A framework for cost-aware process management : generation of accurate and timely management accounting cost reports

Organisations are constantly seeking efficiency improvements for their business processes in terms of time and cost. Management accounting enables reporting of detailed cost of operations for decision making purpose, although significant effort is required to gather accurate operational data. Business process management is concerned with systematically documenting, managing, automating, and optimising processes. Process mining gives valuable insight into processes through analysis of events recorded by an IT system in the form of an event log with the focus on efficient utilisation of time and resources, although its primary focus is not on cost implications. In this paper, we propose a framework to support management accounting decisions on cost control by automatically incorporating cost data with historical data from event logs for monitoring, predicting and reporting process-related costs. We also illustrate how accurate, relevant and timely management accounting style cost reports can be produced on demand by extending open-source process mining framework ProM.

A framework for cost-aware process management : cost reporting and cost prediction

Organisations are constantly seeking efficiency gains for their business processes in terms of time and cost. Management accounting enables detailed cost reporting of business operations for decision making purposes, although significant effort is required to gather accurate operational data. Process mining, on the other hand, may provide valuable insight into processes through analysis of events recorded in logs by IT systems, but its primary focus is not on cost implications. In this paper, a framework is proposed which aims to exploit the strengths of both fields in order to better support management decisions on cost control. This is achieved by automatically merging cost data with historical data from event logs for the purposes of monitoring, predicting, and reporting process-related costs. The on-demand generation of accurate, relevant and timely cost reports, in a style akin to reports in the area of management accounting, will also be illustrated. This is achieved through extending the open-source process mining framework ProM.

Profiling event logs to configure risk indicators for process delays

Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators(PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.

Turning event logs into process movies: animating what has really happened

Today’s information systems log vast amounts of data. These collections of data (implicitly) describe events (e.g. placing an order or taking a blood test) and, hence, provide information on the actual execution of business processes. The analysis of such data provides an excellent starting point for business process improvement. This is the realm of process mining, an area which has provided a repertoire of many analysis techniques. Despite the impressive capabilities of existing process mining algorithms, dealing with the abundance of data recorded by contemporary systems and devices remains a challenge. Of particular importance is the capability to guide the meaningful interpretation of “oceans of data” by process analysts. To this end, insights from the field of visual analytics can be leveraged. This article proposes an approach where process states are reconstructed from event logs and visualised in succession, leading to an animated history of a process. This approach is customisable in how a process state, partially defined through a collection of activity instances, is visualised: one can select a map and specify a projection of events on this map based on the properties of the events. This paper describes a comprehensive implementation of the proposal. It was realised using the open-source process mining framework ProM. Moreover, this paper also reports on an evaluation of the approach conducted with Suncorp, one of Australia’s largest insurance companies.

Linking business goals to process models in semantic business process modeling

Broad knowledge is required when a business process is modeled by a business analyst. We argue that existing Business Process Management methodologies do not consider business goals at the appropriate level. In this paper we present an approach to integrate business goals and business process models. We design a Business Goal Ontology for modeling business goals. Furthermore, we devise a modeling pattern for linking the goals to process models and show how the ontology can be used in query answering. In this way, we integrate the intentional perspective into our business process ontology framework, enriching the process description and enabling new types of business process analysis. © 2008 IEEE.

Business process performance mining with staged process flows

Existing process mining techniques provide summary views of the overall process performance over a period of time, allowing analysts to identify bottlenecks and associated performance issues. However, these tools are not de- signed to help analysts understand how bottlenecks form and dissolve over time nor how the formation and dissolution of bottlenecks – and associated fluctua- tions in demand and capacity – affect the overall process performance. This paper presents an approach to analyze the evolution of process performance via a notion of Staged Process Flow (SPF). An SPF abstracts a business process as a series of queues corresponding to stages. The paper defines a number of stage character- istics and visualizations that collectively allow process performance evolution to be analyzed from multiple perspectives. The approach has been implemented in the ProM process mining framework. The paper demonstrates the advantages of the SPF approach over state-of-the-art process performance mining tools using two real-life event logs publicly available.

Workflow simulation for operational decision support

Simulation is widely used as a tool for analyzing business processes but is mostly focused on examining abstract steady-state situations. Such analyses are helpful for the initial design of a business process but are less suitable for operational decision making and continuous improvement. Here we describe a simulation system for operational decision support in the context of workflow management. To do this we exploit not only the workflow’s design, but also use logged data describing the system’s observed historic behavior, and incorporate information extracted about the current state of the workflow. Making use of actual data capturing the current state and historic information allows our simulations to accurately predict potential near-future behaviors for different scenarios. The approach is supported by a practical toolset which combines and extends the workflow management system YAWL and the process mining framework ProM.

Predicting deadline tansgressions using event logs

Effective risk management is crucial for any organisation. One of its key steps is risk identification, but few tools exist to support this process. Here we present a method for the automatic discovery of a particular type of process-related risk, the danger of deadline transgressions or overruns, based on the analysis of event logs. We define a set of time-related process risk indicators, i.e., patterns observable in event logs that highlight the likelihood of an overrun, and then show how instances of these patterns can be identified automatically using statistical principles. To demonstrate its feasibility, the approach has been implemented as a plug-in module to the process mining framework ProM and tested using an event log from a Dutch financial institution.

Conceptual model linking knowledge management with organisational performance

Better management of knowledge assets has the potential to improve business processes and increase productivity. This fact has led to considerable interest in recent years in the knowledge management (KM) phenomenon, and in the main dimensions that can impact on its application in construction. However, a lack of a systematic way of assessing KM initia-tives’ contribution towards achieving organisational business objectives is evident. This paper describes the first stage of a research project intended to develop, and empirically test, a KM input-process-output framework comprising unique and well-defined theoretical constructs representing the KM process and its internal and external determinants in the context of con-struction. The paper presents the underlying principles used in operationally defining each construct through the use of extant KM literature. The KM process itself is explicitly mod-elled via a number of clearly articulated phases that ultimately lead to knowledge utilisation and capitalisation, which in turn adds value or otherwise to meeting defined business objec-tives. The main objective of the model is to reduce the impact of subjectivity in assessing the contribution made by KM practices and initiatives toward achieving performance improvements.

A near-to-far non-parametric learning approach for estimating traversability in deformable terrain

It is well recognized that many scientifically interesting sites on Mars are located in rough terrains. Therefore, to enable safe autonomous operation of a planetary rover during exploration, the ability to accurately estimate terrain traversability is critical. In particular, this estimate needs to account for terrain deformation, which significantly affects the vehicle attitude and configuration. This paper presents an approach to estimate vehicle configuration, as a measure of traversability, in deformable terrain by learning the correlation between exteroceptive and proprioceptive information in experiments. We first perform traversability estimation with rigid terrain assumptions, then correlate the output with experienced vehicle configuration and terrain deformation using a multi-task Gaussian Process (GP) framework. Experimental validation of the proposed approach was performed on a prototype planetary rover and the vehicle attitude and configuration estimate was compared with state-of-the-art techniques. We demonstrate the ability of the approach to accurately estimate traversability with uncertainty in deformable terrain.

Dimensions of business processes quality (QoBP)

Conceptual modeling is an important tool for understanding and revealing weaknesses of business processes. Yet, the current practice in reengineering projects often considers simply the as-is process model as a brain-storming tool. This approach heavily relies on the intuition of the participants and misses a clear description of the quality requirements. Against this background, we identify four generic quality categories of business process quality, and populate them with quality requirements from related research. We refer to the resulting framework as the Quality of Business Process (QoBP) framework. Furthermore, we present the findings from applying the QoBP framework in a case study with a major Australian bank, showing that it helps to systematically fill the white space between as-is and to-be process modeling.

No time for compliance

In the past few years several business process compliance framework based on temporal logic have been proposed. In this paper we investigate whether the use of temporal logic is suitable for the task at hand: namely to check whether the specifications of a business process are compatible with the formalisation of the norms regulating the business process. We provide an example inspired by real life norms where the use of linear temporal logic produces a result that is not compatible with the legal understanding of the norms in the example.

Testing a framework for the quality of process models: A case study

Process modeling can be regarded as the currently most popular form of conceptual modeling. Research evidence illustrates how process modeling is applied across the different information system life cycle phases for a range of different applications, such as configuration of Enterprise Systems, workflow management, or software development. However, a detailed discussion of critical factors of the quality of process models is still missing. This paper proposes a framework consisting of six quality factors, which is derived from a comprehensive literature review. It then presents in a case study, a utility provider, who had designed various business process models for the selection of an Enterprise System. The paper summarizes potential means of conducting a successful process modeling initiative and evaluates the described modeling approach within the Guidelines of Modeling (GoM) framework. An outlook shows the potential lessons learnt, and concludes with insights to the next phases of this study.

A Framework of Issues in Large Process Modelling Projects

As process management projects have increased in size due to globalised and company-wide initiatives, a corresponding growth in the size of process modeling projects can be observed. Despite advances in languages, tools and methodologies, several aspects of these projects have been largely ignored by the academic community. This paper makes a first contribution to a potential research agenda in this field by defining the characteristics of large-scale process modeling projects and proposing a framework of related issues. These issues are derived from a semi -structured interview and six focus groups conducted in Australia, Germany and the USA with enterprise and modeling software vendors and customers. The focus groups confirm the existence of unresolved problems in business process modeling projects. The outcomes provide a research agenda which directs researchers into further studies in global process management, process model decomposition and the overall governance of process modeling projects. It is expected that this research agenda will provide guidance to researchers and practitioners by focusing on areas of high theoretical and practical relevance.

Towards a framework for business process standardization

Organizations increasingly seek to achieve operational excellence by standardizing business processes. Standardization initiatives may have different purposes, such as process streamlining, process automation, or even process outsourcing. However, standardization of processes is easier said than done. Standardization success depends on various factors, such as existent IT capabilities, available standard frameworks, market situation, and the processes’ nature, such as their level of routine or structuredness. This paper uncovers the complex nature and relative influence of process-internal and -environmental factors relevant to process standardization, by discussing three case studies from different industries. The findings are summarized in a set of initial conjectures about successful process standardization. This exploratory research is a first step towards uncovering the characteristics of successful process standardization efforts.