a case study on process mining implementation in ...

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6 International Conference on Operations and Supply Chain Management, Bali, 2014

A CASE STUDY ON PROCESS MINING IMPLEMENTATION IN MODELLING SUPPLY CHAIN BUSINESS PROCESS: A LESSON LEARNT Mahendrawathi ER Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya 60111 Indonesia, E-mail: [email protected] Hanim Maria Astuti Department of Information Systems, Institut Teknologi Sepuluh Nopember, Surabaya 60111 Indonesia, E-mail: [email protected]

ABSTRACT More and more supply chain business processes are now supported by IT, but there are still ongoing debate on the exact value of IT in supporting supply chain operation and eventually performance. As supply chain emphasizes on managing interconnected business processes that cut across functions within firm and across partner firm, then it is reasonable to think that management of supply chain business process as part of the Business Process Management (BPM) implementation. The first step in BPM is evaluation of current condition which can be done through process mining. This paper attempts to investigate the viability of implementing process mining to model supply chain process through real case study. The case company addressed in this paper is an international manufacturing company that use SAP ERP in conducting their business processes. First a face-to-face interview with representatives from the company are conducted to understand the overall business processes. This is followed by defining and collecting the data necessary to conduct process mining. Based on the interview and initial data collection, two main challenges in implementing the process mining in the case company are identified: breakdown in business processes and information availability. Result from the case company highlights two disconnects in the business processes i.e. between source and make and between make and deliver that makes it difficult to capture and analyze the overall order fulfilment process of the case company. Finally, disconnect between physical flow of materials with the information flow is another main challenge in implementing process mining in a supply chain that has not implement RFID. Keywords: Process Mining, Business Process Management, SAP, ERP, Supply Chain, Case Study.

1. INTRODUCTION The contexts of today’s business environment has moved from a company into a supply chain. Manufacturing company must now think in terms of the entire supply chain rather than focusing on internal manufacturing. Supply chain emphasizes the process approach concerned with how a product or service is delivered to the customer. Cooper et al (1997) proposes several key business process in a supply chain. Lambert et al (1998) argues that the lack of inter-company consistency regarding supply chain business process is a cause of friction and inefficiencies in supply chains.

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To overcome the inter-company consistency, the Supply Chain Operations Referencemodel (SCOR) has been developed and endorsed by The APICS Supply Chain Council as the cross-industry standard diagnostic tool for supply chain management. SCOR describes five primary management processes of Plan, Source, Make, Deliver, and Return. By depicting supply chains using process building blocks, the Model can be used to describe different types of supply chains ranging from a very simple or very complex using a common set of definitions. More and more supply chain business processes are now supported to some degree by information technology (IT). Buijs (2010) states that more and more activities that companies perform are supported by information systems, hence the emergence of Process-Aware Information Systems (PAIS) such as ERP, CRM and SCM. According to Li (2007), IT plays a big role to provide an accurate and real time integration of information and the flow of products along the chain of a company, from inbound to outbound. Modern advanced information technology such as RFID enables data collection at every stage of the supply chain while systems such as electronic data interchange (EDI) and extensible markup language (XML) allows companies to share information across the supply chain (Wang & He, 2011). Mullis (2006) also argues that IT is believed to help a company optimize the performance of supply chain. However, there are still ongoing debate on the exact value of IT, especially Enterprise Systems, in supporting supply chain operation and eventually performance. This may due to the fact that: 1) the system is unable to support the process as it should be carried out or 2) maybe the business process implemented in the enterprise information system is unknown or unaccepted by the employees (Rolland and Prakash, 2000). Jansen-Vullers et al (2006) states that many company faces problem with Enterprise Systems implementation. Therefore, the potential of the systems have not been fully realized. Business Process Management (BPM) is defined as “Supporting business processes using methods, techniques, and software to design, enact, control, and analyze operational processes involving humans, organizations, applications, documents and other sources of information” (Aalst, 2003). The implementation of BPM initiative commonly starts from the evaluation of existing condition which can be done with process mining techniques. Process mining techniques have been invented to model, analyze and ultimately attempt to improve the business process based on the event logs. Buijs (2010) states that nearly all systems record event related data in special purpose event log or “hidden” in the data storage. This enables the use of data stored in the information systems database to evaluate and improve the existing business process models and implementations. Considering that supply chain emphasizes on managing interconnected business processes that cut across functions within firm and across partner firm, then it is reasonable to think that management of supply chain business process can be seen as the BPM implementation. The first step in BPM is evaluation of current condition which can be done through process mining. Therefore, it would be valuable to investigate the implementation of process mining to evaluate supply chain business process. There are growing number of literature that reports the implementation of process mining techniques in real case including De Weerdt et al (2013). Some previous works report on the implementation of process mining on supply chain processes. Zbigniew (2014) describes process mining to analyze processes in inventory management. Other scholars also report the identification of challenges in mining supply chain process and the solution identification using RFID (Gerke et.al., 2009; Gerke, & Mendling, 2009). However, there are many supply chains which are not supported by RFID as data collection tool for their entire business process. This provide a significant challenge for process mining implementation. 809

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This paper attempts to investigate the viability of implementing process mining in modelling supply chain processes through real case study. The case study used in this paper is an international manufacturing company that use SAP ERP to conduct their business processes. The case company have not fully implement RFID for their business process. 2. LITERATURE 2.1 Supply Chain Business Processes In today’s business environment the context has moved from a company into a supply chain. Manufacturing company must now think in terms of the entire supply chain rather than focusing on internal manufacturing. Supply chains emphasize the process approach concerned with how a product or service is delivered to the customer. Cooper et al (1997) describes three elements of supply chain management: the business processes, the management component and the structure of the chain. They enlisted several processes that cut across functions within the firm and across partner firms within the supply chain. These processes are customer relationship management, customer service management, demand management, order fulfillment, manufacturing flow management, supplier relationship management, product development and commercialization and return management. Lambert et al (1998) identifies several challenges in managing supply chain business processes. First, the companies in the same supply chain have different activity structures ranging from functional structure, processes or combination of both. Second, companies have different number of processes, with different activities. Finally, there is no standard reference for business process name so some companies use the same names for different processes and similar names for different processes. These challenge rise the needs for standard in supply chain management. The APICS Supply Chain Council has developed and endorsed The Supply Chain Operations Reference-model (SCOR) as the cross-industry standard diagnostic tool for supply chain management (Poluha, 2007). SCOR is a process reference model for supply chain management that span from the supplier's supplier to with all phases of satisfying a customer's demand. By depicting supply chains using process building blocks, the Model can be used to describe different types of supply chains ranging from a very simple or very complex using a common set of definitions. SCOR describes five primary management processes of Plan, Source, Make, Deliver, and Return, as depicted in the figure below. Plan

Deliver

Return

Supplier’s Supplier

Source

Make

Return

Deliver

Return

Supplier (Internal or External)

Source

Make

Return

Deliver Return

Your Company

Source

Make

Return

Deliver

Return

Customer (Internal or External)

Source

Return

Customer’s Customer

Figure 1. SCOR-model with its 5 management processes (Poluha, 2007) 810

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The above figure depicts the first level of SCOR management process. According to Figure 1, the view of supply chain process is not only seen solely from one company, but also along the chain of a company, i.e. supplier’s supplier, supplier, customer and customer’s customer. In relation to the five basic management processes, the scope of SCOR processes are: 1) Plan, that covers demand/supply management, 2) Source, that covers sourcing stocked, make-to-order and engineer-to-order product, 3) Make, that covers make-to-stock, make-to-order, engineer-to-order product execution, 4) Deliver, this covers order, warehouse, transportation, and installation management for stocked, make-to-order, engineer-to-order, and retail product, 5) Return, that covers return of raw materials (to supplier) and receipt of returns of finished goods (from customer), including defective products and excess products (Poluha, 2007). The processes as seen in figure 1 are decomposed into four level in order to standardize the language of communication among suppliers. The first level or top level describes the main processes in the supply chain or called process type. The second level defines the process categories or called configuration level. The third level decomposes the processes whereas the fourth level decomposes process elements. In addition to five basic processes, there is a level 1 metrics which is usually seen in combination with performance attributes. The performance attributes are reliability, responsiveness, flexibility, costs and asset management. Each of the attribute can be used to help a company define its supply chain performance, for example, “Supply Chain Reliability”, “Supply Chain Responsiveness”, etc. Table 1 below depicts the connection between the first level metrics and the attributes of supply chain performance. Table 1 Supply chain performance attributes and their connection with metrics of the first level (Poluha, 2007) Performance Attribute Delivery performance Fill rate Perfect order fulfillment Order fulfillment lead time Supply-chain response time Production flexibility Supply-chain management cost Cost of goods sold Value-added productivity Warranty cost or returns processing cost Cash-to-cash cycle time Inventors days of supply Asset turns

Customer-Facing Reliability Responsiveness Flexibility √ √ √ √ √ √

Internal-Facing Cost Assets

√ √ √ √ √ √ √

As can be seen Table 1, the attributes are actually categorized into two, attributes for assessing internal performance or internal-facing and attributes related to customer. Each attribute has metrics that can be used as the basis to assess the supply chain performance.

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2.2 Business Process Management According to Weske (2007), Business Process Management (BPM) include concepts, methods, and techniques to support the design, configuration, enactment and analysis of business processes. Aalst et al (2003) elaborates that BPM is restricted to operational processes involving humans, organizations, applications, documents and other sources of information. The process lifecycle that is of main concerned to BPM is described in figure 1. Evaluation: Process Mining Business Activity Monit oring

Evaluation Design: Business Process Ident ification and Modeling

Enactment: Operation Monitori ng

Enactment

Administration and Stakeholders

Maintenance

Design & Analysis

Analysis: Validation Simulation Verification

Configuration

Configuration: System Selection Implementation Test and Deployment

Figure 2. Business Process Lifecycle (Source: Weske, 2007) Figure 2 shows the scope of business process management. One of the important stage in business process life cycle is evaluation stage. In this stage, processes are monitored using Business Activity Monitoring and Process Mining. 2.3 Process Mining Process mining is a technique that combines various field of research including business process modelling and analysis, machine learning and data mining. One of the important factors in successfully implementing process mining is obtaining high quality event logs. Some information systems are equipped with logs to trace the use of the systems. However, in a system that implemented complex PAIS such as SAP ERP, turning on the logs feature will slow down the systems significantly and even potentially crashed the entire systems. Buijs (2010) has developed an application called XESMa that enables extraction of an event log from a data source that does not require programming. 3. METHODOLOGY In order to implement process mining to model supply chain business process, a framework as shown in figure 3 is developed. Process mining project starts with the definition of project goals, scope and focus. The goal of modelling supply chain business process is very much guided by the supply chain strategy. Fisher (2001) has identified two main supply chain strategies, cost efficiency and responsiveness. If the supply chain strategy is cost efficiency then the goal of any BPM initiatives including process mining project will be to contribute on improving business processes to cut costs. On the other hand, if the strategy is to improve responsiveness then the BPM initiatives must aim to cut lead time and speed up time to market. 812

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Any managerial effort with limited resource must have a clear focus and scope. Process mining implementation will require intensive data collection. The focus of the project very much defined by supply chain performance which closely relate to the supply chain strategy. If the strategy is cost efficiency then all the metrics of interests must relate to cost. Responsiveness metrics very much relate to lead time and product availability. Finally, the scope of the process mining implementation is defined by the supply chain business process of interest: plan, source, make or deliver.

Figure 3. A proposed framework of process mining in modelling supply chain business process This research is conducted to explore the viability of process mining implementation as part of BPM in the case company. In order to achieve this objective the first step is to understand the current condition of the company and the challenges that they faced. This step is done through interviews and observations. Based on the findings, the next step is to define the process mining project which include determining project goals, scope and focus, according to the framework as defined in Figure 3. 4. PROCESS MINING IMPLEMENTATION In this section, findings from the case companies are analyzed. First, the case company is described. Then, it is followed by definition of the process mining project and the data preparation. Based on the project definition and data preparation, several challenges are identified. The proposed solution to the challenges are described in the final sub section. 4.1 Case Description The case company, PT. XYZ Indonesia, is part of an international manufacturing company producing leather shoes. The headquarters is located in Europe while the manufacturing facilities are located in Slovakia, Thailand and Indonesia with shops and distribution centers dispersed all over the world. The entire supply chain works in a Push/Pull environment. The production of the shoes is pushed by forecast from the headquarters while the delivery of the finished products are pulled by orders from distribution centers. The company produces wide range of leather shoes for men, women and kids. The products are considered “premium product” with great emphasis on quality, albeit with relatively higher price. The international network produce in two selling seasons: autumn-winter and springsummer. To compete in an industry where customer preference changes rapidly, responsiveness to customer needs is paramount. The company attempts to improve the entire supply chain process to ensure that their product reaches the shop at the right time. To implement process mining for planning process in PT. XYZ, first of all, the planning processes has to be explored. According to the interview for this research, the planning process is started by allocation activity where the headquarters determine the group article to produce within 813

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a certain selling season. The allocation activity is then followed by aggregate production plan in article group level based on sales forecast. The next activity is prognosis where the headquarters breakdown the aggregate plan into specific product and color. The headquarters also distribute the production order to its subsidiaries including the case company in Indonesia. Based on the production order from the headquarters, the case company start to plan production and procurement of material with medium to long lead time. In the third activity, the case company order material with short lead time and check the production capacity. The final activity is order release. In this activity, scheduling of production that include determining the production start and finish date, material to use, material availability, purchase order requirement, material receipt schedule and amount of materials. In analyzing the existing condition of the company’s supply chain process the SCOR model is used as a reference. As the case company have implemented SAP ERP to facilitate the business process, for each process, the SAP Module to facilitate the process automation are presented in Figure 5. Further interviews with manager and planners of the case company provide insights to the challenges faced by the company. For each supply chain process, the issues and also supply chain measure are also presented in Figure 5. As shown in figure 5, each of the four processes in the case company’s supply chain faces different issues. A dashed line rectangle in figure 5 depicts an issue. The main issue faced in source process is the fact that the materials are bought based on allocation and prognosis activity. The materials are not pegged to a certain production order. Furthermore, materials are often bought in bulk/batch while materials are released in smaller quantity. Issues in source process also relate to plan process. As explained previously, planning of production depends on prognosis determined by the company’s headquarters. However, the company does not have a rigid time fence where prognosis are frozen. The headquarters continuously update their prognosis and the company attempts to accommodate the changes. This presents a lot of challenges for the production process. Delivery process is conducted based on orders from headquarters or distributors. The main issue in this process is how to handle various types of products efficiently. The company produces different type of shoes for men, women and kids in different model, size and color. Each customer may order different combination of the product. The company group the handling (pick, pack and delivery) of the customer orders to increase efficiency in processing as well as transportation cost. SAP – Production Planning Forecast continuously change Plan changes to accommodate forecast change

Challenges

Plan Source SAP – Material Management

Materials based on prognosis, not pegged to a certain production plan Different unit of measurement between incoming vs. production Materials are not stored with FIFO rule

Deliver

Make SAP – Production SAP – Warehouse Management

Schedule nervousness Materials availability High work-in-process

SAP – Sales and Distribution

Must wait for headquarters/customers order Handling of products in different grouping (picking wave, M-Group)

Figure 5. SCOR and SAP ERP implemented in the case company 814

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4.2 Process Mining Project Definition Based on the findings from the initial step, the process mining implementation project is defined, following the framework as proposed previously. It is clear that the company as part of an international supply chain network faces many challenges. In order to improve the performance of the company, ideally the main focus must be on the entire business process not on business functions. Figure 5 shows the framework of implementing process mining in the case company. According to the framework as defined in section 3, in order to conduct a project on process mining implementation, there is a need to identify the context of the case implementation. In this research, the context is to model the existing supply chain process of the case company. The subsequent stage is to identify the goal of process mining implementation, which is referred to the supply chain strategy. In this study, the project goal of the case implementation is to improve the end-to-end business process along the supply chain. The next stage is to define the focus of the process mining implementation on the case company’s business process. The focus definition is also related to the definition of supply chain performance measure. The role of other parties in the supply chain such as headquarters and distributors is represented as information flow (prognosis and order). Considering that the company produces fashion-oriented products, thus responsiveness is very important. The focus of the business process management initiative and more specifically, the process mining project is on the lead time of the fulfilment process. Finally, the scope of the process mining implementation project is defined. The scope is the entire process from plan, source, make and deliver in order to capture the existing condition of the supply chain. In other words, the scope of the case implementation encompasses the entire business process of production planning in the supply chain. To sum up, the definition of the case implementation mapped with the framework of process mining implementation is presented in Figure 5.

Figure 5. Process Mining Project Definition 4.3 Data Preparation The next step after project definition is data preparation. In this stage, the case and Case ID must be determined. It is during this phase that challenges of the process mining implementation is 815

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evidence. If the goal is to model the entire business process then it means the case must be something that flow through the processes. However, this is difficult to create a Case ID that can be used to capture the entire business process. This difficulty revealed other challenges in implementing process mining. 5.

CHALLENGES IN PROCESS MINING IMPLEMENTATION According to the analysis that has been presented in the case company, several challenges are found. However, the challenges are then categorized into two main challenges: 1) business process breakdown and 2) information availability. The two challenges will be explained in more detail in the following subsections. 5.1 Breakdown in Business Processes Theoretically, supply chain falls between push and pull systems. The case company presented here works in a push manufacturing and pull delivery system. This fact creates major breakdown in the supply chain business processes. The main breakdowns are: 1) between source and make, and 2) between make and deliver. 5.1.1 Breakdown in Source and Make Processes Materials with long and medium lead time are bought based on prognosis from the headquarters. The prognosis are updated continuously to reflect changes in the market. This means that there are possible deviation from what has been ordered with what is actually needed in production. Continuous change in the forecast may create schedule nervousness. Furthermore, if the deviation is high then the service level will suffer. In one hand, the materials required for production may not be available when needed. On the other hand, some materials may be stored in the warehouse longer than it should. In the end, it may results in high work-in-progress because production must wait for the materials and eventually caused long lead time for production. Another issue is the fact that the materials are not assigned or pegged to a certain production order. In one hand this allow for greater flexibility in material utilization (common materials can be used by different products). However, when materials required for production is unavailable, it will be difficult to identify the root-cause of the problem. 1. Was the material ordered in the right time? 2. Was it due to lateness in material arrival? If the answer to the first question is yes then the planning process is correct, and next check will be the procurement process (question 2). If the material is ordered in the right time, but it has not arrived then the company must check with the supplier for possible issues. If the material is ordered on time and it arrives on time, but it is not available for production, then the company really has to track down the root-cause of the problem. 5.1.2 Breakdown in Make and Deliver Processes When the production process is completed, the finished products are then stored in the warehouse. Delivery of the finished product must wait for order from the headquarters (hub shipment) or distributors (direct shipment). Again, it is difficult to link the production plan with the customer order. 5.2

Information Availability and Visibility Simchi-Levi (1997) emphasizes the importance of information to enable supply chain management. The availability of the right kind of and accurate information provides rich data for 816

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analysis and decision making. Ideally, the information flow correspond to the material flow. In the case company, the material flow in different units: in batch or in smallest unit. But information is not obtained in the same way. Sometimes, information is available only for the batch. Materials are bought in big batches and the information stored in the systems relates to the batch. Production of a certain order may require the materials in different unit of measurement i.e. fractions of the batch. When the materials are picked for production, the systems only record the total quantity taken. There is no record on how each stock-keeping-unit flow through each stage in the production process. Moreover, incoming materials are stored in a rack without specific arrangement. Materials needed for production are picked almost “randomly” without considering which material arrives earlier. This means that the material is not managed in First-in-first-out basis, which may affect the turnover rate of the materials. Finally, the company produces variety of products based on the user (men, women, and kids), models, color and size. Customers may order different combination of end products. The company must manage the handling process (pick-pack-load) carefully to ensure that the right products are sent to right customers while considering packing staff allocation, capacity utilization and delivery efficiency. Finished products are handled in different groups: pick wave and MGroup. As the company received delivery orders, they classify delivery of products with the same criteria (Mode of Transportation, expected due date, delivery route, customers) into M-Group. Several M-Group are grouped into a certain picking wave. Picking wave is a system that guide the entire picking of finished products from the rack until it is packed. Such grouping may be necessary to increase efficiency but it also means more complex tasks co-ordination. While each group information is recorded, it is not always possible to link different groups of information. This means modelling the entire delivery process will be difficult due to the different moving units. 5.3

Discussion The above mentioned challenges mean it will be difficult to capture the entire order fulfilment lead time from the receipt of customer order, creation of plan order, and execution of plan in the production until the order is shipped to customer. Metrics can be obtained for each stage of the business process i.e. procurement, production, packing and delivery time which associates with the functions within the company. If the metrics for entire business process cannot be obtained and the monitoring and evaluation are based on functional metrics, the results may be marginal and negate the main motivation of supply chain management. Furthermore, the entire supply chain suffer from lack information sharing. The case company must wait for forecast and prognosis from the headquarters. Similarly, product delivery must wait for the headquarters and the customers. While the company can actually obtain the information about the forecast and prognosis from the headquarters, they may not fully understand the reason behind the change. The case company may not have the power to influence the decisions. Information sharing and trust related to achieving a win-win solution is certainly a strategic aspects that must be considered by the case company supply chain to successfully implement Business Process Management. In addition, the supply chain must also consider the information availability for measuring high level metrics. While research by Gerke et.al. (2009) and Gerke &Mendling (2009) proposed RFID as a solution to help track and collect data of the material movement and used the data for process mining, it appears to be more important for the case company to firstly improve the link between the business process. Standard artifact must be kept so that the material bought based on forecast can be linked with the production. Likewise, finished product that entered the warehouse 817

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must be linked with delivery order. This would mean that the company must create a procedure to trace and record the material movement in aggregate level, batch level and even individual level. 6.

CONCLUSION Result from the case company highlights the nature of push/pull manufacturing environment as the main challenge in managing the overall business process. There are two main breakdowns in the business processes i.e. between source and make and between make and deliver that makes it difficult to capture and analyze the overall order fulfilment process of the case company. Finally, disconnect between physical flow of materials with the information flow is another main challenge in implementing process mining. 7. REFERENCES Aalst, W.M.P.V, Hofstede, A. H. M.T, Weske, M., (2003), Business Process Management: A Survey, in Wil M.P. van der Aalst (ed.), BPM 2003, Lecture Notes in Computer Science 2678, pp. 1 – 12, Springer-Verlag, Berlin, Germany. Buijs, J.C.A.M., (2010), Mapping Data Sources to XES in a Generic Way, Master Thesis, Eindhoven University of Technology, Eindhoven, Netherland. Cooper, M.C., Lambert, D.M., Pagh, J.D., 1997, Supply Chain Management: More Than a New Name for Logistics, The International Journal of Logistics Management, Vol. 8, No. 1, pp. 1 - 14. Fisher, M. L., 1997. What is the Right Supply Chain for Your Product?, Harvard Business Review, March – April, pp. 105- 116. Gerke, K., Claus, A., Mendling, J., 2009. “Process Mining of RFID-based Supply Chains”. IEEE Conference on Commerce and Enterprise Computing Gerke, K., Mendling, J., & Tarmyshov, K. (2009). Case Construction for Mining Supply Chain Processes. In W. Abramowicz (Ed.), Business Information Systems (Vol. 21, pp. 181-192): Springer Berlin Heidelberg. Jansen-Vullers, M.H., 2006. Mining Configurable Enterprise Information Systems, Data & Knowledge Engineering 56, pp. 195–244. Li, G., Yang, H., Sun, L., Sohal, A.S., 2009. The Impact of IT Implementation on Supply Chain Integration and Performance. International Journal Production Economics, pp. 125 - 138, 2009. Mullis, J.M., 2006. Trade and Industry Development: The Automotive Manufacturing Sector and Their Respective Tier One and Tier Two Suppliers. Lambert, D.M., Cooper, M.C., Pagh, J.D., 1998, Supply Chain Management: Implementation Issues and Research Opportunities, The International Journal of Logistics Management, Vol. 9, No. 2, pp. 1 - 19. Li, L., 2007. Supply Chain Management: Concepts, Techniques and Practices Enhancing the Value through Collaboration. World Scientific Publishing Company. Poluha, R. G., (2007), Application of the SCOR Model in Supply Chain Management. New York: Cambria Press. Rolland, C., Prakash, N., 2000. Bridging the Gap Between Organisational Needs and ERP Functionality, Requirements Engineering 5, p. 180. SCOR Frameworks, https://supply-chain.org/our-frameworks Simchi-Levi, D., Kaminsky, P., Simchi-Levi, E., 2007, Designing and Managing the Supply Chain 3rd Edition, McGraw-Hill. 818

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Wang, H. and He, B., 2011. Research on the Reducing Measures of Bullwhip Effect, International Conference on Software and Computer Applications IPCSIT, vol.9., IACSIT Press, Singapore Weske, M., (2007). Business Process Management: Concepts, Languages, Architecture, SpringerVerlag, Berlin, Heidelberg. Zbigniew P., (2014), Case Study: Process Mining for Analyzing Inventory Processes. [Online] (Updated: 29 January 2014) Available at: http://fluxicon.com/blog/2014/01/case-studyprocess-mining-for-analyzing-inventory-processes/. [Accessed 2 September 2014]

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