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Interpreting Overlaps in Business Process Mapping via Organisational Soft Knowledge Flows
Abstract
Knowledge Management (KM) as the term implies, is broadly about improving knowledge use within an organisation. At a lower level, Business Process Management (BPM) is the set of management activities related to business processes that can ideally be arranged in a life cycle. Social Network Analysis (SNA) is a technique enabling the researcher to better understand interactions between people. Relatively little research has been conducted with regard to the crossover of social networks and workflows, with the aim of examining workflows as management views them, as opposed to the actual social interactions of staff. Improvements in the overlay of management interpretations of work and real social networks could potentially lead to improvements in business process efficacy. In this study SNA diagrams are examined in order to implement executable models and potentially enable automated analysis of workflows. A means of converting SNA data to Business Process workflows is presented and an example provided.
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Power no longer resides exclusively (if at all) in states, institutions, or large corporations. It is located in the networks that structure society. Social network analysis seeks to understand networks and their participants and has two main focuses: the actors and the relationships between them in a specific social context.
Modern organizations are investing in organizational process coordination tools such as collaboration support systems and workflow management systems for better decision-making and business process execution. However, these systems are deployed in a standalone manner with the result that business processes that span these systems are highly fragmented. Work processes are designed and managed independently for each system, resulting in large administration overheads to coordinate activities in business processes that use these systems. Lack of a structured approach to modeling and designing collaborative work processes has been attributed as a primary reason for this disconnect. In this regard, this paper reports on the advances in the area of Collaboration Engineering and its applicability in designing collaborative workflows that can lead to a unified approach for designing organizational processes consisting of interleaved individual and collaborative tasks. The paper also motivates the need for an interface between the workflow activities and the more detailed collaboration support prescriptions.
Workflow management,is a core component,of modern,enterprise information technology infrastructure that au- tomates the execution of critical business processes. Since enterprise transformation typically introduces changes,to the corresponding business processes, it is important for modern workflow management systems to provide effective support for seamless incorporation of these changes. In this paper, we examine a collection of selected workflow concepts and techniques that are significant for dealing with transformational changes. Especially, we will focus on notions and techniques that are directly relevant to enterprise transformation, such as workflow patterns, workflow adaptation, and workflow data mining and merging. We also include a short summary of business process management, the fundamental concepts of workflow management, and a discussion of workflow support for enterprise transformation to keep the paper self-contained.
Process mining is the systematic analysis of the information contained in an event log, which is a data set constructed from the information recorded in modern IT systems. That data consists of both information entered by users, and meta-information about that transaction, such as data stamps and user identity. Critically, meta-information is automatically recorded by the system, beyond the control of the user to manipulate or prevent recording, which makes event logs valuable control tools. Moreover, event log data are so rich that numerous modes of analysis can be conducted on it, yielding many different insights into underlying business processes. Process mining has been widely researched in computer science and management science, as well as adopted in industry with the support of leading high tech companies. This paper provides AIS researchers with an introduction to process mining, a primer on how it is undertaken, and a discussion on why it can add value to both accounting research and practice.
There is little evidence that current BPM deployments deliver significant return on investment (ROI), as most deployments
are small-scale and tactical rather than enterprise-scale and strategic. Further, BPM/Service-oriented Architecture (SOA)
deployments pose a business risk, as the necessary new management techniques are not yet well understood. The routine processes
amenable to application of current BPM techniques must be integrated with high-level management work, knowledge work, and
sectors in which human activity is critical. We present a means of describing collaborative, adaptive human-driven processes,
and optionally supporting them with software, so as to increase individual productivity, improve organizational memory, and
align human work more closely with organizational goals. A framework is provided by the theory of Human Interaction Management
(HIM). HIM facilitates the management of teams, communication, knowledge, time, and plans. HIM also shows how to automate
processes involving human collaboration, even those of cross-organizational boundaries. Introduction of HIM into the enterprise,
as well as its integration with both organizational strategy and mainstream BPM, is via an associated methodology, Goal-Oriented
Organization Design (GOOD).
Business Process Management seeks to do just as its name suggests. As with many management approaches, improvements can made through analyzing at varying levels how processes are actually undertaken compared to how management may think they are being done or vice versa. One novel way business process management may be improved is through the use of Social Network Analysis to observe actual working relationships among employees. If we are able to ascertain who is working with whom in practice, as opposed to how we may think they are, we have a means of either reconstructing workflows or alternatively employee practices, to name but a couple of approaches. Ultimately it is not unreasonable to consider such improvements as aiding in the knowledge management of the organization as a whole.
Increasingly information systems log historic information in a systematic way. Workflow management systems, but also ERP, CRM, SCM, and B2B systems often provide a so-called "event log", i.e a log recording the execution of activities. Unfortunately, the information in these event logs is rarely used to analyze the underlying processes. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs. This paper focuses on the mining social networks. This is possible because event logs typically record information about the users executing the activities recorded in the log. To do this we combine concepts from workflow management and social network analysis. This paper introduces the approach, defines metrics, and presents a tool to mine social networks from event logs.
Social network analysis has gained significant attention in recent years, largely due to the success of online social networking and media-sharing sites, and the consequent availability of a wealth of social network data. In spite of the growing interest, however, there is little understanding of the potential business applications of mining social networks. While there is a large body of research on different problems and methods for social network mining, there is a gap between the techniques developed by the research community and their deployment in real-world applications. Therefore the potential business impact of these techniques is still largely unexplored.
In this article we use a business process classification framework to put the research topics in a business context and provide an overview of what we consider key problems and techniques in social network analysis and mining from the perspective of business applications. In particular, we discuss data acquisition and preparation, trust, expertise, community structure, network dynamics, and information propagation. In each case we present a brief overview of the problem, describe state-of-the art approaches, discuss business application examples, and map each of the topics to a business process classification framework. In addition, we provide insights on prospective business applications, challenges, and future research directions. The main contribution of this article is to provide a state-of-the-art overview of current techniques while providing a critical perspective on business applications of social network analysis and mining.
Workflow management promises a new solution to an age-old problem: controlling, monitoring, optimizing and supporting business processes. What is new about workflow management is the explicit representation of the business process logic which allows for computerized support. This paper discusses the use of Petri nets in the context of workflow management. Petri nets are an established tool for modeling and analyzing processes. On the one hand, Petri nets can be used as a design language for the specification of complex workflows. On the other hand, Petri net theory provides for powerful analysis techniques which can be used to verify the correctness of workflow procedures. This paper introduces workflow management as an application domain for Petri nets, presents state-of-the-art results with respect to the verification of workflows, and highlights some Petri-net-based workflow tools.
As its name suggests, Business Process Management seeks to manage the processes companies typically undertake on a day to day basis. In line with many management techniques, improvements can made through analysing at varying granularity how processes are actually undertaken compared to how management may consider they are being accomplished and vice versa. One innovative way Business Process Management may be improved is through the use of Social Network Analysis to observe actual working relationships among employees. This latter technique permits the workflow manager specifically to consider how well matched employees are to their workflow and as a result of this, we have a means of either reconstructing workflows or alternatively employee practices. A small research-in-progress case study is presented illustrating how these principles may be applied in practice. Overall one may consider such improvements as aiding in the knowledge management of the organization as a whole.
introduction to social networks, interesting the centrality chapter.
The recent progress of Business Process Management (BPM) is reflected by the figures of the related industry. Wintergreen Research estimates that the international market for BPM-related software and services accounted for more than USD $1 billion in 2005 with a tendency towards rapid growth in the subsequent couple of years [457]. The relevance of business process modeling to general management initiatives has been previously studied in the 1990s [28]. Today, Gartner finds that organizations that had the best results in implementing business process management spent more than 40 percent of the total project time on discovery and construction of their initial process model [265]. As a consequence, Gartner considers Business Process Modeling to be among the Top 10 Strategic Technologies for 2008.
Can models of collaboration serve as a foundation for development of collaborative technologies in much the same way that engineers use models when developing complex systems? We explore this issue by investigating how eight approaches to understanding or modeling collaboration could be used to improve technologies that support a change management process. Some approaches are ostensive, defining how collaboration should be achieved. These approaches provide ways of documenting, analyzing, simulating, and automating the process. Other approaches are performative, describing actual collaboration behavior. These approaches reveal the variability in collaboration and deviations from the intended process. Technologies could benefit from and facilitate both types of approaches by recording collaborative events for later analysis. We conclude by considering ways that modeling collaboration could contribute to requirements analysis, new collaboration capabilities, adoption, and maximizing benefit from technologies.
Resource allocation and scheduling are fundamental issues in a Workflow Management System (WfMS). Effective resource management in WfMS should examine resource allocation together with task scheduling since these problems impose mutual constraints. Optimization of the one factor is subject to the other constraints and vice versa. Thus, an ideal algorithm should take into account not only performance metrics of the infrastructure, such as the number of resources and their utilization, but also quality criteria such as the percentage of tasks undergone violation in their temporal restrictions. In this paper, we propose an innovative algorithm which jointly optimizes the two aforementioned contradictory criteria. The algorithm, called Resource Conflicts Joint Optimization (Re.Co.Jo.Op.), minimizes resource conflicts subject to temporal constraints and simultaneously optimizes throughput or utilization subject to resources constraints. To achieve the optimization, the two factors are formulated in a matrix form and the optimal solution is found by applying concepts of the generalized eigenvalue analysis. A rough outline of an agent-based architecture is proposed to achieve runtime integration of our algorithm into a functional WfMS, while experimental results under different load environments and tasks assumption reveal the superiority of the proposed strategy than the other conventional approaches.
The purpose of this paper is to build a fundamental framework of discovering and analyzing a workflow-based social network formed through workflow-based organizational business operations. A little more precisely speaking, the framework formalizes a series of theoretical steps from discovering a workflow-based social network to analyzing the discovered social network. For the sake of the discovery phase, we conceive an algorithm that is able to automatically discover the workflow-based social network from a workflow procedure; while on the other hand, in the analysis phase we apply the degree centrality algorithm to the discovered social network, which is one of the well-known social network analysis algorithms in the literature. Consequently, the crucial implication of the framework is in quantifying the degree of work-intimacy among performers who are involved in enacting the corresponding workflow procedure. Also, as a conceptual extension of the framework, it can be applied to discovering and analyzing degree centrality or collaborative closeness and betweenness among architectural components and nodes of collaborative cloud workflow computing environments.
This study demonstrates how social network analysis (SNA) theory supports the task of designing IT-enabled business processes by providing social network measures for evaluating alternative process designs. These measures offer better information for process designers who are faced with making IT investment tradeoffs, especially as the process design task is being undertaken. A seven step methodology is proposed, demonstrated with the help of two case studies showcasing the robustness and flexibility of SNA measures.
Computers play an integral part in designing, modelling, optimising and managing business processes within and across companies. While Business Process Management (BPM), Workflow Management (WfM) and Business Process Reengineering (BPR) have been IT-related disciplines with a history of about three decades, there is still a lack of publications clarifying definitions and scope of basic BPM terminologies like business process, BPM versus WfM, workflow, BPR, etc. Such a myriad of similar-sounding terminologies can be overwhelming for computer scientists and computer science students who may wish to venture into this area of research. This guide aims to address this gap by providing a high level overview of the key concepts, rationale, features and the developments of BPM.
Workflow management systems, a relatively recent technology, are designed to make work more efficient, integrate heterogeneous application systems, and support interorganizational processes in electronic commerce applications. In this paper, we introduce the field of workflow automation, the subject of this special issue of Information Systems Frontiers. In the first part of the paper, we provide basic definitions and frameworks to aid understanding of workflow management technologies. In the remainder of the paper, we discuss technical and management research opportunities in this field and discuss the other contributions to the special issue.
Part I. Introduction: Networks, Relations, and Structure: 1. Relations and networks in the social and behavioral sciences 2. Social network data: collection and application Part II. Mathematical Representations of Social Networks: 3. Notation 4. Graphs and matrixes Part III. Structural and Locational Properties: 5. Centrality, prestige, and related actor and group measures 6. Structural balance, clusterability, and transitivity 7. Cohesive subgroups 8. Affiliations, co-memberships, and overlapping subgroups Part IV. Roles and Positions: 9. Structural equivalence 10. Blockmodels 11. Relational algebras 12. Network positions and roles Part V. Dyadic and Triadic Methods: 13. Dyads 14. Triads Part VI. Statistical Dyadic Interaction Models: 15. Statistical analysis of single relational networks 16. Stochastic blockmodels and goodness-of-fit indices Part VII. Epilogue: 17. Future directions.