UNFADING DECISIONS

A Position Paper on Decision Reconstruction

Francisco Antunes

Institute of Computer and Systems Engineering of Coimbra, R. Antero de Quental, 199, Coimbra, Portugal

Management and Economics Department, Beira Interior University, Estrada do Sineiro, Covilhã, Portugal

João Paulo Costa

Institute of Computer and Systems Engineering of Coimbra, R. Antero de Quental, 199, Coimbra, Portugal

Faculty of Economics, Coimbra University, Av. Dias da Silva, 165, Coimbra, Portugal

Keywords: Decision Reconstruction, Decision and group support systems, Knowledge management.

Abstract: The importance of understanding and recording past decisions increases when we realize that employees’

memories are not always available, neither will they last permanently in organizations. In this paper we

posit that the ability to perform decision reconstruction using a Group Support System (GSS) can provide a

flexible solution to the problem, but only if the information model underlying it is able to provide

bidirectional support to the phases of a decision-making process. For this, we present general characteristics

for an information model to support decision-making as well as decision reconstruction processes.

1 INTRODUCTION

Probably there are many occasions when the sole

review of discussion topics and resulting decisions is

enough to recall the details of the decision process,

especially if the people who review them are the

same decision agents who were involved in it. Still,

as those decision agents may no longer be in the

organization, we believe that anyone should be able

to retrieve that information easily. In these

circumstances, the GSS, whose features (which are

described in detail, for instance, in Bafoutsou &

Mentzas, 2002) should allow in-depth examination

whenever required. In addition, GSS constitute a

technical element for organizational memory (as

defined, for instance, in Ackerman, 1998; Hoffer &

Valacich, 1993; Lehner & Maier, 2000; Stein &

Zwass, 1995; Walsh & Ungson, 1991) and decision

reconstruction (DR).

Methodologically, our research lies within the

scope of design research. This option takes into

consideration the creation, use, study and

performance evaluation of artefacts in order to

understand, explain and improve information

systems (Hevner, March, Park, & Ram, 2004; March

& Smith, 1995). We have adopted the process

defined by Peffers (explained in Peffers, et al., 2006)

because it is an eclectic approach, which combines

the research steps of other authors and it emphasizes

knowledge use and development, throughout the

research. We tested initial ideas on decision

reconstruction through laboratorial tests and case

studies (published elsewhere). From the gained

insights we found that most of our considerations

were ratified, but there were still unaddressed issues.

This paper presents the combination of all our

findings, whose discussion will, hopefully, gather

extended insights, before performing a second

testing round (iteration).

2 DECISION RECONSTRUCTION

We define decision reconstruction as the process that

allows an individual or group of individuals (the

decision reviewers), whether internal or external to

the organization, to understand how a GSS

supported group has reached a previous decision.

As stated in the introduction, GSSs are a natural

solution for distributed collaborative of work,

providing structured opportunities to engage in

deliberative exploration of ideas, evidence and

374

Antunes F. and Costa J..

UNFADING DECISIONS - A Position Paper on Decision Reconstruction.

DOI: 10.5220/0003080503740377

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2010), pages 374-377

ISBN: 978-989-8425-29-4

 2010 SCITEPRESS (Science and Technology Publications, Lda.)

Table 1: Support needs.

Decision process Reconstruction process

Argumentation

Cover a multiplicity of argumentation models.

Express the relationships among the argumentation elements.

Maintain and evidence the linking scheme of the used argumentation

model.

Structure

Create meaningful categories.

Link information element between discussions.

Review of the in-between steps of a decision process.

Turn information elements into an “inactive” state, instead of its deletion.

Decision-making

Use computer-guided decision-making techniques

Use manual convergence methods

Access the details of the performed convergence processes.

argument (Osborne, 2010).

Nevertheless, as GSSs are built upon the idea of

cumulative (sequential) support for the decision-

making phases (as defined by Simon, 1977, i)

intelligence phase; ii) design phase; and iii) choice

phase), it is not always easy to understand the earlier

stages of a discussion. This is particularly evident at

the end of discussions when classes, which were

created to encompass the discussion elements and

some of the details, are “flattened”.

Understanding how the past decisions affect

present ones fosters the relationships between

information and facilitating the use of knowledge in

mutually dependent contexts (Guerrero & Pino,

2001). We believe that by fostering the decision

reconstruction ability of GSSs, we promote their

capability for information retrieval, thus contributing

to ease and deepen the comprehension of past

decisions, while fostering knowledge acquisition. In

addition, expanding GSSs capabilities from the

perspective of knowledge management can

significantly improve the performance and

satisfaction of group meeting participants (Hung,

Tang, & Shu, 2008). We also stand that decision

reconstruction can enhance transparency (as stated

in Danielson, Ekenberg, Grönlund, & Larsson, 2005;

Stirton & Lodge, 2001), and will empower GSSs as

tools for public consultation and the external

scrutiny of decisions.

It is known that GSS solutions should cover a

multiplicity of approaches to support different ways

of building a collaborative discourse (according to

Turoff, Hiltz, Bieber, Fjermstad, & Rana, 1999).

These ways range from a simple question-reply

pattern to more elaborate argumentation models

supported by argumentation theory (as seen, for

instance Bentahar, Moulin, & Bélanger, 2010; Kunz

& Rittel, 1979; Maleewong, Anutariya, &

Wuwongse, 2008; Toulmin, 2003). A general GSS

information model for decision reconstruction needs

to be able to register (document) the in-between

steps of the convergence/consensus-building

provided by the interconnection of the

argumentation elements presented by the group,

during the discussion. This type of behaviour

resembles the capabilities of entity-based versioning

systems, which can create versions of packages,

classes, and even individual methods of a complete

system over its entire lifespan (Robbes & Lanza,

2005). The fine-grained ability to version

argumentation elements allows its in-depth

registration and to evidence their evolution over

time.

Another issue in decision reconstruction regards

the validity of the organizational memory. When

information expires (whether based on

administrator’s decisions or determined by existing

laws), a cleaning process can occur. We stand,

however, that the deletion of such information might

constitute an important barrier to decision

reconstruction, even when earlier information is

“flattened” to some condensed form. To this matter,

no records could mean no memory and,

consequently, the inability to retrieve past decisions.

Having in mind the intention to register all the

steps in decision-making to foster decision

reconstruction, instead of deleting information,

contributions should be marked as “active” or

“inactive” in order to be considered in the group

analysis (meaning that an inactive contribution

represents a “deletion” but without actual

information loss). We stand that it is possible to

embed the previous characteristics into an

information model to support both decision-making

and decision reconstruction, by incorporating three

different, though implicitly intertwined, types of

Table 1.

3 BUILDING THE DECISION

RECONTRUCTION SUPPORT

In order to develop an information models that fits

the abovementioned needs, whether in decision-

making or in decision reconstructing, previous

research (published elsewhere) makes us stand that

UNFADING DECISIONS - A Position Paper on Decision Reconstruction

375

is necessary to: create a flexible support for inserting

group’s contributions; link the contributions;

establish associations among information elements;

and ensure the recording of the in-between steps of

the group meeting.

A flexible model to support a wide range of

argumentation models should address contributions

as independent elements, without imposing any sort

of pre-established associations. The connection of

contributions should provide the support to establish

void links, and a different support to characterize

such links, as there are different types of expressed

connections. These connections depend on the:

argumentation model relationships (e.g. support,

response to, evidence for, etc.); structuring support

(as one of the most common features in GSS is their

ability to separate contributions into meaningful

categories or information containers, namely,

discussions, topics, categories, information

“buckets”, documents, etc.); and time-span

association (sequence, dependence, versioning,

merging, etc.). The creation of a void connection

network creates the possibility to develop a multiple

characterization framework that does not have to

impose any type of relationships, structure or

argumentation scheme beforehand.

Depending on the discussion, decision-making

support might benefit from the use of formatted

contributions or from predefined data-types used

when inserting data, especially when quantitative

data is under analysis (e.g., percentage numbers,

weights, etc.). Therefore, the connection support

could also address the data validation rules over

contributions, in order to ease or automatically

support later convergence processes. As different

discussions (or discussion segments/phases within

discussions) may require distinct argumentation

schemes, it is important to offer the support for

using different argumentation models, as usual GSS

embed an athwart representation for the whole

discussion.

The connection among contributions requires

additional characterization to define their

argumentation role within the GSS, but such

characterization should not be embedded within the

contribution support, but using associated meta-data.

In addition, different types of connections should

also be expressed using meta-data. Such association

types must include: argumentation model

relationships; structuring support; and time-span

association.

Expressing more complex argumentation models

as simpler ones does not seem troublesome. The

opposite, however, may not be accomplishable (at

least automatically) due to the lack of associated

information. Producing such information requires

the establishment of new types of associations)

beyond the ones established in the decision process.

We believe that two processes (or their

combination) could be tried, in order to achieve the

desired situation. The first one would be the

reviewer’s manual supply of the relationship

properties as individually perceived. To support this

process, the GSS should ask the reviewer to input all

the necessary association attributes, according to the

intended argumentation model. The second

procedure could use automatic mechanisms, i.e.

intelligent agents, to perform a semantic and

syntactic analysis of the different contributions and

propose the type of detected relationships to be

confirmed by the decision reviewer.

The capture of the relationships between the

discussion elements covered by the information

model should also provide the necessary basis for its

visual representation. In order to enhance its utility

in decision reconstruction and especially to respond

to different information needs and cognitive styles of

decision reviewers, it requires, nevertheless, a

combination with tools for filtering, sorting,

selecting and displaying multiple relationships.

When supporting groups in achieving decisions,

divergent contributions may exist. To deal with this

situation a GSS should provide converging and

decision-making techniques. However, as achieving

the final decision might require more than one

convergence process and more than just one

convergence method (whether manual or computer-

guided), GSS should provide a versioning capability

over the used argumentation elements and

convergence processes. Maintaining a record of the

convergence process, as well as the used methods,

contributes to ease the decision reconstruction

processes by saving and linking the in-between steps

of the decision process. The in-between recording

should also allow the production of better

reports/documents derived from the GSS decision

processes, because usual reports only embed the

latest result, especially when reporting is an

automatic feature.

Any decision report should encompass the

reasons that explain the decision outcome. However,

the process that selects such reasons and its

relevance is not a standard or an always-clear one.

As decision reviewers might not share the

relevance pattern or judgment assessment expressed

in the produced documentation, decision

reconstruction might be hindered. It would be

interesting if a GSS could parameterize automatic

KEOD 2010 - International Conference on Knowledge Engineering and Ontology Development

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recording procedures (coarse or fine grained), in

order to produce a final document or report, for

instance, based on the performed convergence

processes, which recorded the decision evolution

within a certain time-span.

4 FUTURE RESEARCH

This paper presented the combination of initial ideas

on decision reconstruction and gained insights from

earlier testing, from which we have outlined what

we posit to be the set of fundamental characteristics

to develop an information model to support the

decision-making process, as well as the decision

reconstruction process. The defined methodology

dictates the need for a second testing round where

we intend to embed the proposed characteristics into

a GSS prototype and to submit it to further

laboratorial evaluation and case study analysis.

ACKNOWLEDGEMENTS

This work is encompassed within the aims of the

FCT PTDC/EGE-GES/113916/2009 project.

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