From Anarchy to System: A Novel Classification of Visual Knowledge Codification Techniques

• Author: Tatiana Gavrilova,Dmitry Kudryavtsev
• Published date: 01 January 2017
• Date: 01 January 2017
• DOI: http://doi.org/10.1002/kpm.1509

■Research Article

From Anarchy to System: A Novel

Classification of Visual Knowledge

Codification Techniques

Dmitry Kudryavtsev*and Tatiana Gavrilova

Graduate School of Management, Saint-Petersburg State University, Russia

The paper suggests a classification of visual knowledge codification (diagramming) techniques for multi-perspective

business systems analysis and design. The classification is based on seven main categories of knowledge:

what-knowledge, how-knowledge, who-knowledge, why-knowledge, what for-knowledge, when-knowledge and

where-knowledge. The classification defines both knowledge type and the most appropriate kind of diagramming

technique. Examples for use of this classification system for marketing function applications are presented. Specific

examples of these applications include mind map, concept map, Ishikawa diagram, strategy map, business process

models and function trees. It is hoped that the new classification will allow better practical use of diagramming

techniques in business and lead to fewer professional misunderstandings and more effective business communication.

The aim of this research is thus to improve visual literacy among both business practitioners and educators. Copyright

© 2016 John Wiley & Sons, Ltd.

INTRODUCTION

Knowledge visualization has proved to be an

effective tool for knowledge creation, acquisition

and transfer (Eisenstadt et al., 1990; Eppler and

Burkhard, 2007; Gavrilova and Gulyakina, 2011).

According to Eppler and Burkhard (2007), there

are several formats of visual knowledge representa-

tion: heuristic sketches (e.g. the ad hoc, joint draw-

ings of complex ideas in meetings), conceptual

diagrams (such as Ishikawa diagrams), visual

metaphors (such as an iceberg visualization

distinguishing implicit and explicit forms of knowl-

edge), knowledge maps (such as a landscape of

in-house experts) and interactive visualizations (to

help users to explore complex information in inter-

active form). These graphic formats capture not

only (descriptive) facts or numbers (information

visualization), but also contain prescriptive and

prognostic insights, principles, basic assumptions

and relations. The focus of the current research is

on qualitative conceptual diagrams —schematic

depictions of abstract ideas that use standardized

shapes to structure information and illustrate rela-

tions. Conceptual diagrams help to make abstract

concepts accessible, reduce complexity to the key

issues (Huff, 1990), amplify cognition and facilitate

discussion of relationships. In this paper, we will

often use diagramming and visual knowledge

codification techniques synonymously.

Diagrams (Blackwell and Engelhardt, 2002)

constitute the basis for visual knowledge represen-

tation, and elaborate diagrammatic techniques

typically form visual modelling languages (Harel

and Rumpe, 2000). In computer science, these

techniques are reflected in such languages as UML

(Rumbaugh et al., 2004) and IDEF (Mayer et al.,

1992). They are also integrated in software engineer-

ing methods, for example, the Structured Analysis

and Design Technique, and are organized by archi-

tecture frameworks, such as the Zachman frame-

work (Zachman, 2003).

The focus of this paper is the realm of manage-

ment. Managers frequently use diagrams in their

work (Galloway, 1994; Hodgkinson et al., 2004;

Lengler and Eppler, 2007), but the choice of dia-

grams is often error-prone and inconsistent (Eppler

and Jianxin, 2008).

For the effective choice of visualization method,

at least five perspectives should be considered

(Eppler and Burkhard, 2007). These perspectives

*Correspondence to: Dr Dmitry Kudryavtsev,Graduate School of

Management, Saint-Petersburg State University, Russia.

E-mail: d.v.kudryavtsev@gsom.pu.ru

Knowledge and Process Management

Volume 24 Number 1 pp 3–13 (2017)

Published online 20 May 2016 in Wiley Online Library

(www.wileyonlinelibrary.com) DOI: 10.1002/kpm.1509

Copyright © 2016 John Wiley & Sons, Ltd.