Managing context in business process management systems

Businesses need to continuously focus on change and innovation in order to survive in dynamic environments. The ability of an organization to deploy appropriate business processes requires that the fit between business processes and systems that support the management of these processes is continuously maintained and evolved. Acquisition and use of the knowledge about the context in which business processes are defined, modified, and implemented can help maintain this fit. We identify requirements for a business process management system (BPMS) capable of managing contextual knowledge. Based on these requirements, we have enhanced KOPeR, a knowledge-based system for business process improvement, with an explanation facility that can acquire and maintain knowledge about the context behind process definitions and design choices. A case study that illustrates the functionalities of this system which is designed to improve the fit between business processes and BPMS is presented.

Mining version histories for change impact analysis in business process model repositories

In order to remain competitive and sustainable in today's ever-changing business environments, organizations need to frequently make changes to their business activities and the corresponding business process models. One of the critical issues that an organization faces is change impact analysis: estimating the potential effects of changing a business process to other processes in the organization's business process repository. In this paper, we propose an approach to change impact analysis which mines a version history of a business process model repository. Our approach then identifies business process models that have been co-changed in the past and uses this knowledge to predict the impact of future changes. An empirical validation on a real business process model repository has showed the effectiveness of our approach in predicting impact of a change.     

数据仓库模式版本的设计与实现

数据仓库的“非易失性”包括“事实数据非易失”和“模式数据非易失”两个方面,“时间”维度保证了事实数据的非易失性,而模式数据的非易失性需要在数据仓库中建立模式版本来实现。论文分析了数据仓库多维模式中应包含的主要元素及其关系,提出基于关系模型设计并存储数据仓库的模式版本,给出了模式版本的结构定义及其更新维护的实现方法。     

多版本数据仓库中版本进化的实现

多版本数据仓库中模式进化将产生新的数据仓库版本,直接设计基本的模式进化操作算法来实现数据仓库版本进化会使得算法中包含大量冗余代码,并产生多个重复版本对象。设计进化元操作来实现数据仓库版本的进化,给出了数据仓库版本的一种形式定义以及基于版本对象的三类元操作定义,并用案例说明了通过执行元操作实现数据仓库版本进化的算法思想。进化元操作的设计降低了版本进化算法的复杂性,有利于版本的管理与维护。     

Resource behavior measure and application in business process management

Efficient resource behavior measure in business process management is a real and challenging problem. It reflects the actual situations in business process execution from resource perspective and is highly relevant for the business process performance. This paper presents an approach of measuring resource behavior from four important perspectives, i.e., preference, availability, competence and cooperation, based on process mining. Furthermore, this paper shows how business process management can benefit from resource behavior measure. In particular, four applications are addressed to demonstrate the applicability of resource behavior measure in business process management. The presented approach is evaluated based on a proof-of-concept implementation and its application to a real case form health-care. The results show that the proposed approach is possible to improve current state of business process management.     

A unit test approach for database schema evolution

Context

The constant changes in today’s business requirements demand continuous database revisions. Hence, database structures, not unlike software applications, deteriorate during their lifespan and thus require refactoring in order to achieve a longer life span. Although unit tests support changes to application programs and refactoring, there is currently a lack of testing strategies for database schema evolution.

Objective

This work examines the challenges for database schema evolution and explores the possibility of using various testing strategies to assist with schema evolution. Specifically, the work proposes a novel unit test approach for the application code that accesses databases with the objective of proactively evaluating the code against the altered database.

Method

The approach was validated through the implementation of a testing framework in conjunction with a sample application and a relatively simple database schema. Although the database schema in this study was simple, it was nevertheless able to demonstrate the advantages of the proposed approach.

Results

After changes in the database schema, the proposed approach found all SELECT statements as well as the majority of other statements requiring modifications in the application code. Due to its efficiency with SELECT statements, the proposed approach is expected to be more successful with database warehouse applications where SELECT statements are dominant.

Conclusion

The unit test approach that accesses databases has proven to be successful in evaluating the application code against the evolved database. In particular, the approach is simple and straightforward to implement, which makes it easily adoptable in practice.     

Strategy archetypes for digital transformation: Defining meta objectives using business process management

Digital transformation dominates the practical and scientific discourse. Still, many companies do not have a clear plan on how to approach it. Particularly, small- and medium-sized enterprises struggle to initiate their digital journey as they lack resources and expertise. In response, we examine how five companies use business process management (BPM) to implement digital transformation. We perform a qualitative interview study, and analyze the capabilities of BPM based on six requirements of digital transformation. Thereby, we carve out 17 recommendations, which must be adapted according to companies’ meta objectives. We derive three strategy archetypes to serve as implementation blueprints.     

A conceptual framework for understanding business processes and business process modelling

It is increasingly common to describe organizations as sets of business processes that can be analysed and improved by approaches such as business process modelling. Successful business process modelling relies on an adequate view of the nature of business processes, but there is a surprising divergence of opinion about the nature of these processes. This paper proposes a conceptual framework to organize different views of business processes under four headings. It also aims at providing an integrated discussion of the different streams of thought, their strengths and limitations, within business process modelling. It argues that the multifaceted nature of business processes calls for pluralistic and multidisciplinary modelling approaches.     

Using a business process management system to model dynamic teaching methods

Enterprise Information Systems are enjoying an extensive trajectory in the optimization of organizations worldwide, of which predominantly the Business Process Management (BPM) systems stand out for their great flexibility. BPM models describe business workflows and are highly useful in detecting errors and bottlenecks and in identifying possible improvements. On the other hand, educational management software tools offer a large number of functionalities, but have yet to take advantage of these techniques. Our main objective is to perform an empirical analysis in this unexplored area to evaluate the advantages of applying BPM in the implementation of innovative and dynamic teaching activities.Using this methodology, we have designed RubricaSoft, a BPM system focused on providing dynamic educational processes. It automates multiple tasks, including peer evaluation, information integration and the management of deadlines. The results have been very promising from the point of view of the three axes upon which the evaluation has been carried out: satisfaction of students, improvement in academic results and increase in the productivity of teachers. In one of the processes, the time spent by the teacher has been reduced by 80% and student participation increased by 41%.     

Measures and mechanisms for process monitoring in evolving business networks

The literature on monitoring of cross-organizational processes, executed within business networks, considers monitoring only in the network formation phase, since network establishment determines what can be monitored during process execution. In particular, the impact of evolution in such networks on monitoring is not considered. When a business network evolves, e.g. contracts are introduced, updated, or dropped, or actors join or leave the network, the monitoring requirements of the network actors change as well. As a result, the monitorability of processes in the network may be disrupted. This paper proposes a framework to solve the problem of preserving the monitorability of processes in an evolving business network. We first propose a formal model of business networks, contracts, and monitoring requirements. Then, we model network evolution and the mechanisms to preserve the monitorability of the processes in the network for different types of evolution. In particular, the preservation of monitorability requires the actors in the network to take appropriate actions in case of dependencies between already established contracts, and update their monitoring infrastructure to satisfy the new monitoring requirements introduced by evolution. We also define a set of metrics that can be used for supporting decisions regarding the potential evolution of a business network. A case study in healthcare and the discussion of a prototype implementation show the applicability of our framework in real-world scenarios.     

Neural controller for business yield management

In the business and operational research field there is a class of perishable inventory control problems called yield management. Examples are floating pricing strategies in air ticket reservation and hotel room booking. Due to the complex nature of yield management, there are few analytical models available for practical application. This paper presents a neural network approach to solving yield management problems. Using modified back propagation neural networks, a threshold band in the high-dimensional yield management space is generated based on historical data and/or management expertise. When the actual inventory level is outside the threshold band, prices should be adjusted to lead the inventory level back to the threshold band. The interval of the threshold band indicates the stability of the business system.     

The impact of process standardization on business process outsourcing success

What is the impact of business process standardization on business process outsourcing (BPO) success? This paper argues that there is a direct impact of process standardization on BPO success, due to production cost economies, and also an indirect effect via improved contractual and relational governance resulting from better monitoring opportunities and facilitated communication and coordination. This threefold impact of standardization on BPO success is empirically confirmed using data from 335 BPO ventures in 215 German banks.     

Reinforcement learning based resource allocation in business process management

Efficient resource allocation is a complex and dynamic task in business process management. Although a wide variety of mechanisms are emerging to support resource allocation in business process execution, these approaches do not consider performance optimization. This paper introduces a mechanism in which the resource allocation optimization problem is modeled as Markov decision processes and solved using reinforcement learning. The proposed mechanism observes its environment to learn appropriate policies which optimize resource allocation in business process execution. The experimental results indicate that the proposed approach outperforms well known heuristic or hand-coded strategies, and may improve the current state of business process management.     

Business process management—the third wave: business process modelling language (bpml) and its pi-calculus foundations

This paper introduces the ideas behind BPML, the business process modelling language published by BPMI. BPML provides a process-centric (as opposed to a datacentric) metalanguage and execution model for business systems. It is underpinned by a strong mathematical foundation, the pi-calculus. The current paper is derived from supplementary appendices to a book which describes a ‘third wave’ approach to business process management [Business Process Management: The Third Wave, 2003]. The aim is to model business processes directly in an executable form, so that the mobility and mutability inherent in business behaviour is reflected and supported in the corresponding IT systems, erasing the present IT-business divide.     

Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modeling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modeling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modeling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.     

Modelling families of business process variants: A decomposition driven method

Business processes usually do not exist as singular entities that can be managed in isolation, but rather as families of business process variants. When modelling such families of variants, analysts are confronted with the choice between modelling each variant separately, or modelling multiple or all variants in a single model. Modelling each variant separately leads to a proliferation of models that share common parts, resulting in redundancies and inconsistencies. Meanwhile, modelling all variants together leads to less but more complex models, thus hindering on comprehensibility. This paper introduces a method for modelling families of process variants that addresses this trade-off. The key tenet of the method is to alternate between steps of decomposition (breaking down processes into sub-processes) and deciding which parts should be modelled together and which ones should be modelled separately. We have applied the method to two case studies: one concerning the consolidation of existing process models, and another dealing with green-field process discovery. In both cases, the method produced fewer models with respect to the baseline and reduced duplicity by up to 50% without significant impact on complexity.     

Analysis and improvement of business process models using spreadsheets

Software in general is thoroughly analyzed before it is released to its users. Business processes often are not – at least not as thoroughly as it could be – before they are released to their users, e.g., employees or software agents. This paper ascribes this practice to the lack of suitable instruments for business process analysts, who design the processes, and aims to provide them with the necessary instruments to allow them to also analyze their processes. We use the spreadsheet paradigm to represent business process analysis tasks, such as writing metrics and assertions, running performance analysis and verification tasks, and reporting on the outcomes, and implement a spreadsheet-based tool for business process analysis. The results of two independent user studies demonstrate the viability of the approach.     

Building ontology based knowledge maps to assist business process re-engineering

Business Process Re-engineering (BPR) is being used to improve the efficiency of the organizational processes, however, a number of obstacles have prevented its full potential from being realised. One of these obstacles is caused by an emphasis on the business process itself at the exclusion of considering other important knowledge of the organization. Another is due to the lack of tools for identifying the cause of the inefficiencies and inconsistencies in BPR. In this paper we propose a methodology for BPR that overcomes these two obstacles through the use of a formal organizational ontology and knowledge structure and source maps. These knowledge maps are represented formally to facilitate an inferencing mechanism which helps to automatically identify the causes of the inefficiencies and inconsistencies. We demonstrate the applicability of this methodology through the use of a case study of a university domain.