The evaluation framework for business process management methodologies

In an intense competition in the global market, organisations seek to take advantage of all their internal and external potentials, advantages, and resources. It has been found that, in addition to competitive products and services, a good business also requires an effective management of business processes, which is the discipline of the business process management (BPM). The introduction of the BPM in the organisation requires a thoughtful selection of an appropriate methodological approach, since the latter will formalize activities, products, applications and other efforts of the organisation in this field. Despite many technology-driven solutions of software companies, recommendations of consulting companies, techniques, good practices and tools, the decision on what methodology to choose is anything but simple. The aim of this article is to simplify the adoption of such decisions by building a framework for the evaluation of BPM methodologies according to a qualitative multi-attribute decision-making method. The framework defines a hierarchical decision-making model, formalizes the decision-making process and thus contributes significantly to an independent, credible final decision that is the most appropriate for a specific organisation

Business process improvement by means of Big Data based Decision Support Systems: a case study on Call Centers

Big Data is a rapidly evolving and maturing field which places significant data storage and processing power at our disposal. To take advantage of this power, we need to create new means of collecting and processing large volumes of data at high speed. Meanwhile, as companies and organizations, such as health services, realize the importance and value of joined-up thinking across supply chains and healthcare pathways, for example, this creates a demand for a new type of approach to Business Activity Monitoring and Management. This new approach requires Big Data solutions to cope with the volume and speed of transactions across global supply chains. In this paper we describe a methodology and framework to leverage Big Data and Analytics to deliver a Decision Support framework to support Business Process Improvement, using near real-time process analytics in a decision-support environment. The system supports the capture and analysis of hierarchical process data, allowing analysis to take place at different organizational and process levels. Individual business units can perform their own process monitoring. An event-correlation mechanism is built into the system, allowing the monitoring of individual process instances or paths

Healthcare process analysis and improvement at Department of abdominal surgery-University Medical Centre Ljubljana

Background: Healthcare processes in hospitals, likewise processes in companies or governmental organizations, may accumulate problems and obstacles over time, which consequently cause the processes to become ineffective. BPM (Business Process Management) is an approach to process modeling, improvement and automating, which has been used with great success for process improvement. Methods: This work was to examine the possibility of improving healthcare process by using BPM. To implement BPM ideas, a revised TAD (Tabular Application Development) methodology was developed, representing an important contribution to BPM. The first three phases of the TAD methodology were introduced in a step-bystep approach. The first phase deals with process identification, the second develops the “as-is” model, and the third phase discusses process improvement by developing a “to-be” model. Results: We found that (a) the Surgery process is efficient and well organized; (b) patient stay in the Department could be shortened; however for humane and social reasons the leadership prefers to leave the residence time as it is; (c) the process is associated with some time-consuming activities that are performed by other departments and represent the bottleneck of the process. Conclusions: The following were concluded (a) BPM proved to be a suitable approach for carrying out healthcare process improvement; (b) the revised TAD methodology showed to be consistent and efficient in performing BPM approach; (c) The Surgery process discussed was found to be an effective one and no changes or improvements are needed; (d) Concerning time-consuming activities, the leadership decided to discuss this problem with the management of the departments where the activities are executed

SNACH a new framework to support business process improvement.

Business processes are central to any organisation. They coordinate activities, roles, resources, systems and constraints within and across organisational boundaries to achieve predefined business goals. The demand for dynamic business environments, customer satisfaction, global competition, system integration, operational efficiency, innovation and adaptation to market changes necessitates the need for continuous process improvement. In order to adequately respond to these demands, business processes are designed in two approaches: Business Process Re-engineering (BPR) and Business Process Improvement (BPI). This thesis follows the BPI approach which considers existing infrastructure in an organization to improve operational efficiency and achieve organisational goals. Many methodologies have been developed for conducting BPI projects, but they provide little support for the actual act of systematically improving a business process. We adopted case study as the research strategy to examine a collaborative business process, specifically the UK Higher Education Institutions (HEI) admission process. The design science research methodology was used to answer the research questions and satisfy the research objectives. The Map technique was employed to construct the new BPI artefact based on the Mandatory Elements of Method (MEM) from Method Engineering. The new BPI framework comprises of a number of elements to support analysts and practitioners in process improvement activities. We present a novel approach to BPI, the SNACH (Simulation Network Analysis Control flow complexity and Heuristics) framework that supports the actual act of process improvement using a combination of process analysis techniques with integrated quantitative measurable concepts to measure and visualize improvement in four dimensions: cost, cycle time, flexibility and complexity. A simulation technique was employed to analyse the process models in terms of time and cost; and Control Flow Complexity was used to calculate the logical complexity of the process model. A complex network analysis approach was used to provide information about the structural relationship and information exchange between process activities. Using a complex network analysis approach to reduce a process model to a network of nodes and links so that its structural properties are analysed to provide information about the structural complexity and flexibility of the network. To achieve this higher level of abstraction, an algorithm was defined and validated using four disparate process models. The complex network analysis technique is integrated into the SNACH framework and its significance lies in the study of the nature of the individual nodes and the pattern of connections in the network. These characteristics are assessed using network metrics to quantitatively analyse the structure of the network, thereby providing insight into the interaction and behavioural structure of the business process activities. To conclude the design science research process phases, the artefact was evaluated in terms of its effectiveness and efficiency to systematically improve a business process by conducting an experiment using another use case

The activity table as an agent-based modeling approach for optimizing patent exploitation processes

The focal idea of the paper is to model the Activity table in order to increase the efficiency of the intellectual property management. The modeling is done by looking into activities of individual agents (resources or entities). The article examines - in light of the review of related research literature - how the Activity table technique can be used when focusing on IP processes, especially in smaller companies. This technique may be a useful, comprehensive, holistic, but still relatively simple way for intellectual property protection processes’ improvement; allowing to find bottle-necks and ways to avoid them as well as to include a systematic element into processes usually riddled by informality and uncertainty. We highlight the steps and considerations needed to use the Activity table in the exploitation phase and especially on facilitating patent transfers. The article provides two concrete examples, showcasing the use of the Activity table

Flood response process knowledge of Lower Sava Valley communities in Slovenia

This paper focuses on the learning process of the flood-endangered communities in the Lower Sava Valley in Slovenia. In past five years, the communities faced several floods, which occurred because of the rain in central and northeast parts of Slovenia. Floods differed by their severity. On the first hand, the least harming caused only higher water levels of the major rivers, which cause isolation of couple of households. On the other hand, the most harming floods caused roadblocks, flooding the entire areas and communities. Hydrological and meteorological data, describing river dynamics and rainfall was gathered from the Slovenian Environment Agency database, while data describing the severity of the flood events from the Administration for Civil Protection and Disaster Relief database. To be able to simulate and assess floods` characteristics, we combined all gathered data into the singled database with the timeline of the flood events. We used data mining, process modeling and statistical methods to build up the simulation model, to compare simulation output with the real world data and to finally evaluate community learning process. Through the past floods, communities had the opportunity to learn about flood characteristics, how to properly react and protect the endangered property. We identified emerged tacit knowledge, which made possible some communities to reduce flood risk. We conducted preliminary semi-structured interviews with people who live in the flood-endangered areas to get the insight on the perception of the floods. Further, we designed fuzzy knowledge assessment system to evaluate which of the communities demonstrated the highest learning experience. We identified influence of the community knowledge on the response process and further try to optimize learning model, with the measures, extracted from the national strategic defense documents. The improved model revealed much higher self-reliance and flood resilience of the communities, when they are provided with more systematic learning about the floods and counter flood measures. Consequently, the whole flood response process workload significantly reduced according to the higher ability of the communities to resolve flood situation with no additional external support

Artificial intelligence and knowledge sharing: Contributing factors to organizational performance

The evolution of organizational processes and performance over the past decade has been largely enabled by cutting-edge technologies such as data analytics, artificial intelligence (AI), and business intelligence applications. The increasing use of cutting-edge technologies has boosted effectiveness, efficiency and productivity, as existing and new knowledge within an organization continues to improve AI abilities. Consequently, AI can identify redundancies within business processes and offer optimal resource utilization for improved performance. However, the lack of integration of existing and new knowledge makes it problematic to ascertain the required nature of knowledge needed for AI’s ability to optimally improve organizational performance. Hence, organizations continue to face reoccurring challenges in their business processes, competition, technological advancement and finding new solutions in a fast-changing society. To address this knowledge gap, this study applies a fuzzy set-theoretic approach underpinned by the conceptualization of AI, knowledge sharing (KS) and organizational performance (OP). Our result suggests that the implementation of AI technologies alone is not sufficient in improving organizational performance. Rather, a complementary system that combines AI and KS provides a more sustainable organizational performance strategy for business operations in a constantly changing digitized society

Artificial intelligence and knowledge sharing: Contributing factors to organizational performance

The evolution of organizational processes and performance over the past decade has been largely enabled by cutting-edge technologies such as data analytics, artificial intelligence (AI), and business intelligence applications. The increasing use of cutting-edge technologies has boosted effectiveness, efficiency and productivity, as existing and new knowledge within an organization continues to improve AI abilities. Consequently, AI can identify redundancies within business processes and offer optimal resource utilization for improved performance. However, the lack of integration of existing and new knowledge makes it problematic to ascertain the required nature of knowledge needed for AI’s ability to optimally improve organizational performance. Hence, organizations continue to face reoccurring challenges in their business processes, competition, technological advancement and finding new solutions in a fast-changing society. To address this knowledge gap, this study applies a fuzzy set-theoretic approach underpinned by the conceptualization of AI, knowledge sharing (KS) and organizational performance (OP). Our result suggests that the implementation of AI technologies alone is not sufficient in improving organizational performance. Rather, a complementary system that combines AI and KS provides a more sustainable organizational performance strategy for business operations in a constantly changing digitized society