Process modelling success factors and measures

Business process modelling has gained widespread acceptance, particularly in

large IT-enabled business projects. It is applied as a process design and

management technique across all project lifecycle phases. While there has been

much research on process modelling, there has been little attention on 'how to'

conduct process modelling effectively, or on the evaluation of process modelling

initiatives and outcomes. This study addresses this gap by deriving a process

modelling success model that contains both the success factors (independent

variables) and success dimensions (dependent variables) of process modelling.

The study employs a multi-method approach, blending both qualitative and

quantitative research methods. The research design commenced with a

comprehensive literature review, which includes the first annotated bibliography

in process modelling research. A multiple case study approach was used to build

the conceptual process modelling success model which resulted in a model with

eleven (11) success factors (namely Modeller Expertise, Team Structure, Project

Management, User Competence, User Participation, Management Support,

Leadership, Communication, Modelling Tool, Modelling Language and Modelling

Methodology), two (2) moderating variables (namely Process Complexity and

Project Importance) and five (5) process modelling success dimensions (namely

Modeller Satisfaction, Model Quality, User Satisfaction, Model Use and Modelling

Impact). This conceptual model was then operationalised and tested across a

global sample, with an online survey instrument.

290 valid responses were received. The constructs were analysed seeking a

parsimonious, valid and reliable model. The statistical analysis of this phase

assisted in deriving the final process modelling success model. The dependent

variables of this model consisted of three (3) contextual success factors (namely

Top Management Support, Project Management and Resource Availability), two

(2) Modelling specific success factors (namely Modelling Aids and Modeller

Expertise), and two (2) moderating variables (namely Importance and Process

Complexity). The dependent variable; Process Modelling Success (PMS) was

derived with three (3) success measurement dimensions (namely Model Quality,

Process Impacts and Process Efficiency). All resulting success factors proved to

have a significant role in predicting process modelling success. Interaction

effects with the moderating variables (Importance and Process Complexity)

proved to exist with Top Management Support (TMS) and Resource Availability

(RA). A close analysis to their interaction relationship illustrated that Importance

(IMP) moderated the relationship between Top Management Support (TMS) and

Process Modelling Success (PMS) in a linear manner and that Process Complexity

(PC) moderated the relationship between Resource Availability (RA) and Process

Modelling Success (PMS), also in a linear manner.

This is the first reported study with empirical evidence on process modelling

success. The progressive outcomes of this study have been readily accepted by

the practitioner and academic community, with 16 published internationalrefereed-

conference papers [including best paper award at the Pacific Asian

Conference on Information Systems (PACIS 2004)], 2 journal publications, and

over 5 major industry presentations made upon invitation.