1- Approaching digital transformation

2- Understanding the relationship between BPM and digital transformation

3- Methodology and case companies

4- Successful digital transformation with BPM

5- Recommendations for the design of digital transformation projects using BPM

6- Strategy archetypes for digital transformation meta objectives using BPM

7- Concluding remarks

References

Abstract

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.

Approaching Digital Transformation

Digital transformation changes societies and industries, and is fueled by the convergence of social, mobile, cloud, and smart technologies as well as the growing need for automation and integration [1, 2]. Despite new opportunities for product and service innovation, it is frequently perceived as a threat to traditional business models, current organizational structures, and well-established business operations [3-5]. As more and more companies encounter corresponding challenges, they have put digital transformation to the top of their priority lists [6].

1- Introduction

2- Background and related works

3- A unified framework for risk and business processes management

4- Implementation of adoBPRIM on ADOxx

5- Experimentation and evaluation

6- Conclusion

References

Abstract

Enterprise engineering deals with the design of processes which aim to improve the structure and efficiency of business organizations. It develops approaches based on modeling techniques, particularly on business process modeling, to ensure the quality and the global consistency of enterprise strategies and expectations. Nowadays, risk consideration in enterprise engineering is a growing concern since the business environment is becoming more and more competitive, complex, and unpredictable. To face this concern, a paradigm named risk-aware business process management (R-BPM) has recently emerged. It seeks to integrate the two traditionally isolated fields of risk management and business process management. Despite the significant benefits that can arise from the use of R-BPM, it suffers from a lack of solid scientific foundations and dedicated tooling. This present research work contributes to bridging that gap in a twofold way: (i) by establishing the BPRIM Business Process-Risk Integrated Method framework, and (ii) by designing a dedicated tool, named adoBPRIM which supports the efficient application of the BPRIM framework. This paper first comprehensively presents the foundation of BPRIM which is based on three main components and, secondly, its dedicated tool adoBPRIM which was designed using the ADOxx meta-modeling platform. An evaluation with a real case study in the health care domain shows the relevance of the methodological framework.

Introduction

Business process management (BPM) is both a management discipline and a set of technologies that support managing by process [1]. It is a paradigm of enterprise engineering that consists of designing, implementing, controlling and improving business processes in order to increase the ability of the organization to achieve a global high level of performance. BPM has shown, over the past decade, to be a valuable approach to confer maturity and agility to organizations applying it [2]. In the context of BPM, a business process is a symbolic resource, designed to coordinate value production by organizations [3,4]. However, the value creation is threatened whenever the process is exposed to unexpected events, whose occurrence can lead to an interruption of business activities. Hence, a business process is somehow subject to the same qualification and availability requirements as a hardware, software or human resource before commissioning. Although this observation is widely shared, using the process model in order to preserve the level of business performance is at present an original approach of business process management. However, there exists a quite recent awareness, promoted by the principle of business continuity management (BCM) [5,6], which significantly drives the use of concepts from the enterprise risk management (ERM) within business process management concepts.

The bankruptcy prediction research domain continues to evolve with many new different predictive models developed using various tools. Yet many of the tools are used with the wrong data conditions or for the wrong situation. Using the Web of Science, Business Source Complete and Engineering Village databases, a systematic review of 49 journal articles published between 2010 and 2015 was carried out. This review shows how eight popular and promising tools perform based on 13 key criteria within the bankruptcy prediction models research area. These tools include two statistical tools: multiple discriminant analysis and Logistic regression; and six artificial intelligence tools: artificial neural network, support vector machines, rough sets, case based reasoning, decision tree and genetic algorithm. The 13 criteria identified include accuracy, result transparency, fully deterministic output, data size capability, data dispersion, variable selection method required, variable types applicable, and more. Overall, it was found that no single tool is predominantly better than other tools in relation to the 13 identified criteria. A tabular and a diagrammatic framework are provided as guidelines for the selection of tools that best fit different situations. It is concluded that an overall better performance model can only be found by informed integration of tools to form a hybrid model. This paper contributes towards a thorough understanding of the features of the tools used to develop bankruptcy prediction models and their related shortcomings. © 2017 Elsevier Ltd. All rights reserved.

Introduction

The effect of high rate of business failure can be devastating to firm owner, partners, society and the country’s economy at large (Alaka et al., 2015; Edum-Fotwe, Price, & Thorpe, 1996; Hafiz et al., 2015; Xu & Zhang, 2009). The consequent extensive research into developing bankruptcy prediction models (BPM) for firms is undoubtedly justified. The performance of such models is largely dependent on, among other factors, the choice of tool selected to build it. Apart from a few studies (e.g. Altman, 1968; Ohlson, 1980), tool selection in many BPM studies is not based on capabilities of the tool; rather it is either chosen based on popularity (e.g. Abidali & Harris, 1995; Koyuncugil and Ozgulbas, 2012; Langford, Iyagba, & Komba, 1993) or based on professional background (e.g. Altman, Marco, & Varetto, 1994; Beaver, McNichols, & Rhie, 2005; Hillegeist, Keating, Cram, & Lundstedt, 2004; Lin & Mcclean, 2001; Nasir, John, Bennett, Russell, & Patel, 2000). This is because there is no evaluation material which shows and compares the relative performance of major tools in relation to the many important criteria a BPM should satisfy. Such material can provide a guideline and subsequently aid an informed and justified tool selection for BPM developers. Most prediction tools are either statistical or artificial intelligence (AI) based (Balcaen & Ooghe, 2006; Jo & Han, 1996). The most common statistical tool is the multiple discriminant analysis (MDA) which was first used by Altman (1968) to develop a BPM popularly known as Z model, based on Beaver’s (1966) recommendation in his univariate work. MDA, normally used with financial ratios (quantitative variables), subsequently became popular with accounting and finance literature (Taffler, 1982) and many subsequent studies by finance professionals simply adopted MDA without considering the assumptions that are to be satisfied for MDA’s model to be valid. This resulted in inappropriate application, causing developed models to be un-generalizable (Joy & Tollefson, 1975; Richardson & Davidson, 1984; Zavgren, 1985). Abidali and Harris (1995), for example, unscholarly employed A-score alongside Z-score (i.e. MDA) in order to involve qualitative managerial variables, alongside quantitative variables, in their analysis when logistic regression (LR) [or logit analysis] can handle both types of variables singularly.

1. Introduction

2. Literature Review

3. Methodology

4. Results

5. Conclusion

Acknowledgements

References

Business process management (BPM) as a systematic managerial approach enables organization’s workflow to be more effective, more efficient and more capable to adapt to an ever-changing environment. BPM attempts to improve processes continuously with consideration of customer’s needs and requirements. The concept of BPM is not new, however many companies are still struggling with the implementation of BPM and with application of concept and methods based on process approach. The article presents findings of our research on current state of implementation and application of BPM in enterprises operating in Slovak Republic. Our study was focused on several aspects related to BPM such as examination of the reasons why managers decide to implement BPM in their businesses, the level of process mapping, the level of usage of concept and methods of BPM as well as the detection of limitations and barriers of process management implementation and application.

Introduction

As natural consequences of the competitiveness growth, of the impact of rising customer requirements and of the increase of the number of companies offering comparable products, companies are constantly trying to streamline the operation of the entire organization and to enhance own productivity. As many practitioners and researches pointed out, business process management in this regard helps to reduce costs, flow time and to improve quality, productivity and efficiency of processes in organization (Repa, 2012; Weske, 2012). By placing business processes on center stage, companies can gain the capabilities they need to innovate, reenergize performance and deliver the value current markets demand (Smith, Finglar, 2006). The company investigates all the details concerning the analysis of their process attributes because every detail can mean an opportunity to improve a competitive advantage and performance of the company. The process approach is seen as a key tool for continuous improvement of business processes. The concept of BPM is not new, but still remains as one of the current trends in management and not only in Slovakia. The benefits and advantages of BPM are quite clear for many managers but on the other hand, it is necessary also to mention the barriers and risks of process management implementation that are discouraging managers from BPM implementation. The main challenge remains how to implement process principles into an organization’s operation (Skrinjar, Trkman, 2013).

Business Process Management (BPM) is one of the major areas in the enterprise information systems field, which has been mainly supported by the development of Decision Support Systems (DSS), and Business Intelligence (BI) (Turban et al., 2011). BPM aims to improve the organization performance by applying a set of processes, methodologies, and strategies in two main industrial areas: planning and operations. According to the BPM’s philosophy, the SP must be one of the first steps toward the optimal performance of the organizations. This process assists companies in converting strategies and objectives into plans, by monitoring continuously its performance. Basically, the SP is a discipline where a team of organization leaders shapes a future and plans some actions in order to reach it by using the following methods: • The SWOT matrix (strategies, weakness, opportunities and threads) which performs a global diagnostic taking into account environmental factors: a) strengths/weakness are focus in internal and, b) opportunities/threads toward external. • The Balanced Scorecard (BSC) is a performance indicator scheme extensively used in industry and business to monitor the organizational performance against the planning goals. During the process of the SP, two other general domain methods are used in order to capitalize the explicit knowledge; both are manually applied: • The brainstorming technique, which is useful for managing the ideas generated by a group of agents. It is generally applied to produce the elements of the SWOT matrix. • The affinity diagram, which is useful to classify information into categories, according to the nature of the elements or some other criteria. This method has proved to be quite functional to classify the elements of the SWOT matrix in topics related to the strategic areas of an organization. Subsequently, the strategic plans can be formulated based on the resulting information. At this point, it is important to underline the complexity of the SP process, which is highly influenced by the nature of the information produced by the planning team. Thus, SP must deal with a high volume of unstructured text-form information. Additionally, an estimated 80% of total corporate information is represented in textual data formats (Ur-Rahman and Harding, 2012). Nevertheless, there is a lack of approaches to automatically process the SP information. Furthermore, while new powerful and sophisticated tools for Text Processing and Natural Language Processing have been recently developed, many of the SP processes still manually applied (Gupta and Lehal, 2009). Thus, we intend to contribute to the field of the SP with a new SP generic model, particularly suited for SMEs, and the incorporation of a TM framework that allows to process the information necessary to produce strategic plans. The implementation of TM methods may be applied in order to automatize and reduce the information processing time during the generation of strategic plans. The application of TM in a SP generic model presented in this paper is an attempt to deal with this problem, which has been poorly addressed in the SP domain. An application is developed under the cloud-computing paradigm and integrated into a generic model for the SP. The objective of the system is to support organizational leaders when creating strategic plans. The rest of the article is structured as follows. Section 2 addresses the theoretical backgrounds of a generic model for the SP, the TM process, and the related work. Section 3 highlights the general characteristics of the proposed system. In section 4, an implementation of the approach in a real industry case is described and it is discussed in section 5. Finally, the general conclusions are mentioned in section 6.

Thanks to the Internet, customers are better informed, more networked and flexible, and thus more powerful than ever before. Their demands are constantly growing and changing. At the same time, competitors are also better informed and more flexible, and competitive pressure in the market is increasing. Consequently, well-working customer relationship management (CRM) is becoming a critical source of competitive advantage (Band 2013). There are several far-reaching trends in CRM (Band 2013). There is social CRM and mobile CRM. There is also business process management (BPM), which already is well-established in many areas and is playing an increasing role in CRM – to fix today’s inefficiencies and disconnections in many CRM processes, and because business processes need to be improved and adapted more quickly. Analytical CRM is also gaining importance because it is the key to obtaining valuable knowledge about customers. Finally yet importantly, customer feedback management is finding its way into more organizations. Between 2011 and 2012, the proportion of companies using voice of the customer programs has risen from 55 to 68 percent, clearly driving retention and growth (Band 2013). In spite of the general acceptance of the CRM idea, many CRM processes are far from optimal today (Band 2013; Thompson 2013). In theory, they should be optimized continually using the latest knowledge generated from operational data with business intelligence (BI) (Wilde 2010). Important starting points of such an optimization are the decision points in the processes. Continually optimizing the decision logic in these decision points with targeted BI support results in intelligent business processes (Hill 2012; Kemsley 2013). The literature has not yet examined this topic in detail and in its entirety. For this reason, we will investigate the state of the art of intelligent business processes in CRM systematically in the first part of the study (Sect. 2). In particular, we will explain the conceptual framework of intelligent business processes in CRM and identify options for implementation. Generally, such intelligent business processes are deployable in all areas of CRM. A particularly important CRM subprocess is complaint management because a complaint implies an actual hazard to a customer relationship – the essential CRM object – and represents an excellent opportunity to strengthen customer retention by offering a solution (Stauss and Seidel 2007). Stauss and Seidel (2004) even refer to complaint management as the ‘‘heart of CRM.’’ In practice, however, complaint management is often neither effective nor efficient (Gu¨nter 2012). This is because it lacks basics – the effect of companies’ complaint-handling activities on the customer relationship is widely unexplored (Davidow 2003; Orsingher et al. 2010). For example, how do the type and amount of a compensation affect repurchase intentions (Grewal et al. 2008)? As long as such relationships are unknown, organizations cannot improve their processes and customers are left unsatisfied. With BI, an organization could analyze such relationships and their relevant variables continually and align the decisions in the complaint management processes with them. In theory, a promising field of application for intelligent business processes can be opened up here.

Business process management (BPM) comes with different definitions which summarize the benefits of using this approach by organizations. Next, some of the benefits of the business process management (BPM) were selected from the concept definitions: improves quality, efficiency, effectiveness (Meidan, Garcia-Garcia, Escalona & Ramos, 2017), it is adaptable to change (Gazova, Papulova & Papula, 2015), and its main role is that it aligns the process to the customer’s needs (Kluza & Nalepa, 2017). Business process management (BPM) became easier to be used due to the support of tools which allows the users to have access to different actions. Nowadays the development of BPM for projects is used through dedicated tools. The selected benefits from the BPM concept give us an overview of the objectives of this concept in the organizations where it is used. Some of these objectives which are in the end the benefits of using BPM concept represent the results of the knowledge management concept when it is applied in an organization. The similarities between these two concepts are important to be mentioned, because one concept does not exclude the other concept. Young et al (2014) quoted by Uden & He et al (2017) mentioned that when good knowledge management is done in an organization the results are positively influenced: the costs are reduced and the speed of response is increased. In conclusion of what he mentioned, the quality of the products increases and the teams of an organization can be more adaptable to change and efficient. Hamza et al (2008) claims that the knowledge management concept should be encouraged to be disseminated at all the levels of an organization. This approach of dissemination at all levels is encountered also for the BPM concept in the BPM cycle mentioned by Mendling et al (2017). Considering the above approaches, this can be easily reworded as the culture of knowledge management and as a culture of BPM. The culture of knowledge management for an organization represents a big necessity and although it is not called as such, without a minimum of knowledge transfer the organization will probably fail (Nazim & Pauleen, 2017). However, the BPM concept should not represent a blocking point for an organization as it has a lot of benefits. The above mentioned idea is that establishing a culture of knowledge management and a culture of BPM helps the organizations to increase productivity. In the present paper the BPM approach is used to validate the utility of a model proposed in the context of knowledge management. The model of knowledge management is described in detail in another article (Plesa & Prostean, 2017). This model was developed based on observing the context of two automotive companies which use Model Based Design. The obtained model of knowledge management could have an increasing usage by any organization, although it resulted from only two automotive companies which use Model Based Design. The model was proposed in the context of the companies which use Model Based Design because this technology is at the beginning and it extends more and more, year by year as reported on MathWorks® et al, (2017). Model Based Design technology, being at the beginning, is facing different problems including knowledge management

Knowledge and the handling of Knowledge in a wide range becoming more and more a significant role in our society and companies. In the economy, knowledge has become a serious competition factor which is influenced by everyone (Guretzky, 2000). Due to these developments, question about the management of this “knowledge capital” have to be answered by Business strategy considerations. Because of the demographic change, companies suspect more and more competitive disadvantages because of the leave of experienced colleagues and knowledge drain (Hommel, 2015). Therefore, the organization of the handover to a successor can save expensive training time and keep the company specific and general knowledge within the organization. In addition, Knowledge Management (KM) can be described as the discipline of exploiting information, people, processes, mindset and collective experience, that will support or lead to the development of new skills, innovation and understanding which turn improves business output or business requirement (Zhu, 2015). From this KM can be understand as type of Business Process Management with specific relations. In times of digitalization, information and communication technology, in particular, the Internet, provides the global technical infrastructure because of which a fundamental new value-added system based on the exchange of information and knowledge is created (Guretzky, 2000). This systematic increase in productivity in “knowledge production” becomes a challenge for the business and developed industries in general to handle and save Knowledge to operate and improve their processes in the best way, to know and satisfy customer requirements and to be competitive at the market (Guretzky, 2000). This paper analyzes the Knowledge Management to support Business Process Management (BPM) in times of digitalization (started from the consideration of (Ternai, 2014)). Therefore, the core terms will be defined to set a mutual understanding by the different literature definitions. Next to theoretical analysis, practical BPM-Trends will be considered as well as proposed methodology that connect KM processes with BPM. To underline the theoretical study’s a specific survey will executed. The outcome of this paper will be an approach for the business to understand better, how KM supports BPM in an optimal way.

Business Process Management (BPM) plays an important role for maintaining efficiency and effectiveness of the operations of companies and organizations. The adoption of BPM is a very complex and time-consuming process that requires much effort, time, resources and discipline. Since BPM is a multidisciplinary concept, its success depends not only on different Downloaded by UNIVERSITY OF TOLEDO LIBRARIES At 09:26 07 February 2018 (PT) 2 factors, but likely also on their interaction. Organizational culture has been identified as one of the key factors for a successful BPM adoption (Rosemann and vom Brocke, 2010; vom Brocke and Sinnl, 2011; Alibabaei et al., 2010), but it is still widely under-researched in connection to BPM adoption (vom Brocke and Rosemann, 2014). Some BPM researchers agree that the organizational culture needs to be suitable for BPM adoption to succeed (Alibabaei et al., 2010; Schmiedel et al., 2014) and that its characteristics should be seen as predecessors for success of BPM projects (Bandara et al., 2009). More specifically, four key cultural values supporting BPM were identified in (Schmiedel et al., 2013), leading to the proposition that organizational culture should fit the characteristics of a BPM initiatives (Schmiedel et al., 2014). However, organizational culture cannot be changed in a short period of time (Grugulis and Wilkinson, 2002) and changing it into a desired direction is difficult (Lee and Dale, 1998). Therefore, it appears to be more promising to investigate options to customize the BPM adoption approach to the organizational culture. The aim of this paper is to derive propositions that explain in which circumstances a BPM initiative is more likely to be a success. To this end, we investigate the differences in BPM initiatives in connection with the organizational culture according to Competing Values Framework (CVF) culture types (Cameron and Quinn, 2006). In this way, we identify characteristics of BPM initiative that are favourable for its success. Our empirical basis is an explorative survey that we conducted with Slovenian, Croatian and Austrian companies that already have experience with BPM. The four main propositions that we identify complement prior research on BPM and organizational culture, such as (Hribar and Mendling, 2014), (Buh and Indihar Štemberger, 2016), Hernaus et al. (2016) and (Buh, 2016), with a more faceted view on the circumstances in which success emerges. The rest of the paper is structured as follows. Section 2 discusses the background of prior research on BPM adoption in connection to organizational culture. Section 3 presents our research design and our empirical data. Section 4 describes explorative data analysis and resulting propositions. Section 5 discusses the findings in connection of prior research and implications for research and practice before Section 6 concludes the paper.

The growing relevance of the “Internet of Things” (IoT) arises from the possibility to connect people, goods and operations through a global network. The IoT allows for an increasing competitiveness of the global corporations by sharing specific knowledge and social value in the long term, thus influencing the company performance and the customer relationship management. On one side, in many sectors such as agri-food, natural environment, smart cities, insurances, safety security, the IoT utility is changing the way of interpreting the business process management inside and outside the firms as well as innovation processes connected to products and services. On the other side, the competitiveness of markets needs of intelligent equipment, expert systems and technology (Al Mashari et al., 2003; Gubbi et al., 2013). The phenomenon of the Internet of Things (IoT) is based on smart infrastructures revolution, connecting companies, machineries, transports and so on under a unique system characterized by logistic mechanisms, energy resources and means of communication. In this direction, some traders predict that 100 billion devices will be connected to the Internet by 2030. A new technology management scenario is therefore emerging where products consisting of electrical and mechanical parts become intelligent systems that combine hardware, software, control sensors, data storage and connectivity in infinite ways. In this regards, the IoT permits to share big data flow among modern companies, by increasing productivity and reducing marginal costs. At the same time, it becomes vital for businesses to understand the potential of the IoT in order to manage business process management, technology strategy, technology forecasting, technology roadmap, technology management portfolio. We still know very little about how the IoT are changing the way of interpreting the business process management inside and outside the firms and this topic is progressively becoming very hot in the leading managerial literature (Al Mashari & Zairi, 2000). Then, management scholars are aiming at investigating the impact and the role of the IoT on the business process management in terms of promotion of knowledge flow, innovation and competitiveness. Likewise, management researchers aim at understanding how IoT foster innovation inside organizations and which implication this phenomenon can have on business process management and competitiveness of the firms (Al Mashari & Zairi, 1999).

همترازی مفهومی می باشد که به قبل از آخر دهه 1990 بر می گردد که در ان زمان همترازی توسط پائول استراسمن توضیح داده شد: همترازی در واقع ظرفیتی برای اثبات رابطه مثبت بین فناوری های اطلاعات و اقدامات مالی پذیرفته شده عملکرد می باشد . ازاینرو ، همترازی مدیریت فرآیند کسب و کار ( BMP ) بایستی از قاعده یا الگوی مشابه تبعیت کند که قرار است موثر باشد . بنابراین ، هدف این است که چگونه این با BMP و بین آن همترازی دارد و می تواند ارزشی را خلق نماید که در نهایت همانند نتیجه مالی مطلوب برای شرکت تجاری قابل سنجش می باشد .

همترازی مدیریت فرآیند کسب و کار که هم بر قابل استفاده بودن مجدد و تسریع خودکار سازی تمرکز می کند ، لازم می داند که مدیران کسب و کار دارای درک از انچیزی می باشند که همترازی این گونه تعریف می گردد که چگونه شایستگی همترازی را توسعه داد و چه ملاحظاتی بایستی توسط سازمان ها اتخاذ گردند تا تضمین نمایند که همترازی به اندازه کافی پذیرفته می شود . فصل حاضر در مورد این جنبه های همترازی بحث می کند و توسعه BPM همتراز شده را باور پذیر می کند .

Introduction

Business process management (BPM) is the art and science of overseeing how work is performed in an organization to ensure consistent outcomes and to take advantage of improvement opportunities (Dumas et al., 2013). Typically, these improvement opportunities include reductions in cost and execution times, enhanced quality and efficiency, as well as better productivity of processes (Arias et al., 2015). In recent years, the use of information systems in different organizations has increased, thereby facilitating the storage of information relating to the activities that are executed in distinct processes (e.g. case ID, activity name, timestamp, resource) in event logs. This information, also known as event data, can be used to improve end-to-end processes (van der Aalst, 2016). Accordingly, there is an emerging discipline, called process mining, which focuses on extracting useful knowledge based on the information stored in the event logs (van der Aalst, 2016). Process mining can be seen as a means to bridge the gap between Data Science and Process Science, where Data science refers to an interdisciplinary field that aims to extract real value from data, and Process Science refers to a broader discipline that combines knowledge from information technology and management sciences to improve and run operational processes (van der Aalst, 2016). Both BPM and process mining are interested in profoundly analyzing business processes. In conjunction with the methods, techniques and tools created for the design, execution and analysis of operational business processes (van der Aalst, 2013), there is also a central aspect to consider within BPM and process mining: the resource perspective (Dumas et al., 2013), also known as the organizational perspective (van der Aalst, 2016). This perspective focuses on the analysis of information related to the resources that are in charge of executing the activities of a business process (e.g. human resources, software systems, and equipment, among others) (Dumas et al., 2013). This helps to generate insights into how the resources work and it facilitates a more in-depth study of their behavior regarding the processes (Guo et al., 2013; Huang et al., 2012a). In particular, human resource allocation has been considered as a significant problem within the context of BPM (Huang et al., 2012b; Wibisono et al., 2015; Xu et al., 2008; Zhao and Zhao, 2014), due to the influence that the correct allocation may have on the performance of the process (Liu et al., 2014; Zhao and Zhao, 2014), on costs (Huang et al., 2011; Obregon et al., 2013), and on the efficient use of resources during the process execution (Fadol et al., 2015; Kumar et al., 2002; Xu et al., 2008).