Elsevier

Decision Support Systems

Volume 48, Issue 1, December 2009, Pages 267-281
Decision Support Systems

Policy-Driven Process Mapping (PDPM): Discovering process models from business policies

https://doi.org/10.1016/j.dss.2009.08.006Get rights and content

Abstract

Analyzing business policies for discovering and validating business process models is a critical task in modern organizations, which is currently done in an ad hoc manner due to a lack of systematic methodologies. In this paper, we propose a novel methodology called Policy-Driven Process Mapping (PDPM) for extracting process models from business policy documents. Our research objective is to make process discovery from policy documents more systematic with fewer structural and semantic errors. To the best of our knowledge, PDPM is the first formal approach to discovering process models from business policies.

Introduction

Business policies enable the efficient management of an organization by defining the procedures and rules for its daily business operations [28]. Many of these business policies are used to specify some business processes, such as order fulfillment, product development, travel reimbursement, and cash handling. We refer to these business policies as process policies. For instance, a travel reimbursement policy may define that a reasonable exception request form must be submitted if a travel reimbursement form is submitted later than 60 days after completing the travel. This policy specifies the condition under which a submission task must be executed. In order to describe a business process, a great number of process policies need to be established.

Although process policies are in place in many organizations, they often do not completely match the processes actually conducted in the field due to imprecise, ambiguous, or incomplete process policies, and failure to update the policies as processes change [10]. Recently, many organizations have invested a great amount to revamp their business policies in order to comply with various regulatory requirements, such as Sarbanes–Oxley [7], [9]. At the same time, organizations also need to adapt their business processes to meet the various changes in the business environment to maintain competitive advantages. Those changes further escalate their incompatibility, which may lead to problems such as miscommunication between the management and employees, misunderstanding of enterprise processes across different functions, and potential internal control deficiencies [7], [12]. As such, discovering new process models from and validating existing process models with business policies are critical issues for modern organizations.

Process mapping has been adopted in companies as an effective technique to enable organizations to view their business system graphically at any level of detail and complexity [24]. Although many process mapping projects have successfully helped organizations achieve higher level of cross-functional collaborations and tangible cost reduction, traditional process mapping has been done in an ad hoc manner and tends to be resource-intensive and time-consuming due to the informal and ambiguous collection of process information [17], [29]. Different from the traditional process mapping approach, there has been research on applying formal methods and theories, such as linear programming [1], cost optimization [38], computational experiments [16], and probability theory [11], to generate process models. Although those analytical process mapping methods provide rigorous process extraction procedures, few applications of those approaches have been found due to their restrictive assumptions. In addition, none of those analytical approaches use business policies as their inputs, and therefore they cannot be directly applied to process discovery based on business policies. Therefore, there is an imperative need for advanced process development tools that can leverage business policies for process discovery and validation.

In this paper, we respond to this need by proposing an innovative methodology for systematic process model mapping from business policies, which we refer to as Policy-Driven Process Mapping (PDPM). As shown in Fig. 1, PDPM builds on both traditional and analytical process design methods and advocates a new way of discovering process models. More specifically, PDPM uses business policies as the inputs for process discovery and provides systematic guidelines for business analysts to efficiently leverage policy documents. To the best of our knowledge, this is the first systematic approach to the discovery of process models from business policies.

The rest of this paper proceeds as follows. In the next section, we present a case on travel reimbursement policies, which provides a conceptual foundation of our Policy-Driven Process Mapping (PDPM) approach. Then, we formalize the concepts of process policy and process map and discuss the details of PDPM procedure in Section 3. The PDPM approach is further demonstrated and validated in Section 4 via another case study and a prototype system. Related work is discussed in Section 5. Finally, we summarize our contributions and present our future research.

Section snippets

A case study on business process policies

In this section, we present a case study on the business policies for a major public university in the US and discuss the conceptual foundations of our Policy-Driven Process Mapping (PDPM) methodology. The business policy manual for the university is published online and is accessible to the public. The policy manual has nineteen sections covering various topics, such as accounting, finance, information systems, etc. For our case study, we focus on the “Travel Regulations” section, because

Policy-Driven Process Mapping methodology

In this section, we propose a Policy-Driven Process Mapping (PDPM) methodology to systematically construct process models from narrative process policies. We first give the definitions of process policy and process map. Then, we present a detailed PDPM procedure with mapping rules and algorithms. The travel reimbursement example is used throughout this section to illustrate the PDPM approach.

PDPM validation via case studies

In order to further validate the PDPM methodology, we conduct several case studies. Next, we present a case on product development in detail, summarize several additional cases, and discuss the lessons learned.

Related work

Identifying and analyzing existing organizational processes (a.k.a. AS-IS process models) is the foundation for any further process changes and improvements [20]. Process mapping refers to the methodologies and related tools that help organizations identify, understand, and improve their current AS-IS processes [17]. Existing process mapping methods can be classified as either mainly participative or analytical [29]. Participative approaches tend to obtain process information using traditional

Conclusions

In this paper, we proposed an innovative process mapping approach by means of systematic process policy analysis, which is referred to as Policy-Driven Process Mapping (PDPM). PDPM is a new process mapping methodology different from the existing participative and analytical process mapping methods by leveraging business policies for process discovery. We applied PDPM approach to five case studies to demonstrate its feasibility and developed a PDPM toolkit to facilitate the process mapping

Harry Jiannan Wang is Assistant Professor of Management Information Systems in the Lerner College of Business and Economics at the University of Delaware. He received Ph.D. in Management Information Systems from the Eller College of Management, University of Arizona, and B.S. in Management Information Systems from Tianjin University, China. His research interests involve business process management, workflow technologies and applications, and services computing. He has published several

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  • Cited by (0)

    Harry Jiannan Wang is Assistant Professor of Management Information Systems in the Lerner College of Business and Economics at the University of Delaware. He received Ph.D. in Management Information Systems from the Eller College of Management, University of Arizona, and B.S. in Management Information Systems from Tianjin University, China. His research interests involve business process management, workflow technologies and applications, and services computing. He has published several research articles in academic journals and conferences such as International Journal of Web Services Research, Journal of Information Systems and E-Business Management, Communication of the AIS, International Conference on Information Systems (ICIS), Workshop on Information Technologies and Systems (WITS), and Americas Conference on Information Systems (AMCIS).

    J. Leon Zhao is Head and Chair Professor in Information Systems, City University of Hong Kong. He was Eller Professor in the Department of Management Information Systems, University of Arizona before January 2009. He also taught previously at HKUST and College of William and Mary, respectively. He holds Ph.D. and M.S. degrees from the Haas School of Business, UC Berkeley, M.S. degree from UC Davis, and B.S. degree from Beijing Institute of Agricultural Mechanization. His research is on information technology and management, with a particular focus on workflow technology and applications in knowledge distribution, e-learning, supply chain management, organizational performance management, and services computing. Leon's research has been supported by NSF, SAP, and other sponsors. He received an IBM Faculty Award in 2005 for his work in business process management and services computing. Leon has been associate editor of Information Systems Research, IEEE Transactions on Services Computing, Decision Support Systems, Electronic Commerce Research and Applications, International Journal of Business Process Integration and Management, International Journal of Web and Grid Services, and International Journal of Web Services Research and is on the editorial board of Journal of Database Management. He has co-edited nine special issues in various IS journals. Leon has been chair or program chair for numerous conferences including the 5th International Conference on Design Science Research in Information Systems and Technology (DESRIST'10), the IEEE International Conference on Services Computing, Bangalore, India (SCC'09), the 2008 IEEE Symposium on Advanced Management of Information for Globalized Enterprises (AMIGE'08), the 2008 Arizona Exposium on Frontiers of Information Technology and Applications (FITA'08), the 2007 China Summer Workshop on Information Management (CSWIM'07), the 2006 IEEE Conference on Services Computing (SCC'06), the 2005 Workshop on Information Technology and Systems (WITS'05), and the 2003, Workshop on E-Business (WEB'03) among others. He has also served on many program committees in international conferences.

    Liang-Jie Zhang (LJ) is a research staff member (RSM) and program manager of application architectures and realization at IBM T.J. Watson Research Center. Currently, he leads the creation of Cloud Computing Open Architecture and associated application development technologies for the cloud. He is the worldwide leader of IBM's SOMA Modeling Environment (SOMA-ME), which is the model-driven SOA (Service-Oriented Architecture) solution design platform from IBM. He is also the worldwide co-leader of IBM's SOA Solution Stack (a.k.a. SOA Reference Architecture) project. He is the lead author of book “Services Computing” published in 2007 by Springer. He has published more than 140 technical papers in journals, book chapters, and conference proceedings. He has received 2 IBM Outstanding Technical Achievement Awards, 10 IBM Plateau Invention Achievement Awards, an Outstanding Achievement Award by the World Academy of Sciences, and an Innovation Leadership Award from Chinese Institute of Electronics. Dr. Zhang has 36 granted patents and 20 pending patent applications. As the lead inventor, he holds federated Web services discovery and dynamic services composition patents. He is the founding chair of IEEE Computer Society Technical Committee on Services Computing and IBM Research Services Computing Professional Interest Community (PIC). Dr. Zhang currently serves as the Editor-in-Chief of IEEE Transactions on Services Computing (TSC).

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