guide to Good Practices in Knowledge Management – Part 2: Organizational Culture

Notes from European Guide to Good Practice in Knowledge Management – Part 5: Knowledge Management Terminology

English Translation of Locating Expert Knowledge: Yellow Pages

English Translation of Brief Inventory of Models for Knowledge Management in Organizations

English Translation of Design of a Knowledge Management Model for Improving the Development of Computer Projects’ Teams

English Translation of Design and Implementation of Knowledge Management Projects