Diagnosis and Prognosis of Knowledge Management based on

k-Workflow, on Conversion and Knowledge Flow

The Case of the National Land Transport Agency in Brazil

Luiziana Rezende

1,2,4

, Maria Angela Lobão

2,5

, Joel de Lima Pereira Castro Junior

2,3

Luiz Angelo Merino

, Soraia Alves Rocha

, Carlos Alberto Malcher Bastos

Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

GtecCom / Fluminense Federal University, Niterói, Brazil

PPGAd / Fluminense Federal University, Niterói, Brazil

Post DocPPEngProd / Fluminense Federal University, Niterói, Brazil

IBMEC Faculty, Rio de Janeiro, Brazil

Keywords: Knowledge Management, Knowledge Workflow, Conversion and Knowledge Flow, Innovation.

Abstract: This paper presents the main contributions of the Iterative Model for Knowledge Management proposed by

Universidade Federal Fluminense (UFF) in cooperation with the Brazilian Agency for Land Transport

Regulation (ANTT). The method’s great innovation is to combine to the KM diagnosis and prognosis, the

concepts of conversion and knowledge flow, with the application of the 5W1H method and Enterprise

Architect (EA) software to integrate the models built, also allowing its graphical representation. The models

and products obtained have allowed: to understand the culture of the Agency's current KM; view existing

gaps and needs in their knowledge flow construction and in the process of converting knowledge; propose a

set of KM practices and tools appropriate to their reality and predict future actions of improvement that

impact on the efficiency of the regulatory process.

1 INTRODUCTION

Currently, organizations have several computerized

systems to support the implementation of its

processes and activities without a structured

information and knowledge model. In this scenario,

some problems were identified: the absence of an

information critical analysis culture; low level of

information integration between sectors; absence of

a formal structuring information process to

facilitate/enable the fulfillment of the institutional

mission; dispersed knowledge and with difficult

access, requiring transformation of tacit knowledge

into explicit and provision /sharing explicit

knowledge to decision making process.

ANTT, National Land Transport Agency in

Brazil, is an entity linked to the Ministry of

Transportation and the regulation Agency of the

exploitation of federal railway and highway

infrastructure activity and land transportation

provision activity in Brazil.

In order to fulfill its mission, the Agency needs

to have its information and knowledge identified,

mapped, integrated and available to those who may

need it effectively building an Information and

Knowledge Management Model (MGIC).

In order to develop a MGIC for an organization

there are some necessary preliminary steps which

are essential: information assets identification,

information and knowledge flows and knowledge

and skills mapping.

The major difference of MGIC is that it uses, in

an innovative way, a specific methodology that

brings together several theories, methods and tools

embodied in the information and knowledge

management.

This paper is a step of the building process of a

MGIC and the result of the academic and scientific

research; with the application of a case study

conducted in the Brazilian land transportation

Agency (Bastos et al., 2011).

Based on these products and aimed at creating a

fertile environment for new ideas and problem

413

Rezende L., Lobão M., de Lima Pereira Castro Junior J., Merino L., Alves Rocha S. and Malcher Bastos C..

Diagnosis and Prognosis of Knowledge Management based on k-Workﬂow, on Conversion and Knowledge Flow - The Case of the National Land

Transport Agency in Brazil.

DOI: 10.5220/0004550104130418

In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge

Management and Information Sharing (KMIS-2013), pages 413-418

ISBN: 978-989-8565-75-4

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

solving, another goal is to make proposals and

suggestions for improvements in knowledge

management in ANTT.

The phases presented in this work are

specifically modeling, analysis and representation of

knowledge management in one Organizational Unit

of the ANTT, providing details on methodology and

method.

This paper is organized as follow. The next

section presents the Knowledge Models

Development Phases; the section 3 the Analysis of

the Models and Generated Products, the fourth

section shows Diagnosis of the current status of

Knowledge Management, finally the fifth section

shows the conclusion of the work in progress.

2 KNOWLEDGE MODELS

DEVELOPMENT PHASES

For developing of an Information and Knowledge

Management Model (MGIC), the first phase is the

knowledge and skills mapping using a specific

method, which enables to build a knowledge tree,

knowledge and skills topography and a unified

knowledge database, which enable a descriptive and

analytical approach to knowledge management in

the organization.

For building a MGIC, there have been

specifically adopted the following integrated

methodologies and scientifically proven in the

literature: Zarifian (2005) and Fleury and Fleury

(2004) with the concept of mobilization of

knowledge and skills; Rezende (2007) with the

Iterative Method for Mapping and Analysis of

knowledge and Skills; Nonaka and Takeuchi (1995,

2009) with the SECI Model explaining the processes

of knowledge conversion and the knowledge spiral;

Michael Authier and Pierre Lévy (1992) with the

concept of the knowledge tree for knowledge

dynamic structuring .

It is worth mentioning that the initial part that

composes the MGIC: Information Asset

identification and modeling, Information Flow and

Ontology model, as well as the final phase of

construction of the architecture and implementation

of knowledge management in the organization, are

described in a more complete methodology for the

construction of MGIC (Bastos et al., 2011).

The relevance of the method lies in the fact that,

while it maps knowledge/skills/professionals, it also

analyzes the flow and the processes of knowledge

conversion in the organization, supporting the

construction of architecture and a tool proposition

for knowledge management.

The method application allows the organization

to identify the relevant sources of information and

knowledge and set the strategy for its collection and

methods for its analysis; to implement a culture of

research, collection, recording and analysis of

knowledge within an organizational context; to

know what types of knowledge exist and where they

are located, to manage them, integrate them and

organize them, in order to make the most of their

extraction for decision-making; support to the

organization through knowledge sharing and

integration among employees, enabling the

transformation of tacit knowledge into explicit;

improve the localization and exploitation process of

new knowledge that, despite having it, the

organization is not able to identify, thus enriching

creativity and generating competitive intelligence; to

identify experts (inside professionals) to give

technical support for analysis; to support the

construction of communication forms, conversation,

learning, training community work, structuring

individual and teams experiences, facilitating access

to ideas and solutions.

In the phases of knowledge and skills

identification and collection, initially, there were

mapped the procedures for carrying out the

information flows activities and related to explicit

and tacit knowledge, as well as the skills of the

professionals involved. In this process we created a

Knowledge Workflow (k-workflow), an innovation

in modeling process and knowledge management

created especially for the MGIC.

For knowledge and skills mapping and

representation and k-workflow building, there were

used a methodology based on research developed by

Rezende (2011), the methodology 5W1H (Ikeda et

al., 1997) and the software Enterprise Architect (EA)

for the models integration and reports generation.

For visualization in a hierarchical form of shared

and specialized knowledge, the Treebolic (2007)

software was used for the construction the

knowledge tree (Authier and Lévy, 1992).

From the construction of knowledge and skills

topographies and an integrated database, it was

possible to generate descriptive graphs that enable

statistical analysis.

An important level of analysis is the

identification of gaps in knowledge flow (Figure 1)

and the process of knowledge conversion (SECI

Model), proposed by Nonaka and Takeuchi (1995;

2009), which allows to have a vision of KM as a

process.

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From the knowledge gaps identification during

the analysis phase there were suggested techniques,

practices and tools that allow the organization to

capture, mobilize and innovate knowledge as an

input for the development of intellectual capital and

social capital through effective services.

Figure 1: Knowledge flow.

The models developed, Iterative Method for

Knowledge Mapping and Management in Enterprise

Environments, indicating the different steps

performed: 1) information collection; 2) knowledge

and skills survey; 3) classification; 4) representation

and 5) analyzing, during which several products are

generated.

The first stage of information collection was

conducted through open interviews with managers

and employees, chosen by the nature of their

functions and specializations potentially useful to

participate in the collective knowledge development

process.

This step has two well featured phases, the first

phase is inputs consolidation at the information level

and needed knowledge to start modeling, where it

was taking into consideration: a) all documents

provided to assist the agency understanding, b)

existing systems at the agency, c) the list of

information assets and d) the actors/workers

identified at the generated models in the previous

stages of MGIC construction.

From the consolidation phase of the inputs, the

professionals list to be interviewed was identified. A

script was prepared for interviews considering all the

knowledge previously gathered in information

flows.

The interviews, which were carried out openly

and transcribed manually searched to identify the

existing explicit and tacit knowledge and skills

needed to perform the activities.

The method generates a table that shows a sketch

with the demographic data of the interviewed

employees that can allow to analyze the expertise

level and realize their correspondence to operational

skills at the Organizational Unit (OU).

The workflow, was made based on 5W1H method

(Ikeda, Okumura and Muraki, 1997), led to the

breakdown of activities to be undertaken for the

management of an information asset. The method

also generates an outline of working groups identified

in the information assets.

Thus, the collection stage enabled the

construction of the k-workflow containing

procedures for implementation of information asset

and their knowledge, their skills and their related

working groups, the information asset matrix x

interviewed x working group and the listing of

demographics data of the interviewed professionals

(Figure 2).

The second stage was to survey, which allowed

the mobilized knowledge definition and the skills

needed to perform the activities of an information

asset by working group. Consequently it was

possible to generate knowledge and skills lists.

After information collecting phase the

knowledge and skills of an information asset were

identified. The materials collected in the interviews,

documents provided and the existing systems

applied were used to define the knowledge and

skills.

In this phase it was performed the knowledge

Topography composed of the following steps:

identification, description and classification (nature,

relevance and level).

By analyzing the knowledge topography, it was

identified that the majority of processes are well

structured for employees.

All identified knowledge was of explicit nature,

with well-defined location, but without a systematic

storage, retrieval, update, dissemination and

recreation.

In this phase it was performed the skills

topography, consisting of the following steps:

identification, description, relevance and skills

representation (Rezende, Lobão, Burmann, Castro

Júnior, Merino, Rocha and Bastos, 2012).

The third stage, the classification, aims to

construct the knowledge and skills topographies.

The knowledge topography consists in classification

in nature terms (tacit or explicit), relevance

(irrelevant, little irrelevant, relevant and very

relevant), knowledge level (basic, intermediate and

advanced) and its location. Based on these ratings

the relationships map was constructed from

information assets x activities x working groups.

From knowledge and skills topographies and the

relationship matrix it was prepared the basis for

DiagnosisandPrognosisofKnowledgeManagementbasedonk-Workflow,onConversionandKnowledgeFlow-The

CaseoftheNationalLandTransportAgencyinBrazil

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Figure 2: Knowledge workflow and map of knowledge/skills/work groups.

construction of knowledge /skills / professionals

map.

The fourth step was the representation, which

consisted of the knowledge/ skills/professionals map

(through the use of EA software) and the knowledge

tree (using the Treebolic software).

To view in a hierarchical way the knowledge

gathered the knowledge tree was used as graphic

representation. This visual instrument to represent

knowledge is easy to handle and allows any user to

explore a whole information structure without

feeling lost in its hierarchy.

The organization can use the knowledge tree as a

support tool to help: the elaboration of a training

plan and capacity building; locating expertise;

sharing information; indicating knowledge gaps.

In the final stage of model analysis there were

constructed descriptive charts, showing the different

possible groupings of the information and

knowledge gathered, classified, represented and

mapped. Gaps were identified in relation to the

knowledge flow (Figure 1) and the SECI Model

(Nonaka and Takeuchi, 1995, 2009).

Yet it was possible to investigate the correlations

between skills and knowledge that indicate new

relationships associated with information assets,

activities and working groups.

The following section presents outlines of

models and generated products at each stage of the

method and its application.

3 ANALYSIS OF THE MODELS

AND GENERATED PRODUCTS

Several analyses can be performed from the models

and generated products. With the knowledge basis

built it is possible to identify: the existing working

groups in the organization, the working groups

associated with an information asset, the working

groups associated with different information assets

activities; the technical knowledge ordered by the

relevance; correlations between activities /

knowledge /skills; specializations by working groups

and vice versa; specialized and shared knowledge

and data intersections of interest to the organization.

The analysis of the technical knowledge of an

information asset by relevance may influence the

profile definition of knowledge that an employee

must have to perform his activities efficiently.

Another application may be the use of these analyses

as an additional tool for the process of evaluating the

employee performance.

The analyzes of the activities numbers of the

working groups in the implementation process of an

information asset within the Organizational Unit

may help in assessing the OU assessing the number

of activities performed by a particular working

group.

It should be noted that other possible analysis

may be performed from the knowledge basis such

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as: a) working groups in ANTT by area; b)

information asset associated to working groups; d)

technical expertise ordered by relevance; e)

correlations between activities/ knowledge/skills; f)

expertise by working group and vice versa; g)

specialized and shared knowledge. Therefore, the

Agency has a strong management tool to define

projects teams, employees recruitment process,

development of training courses for the different

working groups, monitoring and evaluation of

performance of its employees, among others.

4 DIAGNOSIS OF THE CURRENT

STATUS OF KNOWLEDGE

MANAGEMENT

Throughout the processes of data collection,

mapping and modeling, information and knowledge

inputs were consolidated provided by the Agency to

understand the business processes, ANTT's mission

and how their activities contribute to achieving the

Agency’s goals.

Based on these inputs a diagnosis of Knowledge

Management was built in the following categories:

People; Knowledge Management; Organization/

Procedures.

Regarding the People category, we evaluate the

experience and the educational of the Agency staff.

As far as the Organization and Procedures for

Knowledge Management category is concerned, we

evaluate the knowledge required for the execution of

information assets, if it is formalized in documents

and is integrated by systems. We are also interested

if the Agency promotes knowledge sharing and if it

includes dissemination activities for training new

employees. The K-workflow procedures for carrying

out the necessary activities for implementing their

information assets helped us to understand its

operation and identify its working groups. It is

noteworthy that the most of employees interviewed,

participate in more than one working group. We are

particularly interested to know if the environment is

adequate for the implementation of methods and

techniques of knowledge management.

Knowledge management has the function to

strengthen the individual and organizational

knowledge basis. In the category related to

Knowledge Management, we evaluate if the stages

of knowledge flow are properly covered, associated

to the steps of knowledge capture, mobilization and

consequently to innovation steps.

We evaluate if documents and reports

standardization support the implementation of

information assets and if storage and documents

protection are done in an unique way.

Regarding the mobilization stage, we evaluate if

overall and specific goals from previous years are

used as inputs for the creation of the new documents

and information assets. It is also verified if the

Agency promotes sharing and dissemination among

stakeholders.

We also evaluate if there are some gaps in the

steps of knowledge capture and mobilization that

can compromise the innovation stage.

We also evaluate if the four models of

knowledge conversion: socialization,

externalization, combination and internalization are

performed systematically in stages of knowledge

flow for implementing identified information assets.

The socialization process is regarding individual

and collective experiences sharing to create new

tacit knowledge. In the organizational, it occurs

through training, customer interactions, informal

sessions, brainstorms. So, we are interested in

identify the need to intensify the integration among

actors involved and to socialize knowledge and

successful practices.

The externalization process consists of

knowledge creation through new and explicit models

from tacit knowledge. We are interested to check if

tacit knowledge is been explicit and registered and if

knowledge is mapped and organized to be used.

In the combination process, which occurs

through the exchange and combination of different

sets of explicit knowledge, and that in the

Organization is acquired especially by means of

documents, meetings or computer network, it has

been found that the absence of a knowledge database

centralized, integrated and consolidated causes

avoidance of explicit knowledge thus making it hard

the activities related to analysis, reporting and

consultation documents. In order to have quality and

efficiency in the activities performance, it is

necessary to ensure that the skills are available for

the application, reuse and creation.

The internalization process occurs in conversion

of explicit knowledge into tacit, by "learning by

doing". So we are interested to check if information

from prior years is used as support for the

development of new reports and documents and if

knowledge is internalized and therefore used for the

construction of new explicit knowledge.

In order to accomplish the prognosis of methods,

techniques and tools for Knowledge Management,

each category used in KM diagnosis is then analyzed

and some improvements recommendations are

DiagnosisandPrognosisofKnowledgeManagementbasedonk-Workflow,onConversionandKnowledgeFlow-The

CaseoftheNationalLandTransportAgencyinBrazil

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proposed in order to eliminate the gaps identified in

knowledge flow and knowledge conversion

processes.

5 CONCLUSIONS

The Iterative Method proved to be effective in its

application, allowing to identify, collect, map,

analyze and represent tacit and explicit knowledge,

skills and professionals mobilized and involved in

the construction of information assets, besides

analyzing the knowledge flow in all stages.

Mapping will facilitate the activity of allocation,

reallocation and professional training according to

the activity to be performed, besides facilitating the

location of key people, those that have the most

relevant knowledge on a particular subject.

Critical success factors identified and their

enablers in KM may assist managers in their

decision making process in different situations, such

as: process improvement using techniques and tools

of knowledge management; identification of

knowledge gaps in professional activities; perception

of opportunities for new training courses and

competences building; identification of gaps

between individual's professional knowledge and

skills needed to perform activities.

The method developed can be applied to other

domains of different areas, constituting a knowledge

basis for Knowledge Management.

KM models developed for the Agency based on

its information assets are implementable in the short

or medium term, through the use of best practices

and tools (intermediate results) or from the

application of KM architecture still under

construction (final results).

From knowledge basis constructed throughout

modeling process it is possible to make more

descriptive analysis such as: working groups

associated with one or several information assets and

vice versa; working groups associated with different

activities of an information asset, correlations among

activities/skills/abilities of one or more working

groups and vice versa. The managers have at their

disposal an incremental basis of knowledge, unique

to the Agency, which enable different analysis

depending on the need and the decision to be made.

With mapping and modeling built it will be

possible to structure the KM architecture of the

Agency and define proper methods, techniques,

technologies and tools for their effective knowledge

management, allowing it to fulfill its mission more

effectively.

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