Supporting distributed decision processes using an evolution model

ORI GIN AL PA PER

Supporting distributed decision processesusing an evolution model

K. N. Papamichail Æ I. Robertson

Received: 7 September 2006 / Revised: 11 September 2007 / Accepted: 4 June 2008 /

Published online: 22 August 2008

� Springer-Verlag 2008

Abstract In recent years, emerging Information and Communication Technologies

have changed the nature and process of decision making. Decision processes are

often distributed, heterogeneous and subject to change. Business process modelling

is a key technology for analysing, representing and executing business processes. It

can be used to study distributed decision processes and improve decision making

practices. A theoretical model of the decision process has been developed in order to

better integrate the decision concept with models of business processes. The decision

model is executed using a process support system that provides a distributed Web

user interface. The enacted decision model evolves as the decision process pro-

gresses and supports decision makers if and when needed. The case study of an actual

decision process undertaken in a not-for-profit organisation is presented to highlight

the use, execution and validation of the decision model.

Keywords Business process modelling � Decision support systems �Distributed decision processes � Evolution � Process support technologies �Web-based decision support

1 Introduction

‘An executive decision is a moment in a process’, so stated Mary Parker Follett

(Follett 1941). This observation, which has unfortunately been largely ignored in the

K. N. Papamichail (&)

Manchester Business School, University of Manchester,

Booth Street East, Manchester M15 6PB, UK

e-mail: [email protected]

I. Robertson

School of Computer Science, University of Manchester,

Oxford Road, Manchester M13 9PL, UK

123

Oper Res Int J (2008) 8:279–297

DOI 10.1007/s12351-008-0019-1

intervening years, can refer to two contexts. The first is when the decision is a

commitment to action, and the commitment is only one element of the overall

process of making a decision. The second context is when the act of decision-

making may be only a small element in a very much larger process by means of

which an organisation fulfils its objectives. Contemporary activity in the area of

decision support has largely ignored the relevance of the business process to the

decision. The main focus of decision-aiding tool development has been on

supporting more elegant analyses and evaluation algorithms and integrated solutions

(i.e. one piece of software to cover all functionality).

It has been shown that the effectiveness of strategic decisions depends on the

decision steps that managers follow in order to reach them (Dean and Sharfman

1996). Particular conditions, i.e. patterns of relationships among variables such as

sufficient information and means of implementation, organisational type and

interference from the top can contribute to successful decisions (Rodrigues and

Hickson 1995). Decision processes are related to decision-specific and top-

management characteristics as well as contextual factors (Papadakis et al. 1998).

Even behavioural characteristics such as affective state or mood can affect the

decision process (Elsbach and Barr 1999). An analysis of a large number of

decision processes can help researchers and practitioners identify best and worst

practices in exploring alternatives and adopting a suitable decision approach (Nutt

2000, 2002).

Organisational decision makers often skip decision steps, execute decision steps

out of order and do not adopt a decision protocol (Mintzberg et al. 1976; Nutt 1984;

Hickson et al. 1986). Process support technologies could be used to support and

coordinate decision processes. Such technologies tend to support well-structured,

time-invariant and single-dimension workflows. However, workflows and decision

processes are influenced by actors whose behaviour is not deterministic (Volkner

and Werners 2002). More flexible technologies are therefore needed to coordinate

decision processes.

A framework called D2P has been developed to support decision processes in

organisational contexts (Oquendo et al. 2000). The D2P model represents the

decision making process at a high level. Its role is twofold: it prescribes how to take

well-researched decisions but it also describes how decision makers have actually

taken a decision (when the model is executed, it can evolve to reflect the way that a

decision process has unfolded).

In order to capture, analyse and execute complex decision making behaviour, we

have translated the framework into an enactable model that is implemented in

ProcessWeb (Warboys et al. 1999). ProcessWeb is a process support system that was

adopted for its capability to support complex processes and for its distributed Web-

based user interface. The system implements process models that are subject to

change and evolve over time.

We have explored the role of D2P in a range of settings. Previous work

investigated the use of D2P as a mechanism for understanding and influencing the

management control process within organisations (Papamichail and Robertson

2005). We have also explored the role of D2P in supporting societal decision

making (Papamichail and Robertson 2003, 2004) and e-tendering processes

280 K. N. Papamichail, I. Robertson

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(Mohamad Noor et al. 2006). The next step is to use D2P to model a real-life

decision making process.

The concept of distributed decisions is of particular interest (Barthelemy et al.

2002). Information and Communication Technologies do not require decision

makers to be ‘statically located’ and have dramatically changed the nature and

process of decision making. This work examines the capability of D2P to adapt at

run-time in order to support distributed decision processes that involve various

participants and are subject to change. A case study is used to demonstrate the

applicability of our approach. The case study describes a decision process in a not-

for-profit organisation. This decision had to be arrived at within a specific time

frame and implementation also took place within a specific period.

The setting of the decision is a UK higher education institution. From time to

time, institutions are invited to submit bids for specific allocations of funds by their

principal funding council HEFCE (Higher Education Funding Council for England).

In responding to such requests for proposals, the institutions must identify an

individual to bring the action forward, formulate a response from identified

possibilities, and negotiate (to a greater or lesser extent) its acceptance among

concerned members of staff. The proposal, if accepted and successful in providing

funds, must also be capable of being implemented. In general, such responses are

undertaken over relatively short periods of time, making them useful for carrying

out longitudinal studies.

Of particular interest are the different models that are needed to convey

understanding of decision processes. Several modelling techniques have been

employed in this study to describe and view the HEFCE decision process (thereafter

referred to as HEFCE 00/56) from different perspectives. Some of these models can

be executed (or enacted) in order to support inherently complex human behaviour.

A core property of the models is that they are evolvable, that is, they are able to

support self-adaptation to a certain degree.

Unlike other studies that attempt to identify patterns in decision processes that

lead to successful decisions, the aim of this work is to help decision makers become

more competent at taking decisions through their understanding of the decision

process. Process support tools are employed to help actors analyse existing

processes and explore road maps, i.e. methods for creating new and more efficient

decision processes.

The structure of the paper is as follows. A review of approaches to modelling

decision processes is given in Sect. 2. Section 3 discusses our approach to

modelling decision processes and introduces a generic model whose purpose is to

support the decision-making process in organisations. The models used to analyse

the decision problem of our case study are described in Sect. 4. The relationships

between the different models of the process are discussed in Sect. 5. Section 6

describes the technology used to execute the model and Sect. 7 discusses our case

study and the implemented model. Section 8 highlights the relevance of the work to

researchers and practitioners. It is followed by the conclusions of the study in

Sect. 9.

Supporting distributed decision processes 281

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2 Modelling decision processes

Organisational decision processes are complex phenomena and it is not always

possible to track them down and identify the points in time and space where

decisions were taken. Langley et al. (1995) refer to the case of a car manufacturing

company that hired consultants to investigate the introduction of a new model of a

car. However, it was difficult to determine who decided, what, where and how.

Various departments were involved in the process and after several very complex

decisions and actions the new model was produced.

Several contemporary descriptions of decisions are narrative text (e.g. Argyres

1999). This is probably because of the complexity of situations in the real world.

However, this approach cannot be used to define support for real world processes

mainly because such processes are very complex and natural language is

insufficiently rigorous. In other studies, examples from practice are used to support

theoretical and methodological arguments. Rich narratives and case studies are

viewed as two popular approaches for enhancing debate and learning about OR

applications (Keys and Midgley 2002).

Pidd (1999) states that ‘a model is an external and explicit representation of part

of reality as seen by the people who wish to use that model to understand, to change,

to manage, and to control that part of reality in some way or other.’ Various models

can be used to examine a decision process and enhance our understanding. These

models are often high-level descriptions of the actual process.

A range of modelling strategies such as visual mappings and grounded theory can

be used to make sense of process data (Langley 1999). Soft models act as sense-

making and interpretive devices that offer insight into how a process is being or

should be executed (Melao and Pidd 2000). Pidd (1999) gives a short review of

models and modelling and discusses several principles.

Modelling decision processes creates challenges such as deciding the level of

detail, scoping the study and determining the boundaries between patterns of

behaviour. Business process modelling (Warboys et al. 1999) is a key technology

for studying, representing and implementing business processes. It shows who are

the participants involved in a process, what activities they are undertaking and howthey interact together in order to achieve given goals. It is used in this study in order

to analyse, explain and enact the behaviour of a decision process.

Process modelling allows organisations to monitor, control and manage business

processes in real-time (Eastwood 2002). It helps people not only to redesign

processes but also invent new ones as well as share and communicate knowledge

about organisational practices (Malone et al. 1999). Process modelling tools increase

quality and predictability by standardising activities (Wreden 1998). Increased

explanatory and computational ease are additional advantages (Mackenzie 2000).

3 The approach

A decision process is a kind of transformation process where the transform activity

is to change an aspect of the real world from a state where there is a need or


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opportunity, but no means to deal with this situation (a ‘problem’), to a state where a

solution process has been identified. Subsequently, implementation of the solution

would normally lead to the original problem being ‘solved’.

Modelling of transformations can be done with Checkland’s conceptual models

(Checkland 1981; Wilson 1984), identifying activities that contribute to the

transformation and the dependencies between them. Such dependencies are usually

information flows. The diagrammatic representation of the model can also indicate

external information flows and sources, and indicate those information flows that

serve as control actions.

Generic models are the typical published models—a graphic indicating

significant activities connected by edges that depict dependency or information

flow. They generally exclude any information as to how they may be adapted to

illustrate a real-world decision process.

So far one generic process support model called D2P (Decisioning for Decision

Support in Processes) has been developed (Oquendo et al. 2000; Papamichail and

Robertson 2005). This illustrates a model that has been refined and implemented in

a technology suitable for supporting the decision process. It supports evolution in

that the methods for carrying out tasks can be substituted one for another using an

evolvable framework. Such a model does not attempt to prescribe a certain pattern

of behaviour. It is intended to support activities that can reasonably be considered in

this context.

The architectural model of D2P is shown in Fig. 1. Once a decision opportunity

or threat is identified (in ‘doing’), the D2P model is instantiated. Decision making

behaviour is then decomposed in the following phases:

Evaluating

Appraising

Formulating

Enacting Operational

Process

Information flow

Change

Levels Decisioning Doing

List of alternativesand objectives

Refined list of alternativesand objectives

Ranked list of alternatives

Refined decision model

Implementalternative

Fig. 1 Architectural model of Decisioning for decision support in processes


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• Formulating. The decision problem is formulated and structured. Stakeholders

are invited to contribute their input and identify the main issues of the problem.

Decision actors devise alternative strategies and determine the main factors that

drive decision making.

• Appraising. Those alternatives and objectives that have been identified in the

Formulating phase are reviewed. Chief decision makers appraise the formulation

process and decide how to proceed. They may suggest other alternatives and

objectives before they initiate the Evaluating phase. They may be satisfied with

the results of the Formulating and/or Evaluating phases, decide a course of

action and implement their action plan. Finally, they may be unsatisfied with the

Formulating and/or Evaluating results and re-instantiate the decision process.

• Evaluating. This may include a cost-benefit analysis of those alternatives that

are under consideration, a thorough and systematic assessment using multi-

criteria decision analysis techniques or an evaluation facilitated by the use of

decision aiding technology.

Conceptual and generic models can be used to enhance understanding of

activities, their sequence and dependencies. Neither of the above models can,

however, identify the actual progression through a process and for this a timeline

diagram can place events in perspective, and identify where iterations have taken

place.

Irrespective of the models employed, we have identified a number of properties

that we believe should be captured and analysed when studying decision processes:

• Purpose of taking a decision and striving to achieve some given goals.

• Stakeholders with an inherent interest in the decision taken and possibly affected

by the outcome of the decision.

• Participants involved in the decision process. One or more participants, called

chief decision maker(s), might be responsible for taking the ultimate decision.

• Responsibilities of the decision participants and expected behavioural patterns.

• Activities undertaken to achieve some given goals.

• Temporal progression of the process, i.e. how the decision process unfolds.

• Dependencies among activities or behavioural patterns.

• Iterations of decision steps.

• Factors influencing the process.

4 Modelling a real-life decision process

HEFCE 00/56 was a consultation process initiated in 2000 by the Funding Council

followed in early 2001 by an invitation to bid for funds. The process modelled was

the series of activities set in train in order to construct and submit a credible and

implementable response.

The initial activity was to allocate the task to a senior member of staff. This was

not difficult as the scope of the request fell almost entirely within one functional

area of the organisation. There were initial presentations to members of senior


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management and subsequently the activity consisted of identifying areas within the

scope of the request that would benefit from an infusion of funds with results that

would again fall within the scope of the request. A concern was that a commitment

to undertake an improvement in an area could be implemented and the benefits

measured.

Of course there are invariably decisions about decisions and these aspects were

not modelled although they had been considered in model development. Three

models were necessary to obtain a clear understanding of the process as it took place

and how it might be supported. They were a system conceptual model, a timeline

model, and an active model.

The conceptual model is shown in Fig. 2. It is an easily understandable model

that indicates state transitions, dependencies between transitions, as well as

stakeholders and other interactions with behaviours in the system environment. It is

based on Checkland’s models and his Soft Systems Analyses (Checkland 1981;

Wilson 1984). By virtue of the fact that it is easily understandable it is a useful

vehicle for developing other models. The model exhibits the following decision-

making properties:

• Stakeholders

• Participants

• Activities

• Dependencies

• Iterations

• Factors influencing the process

The Timeline model is illustrated in Fig. 3. This is a model of an actual example

of the process, and indicates the sequence of certain activities or events that took

Fig. 2 Conceptual model of HEFCE 00/56 decision process instance


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place, and the extent to which the process had to be iterated over before an outcome

was arrived at. The model highlights the following decision-making elements:

• Activities

• Temporal progression

• Dependencies

• Iterations

The active model (Fig. 1) is a generic model that supports decision processes. It

is active in the sense that it can be implemented in a technology (see Sect. 6 and 7).

The concern here is to have a succinct and reusable model that is less conducive to

easy understanding. It represents:

• Participants

• Responsibilities

• Activities

• Temporal progression

• Dependencies

5 Relating the models one to another

The relationship between the timeline and conceptual models is clear. The

sequences that are identified in the timeline model must be logically possible in the

conceptual model. Where an activity or an event is mentioned in one but not the

other is usually explained in terms of significance in the context. For example, the

activity ‘solicit views’ is implicit in the timeline model but it is explicitly

represented in the conceptual model because it highlights an important behavioural

pattern.

The relationship between the conceptual model and the active model is more

complex, in that we know from the outset that, because the active model is generic it

can only support the instance of the decision process illustrated after having been

adapted. D2P represents decision-making activities that are likely to occur at a high-

level of abstraction. Decision-makers, however, might skip decision steps.

Meetingwith UCEA

ProduceHEFCEreport

Produceproposal

Meetingwith Deans

MeetingwithDeans

Write report

MeetingwithSMT

Meetingwith PC

MeetingwithCouncil

MeetingwithTU

Revise report

UCEA - University Continuing Education Association

TU - Trade Unions

PC - Personnel Committee

SMT - Senior Management Team

Sendreport to HEFCE

t

Fig. 3 Timeline model of HEFCE 00/56 decision process instance


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Therefore, the actual decision process as represented by the conceptual model is a

specialisation or adaptation of the D2P. Any time a decision process is instantiated,

the active model, which is essentially an executable D2P instance, needs to adapt in

order to support the process.

Adaptations must take place in two dimensions. The first is in the detailed model

that defines behavioural support for D2P operations, and the second is in the

insertion of D2P models where decisions are needed within the decision process, i.e.

a kind of meta-decisions: decisions about aspects of the decision process itself. This

is the normal situation that we cope quite well with in our day-to-day activities.

In our case study, decision-making behaviour can be decomposed into the

following phases (see Figs. 1, 2):

• Formulating. This is the generation of alternatives. The core of the response was

determined by identifying where the request coincided with initiatives that were

already a part of the university’s strategic plans. Once this was identified,

consideration was given to what activities could be undertaken in order to

address the remaining aspect of the 00/56 request. This consisted of soliciting

views from the community at large, and, more specifically, interacting with pro-

active stakeholders. The stakeholders included members of the university’s

senior management team, the Personnel Committee and particularly the Deans

of Faculties representing the academic membership of the university.

• Appraising. Appraising is initially a refining activity—testing the adequacy and

feasibility of alternatives generated in Formulating and possibly extending them.

The conventional Appraising is comprised of two parts: one dealing with the

transfer of the decision model to Evaluating, and the other dealing with taking

the ranked list of alternatives from Evaluating and either implementing one of

them or returning the decision model to Formulating for cycling again. In this

study, one alternative was iteratively negotiated with the stakeholders so that at

the end there was no need to defend it. Therefore, the focus was placed upon

refining the previous draft of the solution rather than refining a list of

alternatives. In fact there was a cycling between ‘Formulating’ and ‘Appraising’

of the D2P model. This can be supported by the active model by skipping the

‘Evaluate’ activity until it is really needed and utilising the ‘refined decision

model’ feedback link to Formulating.

• Evaluating. This is conventionally the behaviour of ranking the alternative

solutions in terms of participants’ values and weighting. In the 00/56 context, the

activity here was one of testing the adequacy of the draft proposal with regard to

the requirements of 00/56 and the perceived needs of the university. If the test

failed, the decision model had to be refined, and it was returned to Formulating

and Appraising.

6 The technology

D2P is a generic role model of the decision process that can be implemented in a co-

ordination technology, a technology that facilitates co-ordination among users in an


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organisational context. It is an active model, which means that, when executed, the

system prompts users for their contribution to the process at the appropriate point. It

thus effectively passes control of the process between users to progress the process

to a conclusion. The conclusion in this case is the identification (and rationale) of an

alternative (i.e. a potential solution) which is deemed to be ‘best’ for dealing with

the stated problem.

The technology is ProcessWeb (Warboys et al. 1999), which is characterised by

its persistence, and the facilities that it provides for run-time evolution of

implemented models. It is a process support system designed to work across the

World Wide Web. Users can access the system through their Web browsers and

enter data or submit queries to check on the status of the enacted process. Any time

the state of the process changes, the system propagates the changes and the user

displays are updated to reflect the change.

ProcessWeb provides a concise expression of the pattern of activities nominally

required to arrive at a decision by choosing amongst alternatives. For example,

during a decision analysis process, alternatives need to be evaluated. Depending on

the evaluation method used, the alternatives can be scored against criteria such as

quality, implementation time, priority and cost.

A feature of ProcessWeb, which makes it very suitable for experiments on

decision processes, is its ability to evolve at run-time. This means that the pattern of

activities that are supported can be changed whilst decision-makers are interacting

in certain activities. The final steps of a process do not have to be established until

just before they are needed.

7 The implemented model

The implemented computer model was based on the earlier version (Oquendo et al.

2000) developed in the PIE project (PIE 2001) and was extended to make it capable

of supporting the case study process. There were two main areas of difference:

1. The HEFCE case study did not have, as its main task, the choosing among

alternative responses to the HEFCE request. The broad structure of the response

was accepted by all parties, and the task in hand was to best shape this response

so as to maximise benefit to the institution and to maximise likelihood of it

being accepted by HEFCE. In the former aspect, this was to align it as far as

possible with existing strategies, and in the latter aspect to ensure that all the

constraints imposed on their funding were met. This was achieved by a process

of negotiation with the principal stakeholders, the Deans, who were represented

on the Senior Management team.

2. There was no ‘ranking of alternatives’. Once that approach had been negotiated,

the choice for the management team was to proceed, or not to proceed, with the

bid as prepared. Final approval of the bid was the responsibility of Council, a

senior committee of the university.

The additional support was provided by adapting the original model such that it

could support decisions that involved the choosing among alternatives, or decisions


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that involved the development of a unique solution. In our case study (see Sect. 4),

the chief decision maker was the human resource manager of a large higher

education organisation who had to put together a bid for funding. His aim was to

devise a detailed human resource management strategy and submit a bid. If

successful, he would obtain additional funds that would allow him to implement the

devised strategy. The main task in this effort was to decide on funding percentages,

i.e. to explain how the funds would be distributed to support initiatives such as

recruiting highly skilled staff, improving retention levels and increasing salaries of

staff on low income. In order to justify the percentages of funding, he invited

stakeholders (e.g. the Deans and the Senior Management Team) to comment on and

contribute to his proposals. He was constrained however, by the amount of time he

could spend on the preparation of the bid as he had to meet the submission deadline.

The decision process in our case study starts with the chief decision maker

becoming aware of the opportunity to obtain further funding and devising a draft bid

that includes funding percentages. He logs into ProcessWeb using login id and

password facilities (Fig. 4) and initiates an instance of the D2P process model. He

assigns himself to the Appraising role and sends the draft bid to those actors that are

responsible for formulating the problem, i.e. those assigned to the Formulating role.

The ‘Formulating’ role actors receive notification that a draft proposal has been

submitted and login to the system. Only those parties that have been assigned to the

Formulating role (i.e. Personnel Committee members, Senior Management Team

members, Trade Union representatives and the Deans) can submit their views

through the system. They essentially have to review the draft proposal and suggest

criteria, e.g. cost of implementing the proposed strategy and quality of proposal. The

user interface (see Fig. 5) gives them the flexibility of proposing new alternatives

for comparison (even though this activity did not take place in our case study). It

should be noted that other users (e.g. the human resource manager) can check on the

status of the process and indentify which parties may be causing delays but cannot

interact with the Formulating user interface.

Fig. 4 The login interface of ProcessWeb


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Once all the interactions with the stakeholders have been completed, the human

resource manager is notified. He connects to ProcessWeb and views the results of

the consultation process on the Appraising user interface (Fig. 6). As the chief

decision maker, he can still make changes and delete or add new criteria such as

‘priority’, i.e. how well the proposal meets the priorities set by the funding body. He

is then able to make one of four choices (see Fig. 1): Firstly, if he is happy with the

appraisal, he can submit the final draft, complete the ‘Decisioning’ process and

return to ‘Doing’. Secondly, he can submit the proposal for evaluation. Thirdly, he

can initiate a further consultation cycle by returning control to Formulating and

inviting stakeholders to resubmit their views. Fourthly, he can have the proposal

appraised by someone else.

In our case study, the human resource manager is focused on incremental

revisions of his bid rather than devising alternative proposals and conducting a

thorough evaluation of the alternative bids. Therefore, the evaluation decision step

was implicit. The implemented D2P model, however, is prescriptive. It offers the

possibility of thoroughly assessing alternatives and it is up to the decision actors

whether they would like to do so. This illustrates the point made in Sect. 5 that an

actual decision process is an adaptation or specialisation of the D2P.

There are two options in the ‘Evaluating’ role: a voting facility (yes/no, with or

without comments, majority/unanimous voting) or a ranking system connected to a

library of multi-criteria decision analysis models (currently populated with a multi-

attribute value theory model). The two options appear in Fig. 7 and 8, respectively.

In Fig. 7, the human resource manager opts for the voting facility and assigns

stakeholders/actors to the Evaluating role. These decision actors are given the

choice of approving the main parts of the proposal. If the bid is approved by the

majority of them, a message is sent to the human resource manager (assigned to

Appraising) who can then proceed with the submission of the bid. If the proposal is

not approved or the chief decision maker is not happy with some aspects of the

decision process, the D2P cycle is repeated.

Fig. 5 The Formulating user interface


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The second option in the Evaluating role is to rank alternatives. For example, if

the decision actors suggested alternative strategies, the Evaluating user interface

would look like in Fig. 8. Whoever is assigned to Evaluating, for example the chief

decision maker in consultation with a decision analyst, would then have to score the

alternatives (on a scale from 1 to 100) and decide the weights of the criteria (i.e.

cost, time, quality). A multi-attribute value function would be used to rank the

alternatives.

After the completion of Evaluating, the results of the voting/ranking process are

then sent to the actor(s) assigned to the ‘Appraising’ role and displayed on their

Web pages when connected to ProcessWeb. A future plan is to explore the

capability of D2P to invoke external decision aiding tools and display their outputs

Fig. 6 The Appraising user interface

Fig. 7 The Evaluating user interface (voting system)


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on ProcessWeb. In our case study, the final step is to have the decision approved by

the Council and complete the D2P process.

8 Relevance to researchers and practitioners

The aim of this work is not to aid decision makers in taking better decisions, but

rather to help them become more competent at taking decisions through their

understanding of the underlying process. Process-support technology has been used

for representing decision processes with the aim of improving decision-making

practices. Decisions of particular interest are those that are taken over a period of

time. These decision processes are often distributed, heterogeneous and subject to

evolution because of the ever changing organisational environment.

This paper describes D2P, a framework designed to coordinate distributed

decision processes and implemented using Web-based process support technology.

The setting is the formulation of a human resource management strategy for

retaining and training staff in a not-for profit organisation. We believe the work is

relevant to researchers and practitioners who are interested in modelling decision

processes and developing decision support technologies that coordinate complex

and distributed decision processes which evolve over time. It is of particular interest

to managers that are trying to increase acceptability and trust in organisational

Fig. 8 The Evaluating user interface (ranking system)


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decisions by making the underlying decision processes transparent and consistent as

well as encouraging stakeholders to participate in the process.

The HEFCE case study allowed us to demonstrate how to map and execute a

longitudinal decision process in a real-life setting as well as explore the validity and

utility of D2P. Along the lines of other studies (Mintzberg et al. 1976; Nutt 1984;

Hickson et al. 1986), we found that decision makers skip or iterate decision steps

and do not follow a well-structured process. The HEFCE decision process was

found to be a specialisation of the D2P model. Therefore, the D2P model can

represent decision processes at a high level but when enacted, it can adapt to reflect

the actual decision process.

Several models of decision making have been suggested in the literature (see for

example Simon 1960; Pounds 1969; Keeney 1982; Holtzman 1989; Pokras 1989;

Couger 1995; Altier 1999; Shim et al. 2002). What differentiates D2P from such

models is that it is executed using process support technology and adapted at run-

time to reflect changes in the process. It should be noted that this work is intended to

make a contribution to the area of decision modelling and decision support rather

than the area of computer-supported cooperative work. A wide range of Web-based

workflow and process-centred systems (Fuggetta and Ghezzi 1994) have been

developed over the years to support teamwork (Ambriola et al. 1997). D2P is a

specialised process-centred system that coordinates distributed decision processes

that involve multiple decision makers and stakeholders.

There has recently been interest in the development of knowledge repositories

that codify contextual information. KnowledgeScope (Kwan and Balasubramanian

2003) and KOPeR (Ramesh et al. 2005) are two knowledge-based systems that use

process support technology to facilitate knowledge sharing and access to a

repository of solution options and process templates. D2P can capture contextual

knowledge as the decision making process unfolds. It can be used to codify and

retrieve contextual decision making knowledge such as who was responsible for a

decision making task, when and how they contributed to the process and what was

the reasoning behind their actions. In the long run, this could help decision makers

to access and codify good practice in decision making.

WOODSS (Pinto et al. 2003; Medeiros et al. 2005) is the only other Web-based

decision support system we have come across that uses workflow technology to

capture and codify user interactions. These are stored in a repository of evolvable

and executable process elements to help decision makers synthesise alternatives.

The process engine executes and dynamically updates decision processes as well as

coordinates actors. The main strength of the executable D2P over other decision

support systems is that it offers prescriptive advice by encouraging decision makers

to follow certain decision steps and thoroughly explore the decision problem. It

assists distributed decision actors throughout all the phases of decision analysis and

implementation including the formulation, evaluation and appraisal of a decision

model. Its main weakness is its user interface that is not as sophisticated as that of

other workflow based tools.

In order to determine the attitude of potential users towards D2P, we have

demonstrated the model and received qualitative feedback through discussions. The

subjects of our study felt that the D2P enhances learning by facilitating


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understanding of the decision content, context and process. It extends organisational

memory by codifying knowledge in the form of problem solving strategies and

information about the decision problem.

Potential users of D2P range from expert decision makers, facilitators and

decision analysts to novices that need guidance through the decision process. We

believe that D2P appeals to those managers that would like to exercise control over

the decision process and the type of knowledge codified. Some subjects stated that

D2P is best suited to organisations with hierarchical structures in which decisions

are taken at different levels and multiple decision makers are involved in different

stages.

The active D2P model can be used to invite actors to participate in the decision

process at given decision points or elicit the views of stakeholders. This is of

particular importance given that in the public sector, there is currently the need to

involve stakeholders when devising public policy while in the private sector,

shareholders increasingly demand to be involved in taking key decisions. This

feature coupled with the ability to map decision processes as they unfold makes D2P

best suited to organisations with a learning culture that encourage and support

knowledge sharing and distribution.

9 Conclusions

A theoretical framework called D2P has been used to support and coordinate

decision processes. The framework has been translated into a formal model that can

be executed by a process support system. This section discusses the potential and

limitations of the D2P model and process support technology.

The D2P was developed as an attempt to model a generic decision process. How

successful it was can only be determined in using the model in a variety of different

contexts. This article describes a decision process carried out in a not-for-profit

organisation and is one such context.

The models used in the study perform very different and complementary

functions. A timeline model gives an indication of the significant events (i.e.

changes of state of the decision process) but does not indicate behavioural

dependencies. This is provided by the conceptual model which, however, suffers

from offering no temporal indications or of the coordination that actually makes it

happen. This brings us to the third model—the active model. This defines

coordinations and a general route through the process but offers the participants the

possibility of tailoring the process to suit their own needs.

Because it supports self adaptation, the potential of the model is constrained

solely by the interpretations put on this by the model developers, and by the

availability of suitable methods to address the needs of the participants. One aspect

of the model which has not been exploited is the ease with which it could interact

with external tools. This was demonstrated in an earlier project, however, now the

potential exists for suitable methods, or even algorithms, to be furnished by a

method provider, or even run by the methods provider and the results made

available to the decision makers. Such methods could be provided via web services.


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The D2P is a research vehicle and is not itself intended for or suitable for use as a

tool of general application. It does, however, provide a template for commercial

exploitation.

Cascading decisions is an aspect of decision processes that has never before been

supportable using contemporary technologies. However, some decision points in the

process often involve taking other decisions. D2P offers the possibility of support at

any level in the process: wherever it is needed.

The primary drawback to this technology is its experimental nature. It is not yet

sufficiently intuitive to use, requires a high level of user application to master it

(which individuals might be reluctant to commit in what might be a time-limited

decision), and the library of methods is still quite primitive.

Societal problems are almost invariably complex and encompass power,

legitimacy and urgency structures (Liebl 2002). There is no mechanism in this

model to address social and political issues and support one form of power structure

over another, or of attempting to elaborate on the ‘why’s’ of an actual decision

process. The authors believe that, in the first instance, behavioural support is itself a

major challenge without yet addressing political support.

Human behaviour is, to a large extent indeterminate. The goals and motivations

that are observed may or may not accord with reality. There is clearly the need for

IT to be embedded in human activity. The aim of technology, however, is to support

that activity that can benefit from IT support, and not to hinder that insightful,

imaginative, and purposeful aspect of human behaviour which contemporary

technology is ill-equipped to deal with.

Acknowledgments We would like to thank all those individuals who willingly set aside their time to

enlighten us about the HEFCE 00/56 decision process and also to participate in interesting discussions

about the decision-making practices within their organisation. We would also like to acknowledge the

support of our colleagues. In addition, special thanks are due to Melvin Loh who contributed to the

implementation of the active model. This work was funded by the Research Support Fund (University of

Manchester). Ian Robertson sadly passed away before this article was published. Nadia Papamichail is

grateful for his insightful discussions and wise comments. He was a great man, a trustworthy friend and

an extraordinary colleague. Trained as civil engineer, he worked for several years in the Middle East

before being appointed as Research Fellow in the School of Computer Science, University of Manchester.

He was an active member and representative of the Association of University Teachers (Manchester

University branch) and an elected local Councillor for the Rochdale Metropolitan Borough Council in the

area of Greater Manchester. Ian’s motto in life was ‘what is popular may not be right and what is right

may not be popular’. He will be sadly missed and fondly remembered by all his colleagues.

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Supporting distributed decision processes using an evolution model