An Application of Process Mining in Organizational Process Redesign

doi:10.21203/rs.3.rs-5268673/v1

In the competitive business environment, organizations face challenges such as rapid customer needs changes and uncertainty, necessitating continuous adjustments in business processes to maintain competitive advantage. Fundamental changes can lower service costs, reduce time, and ultimately increase profitability. Organizations increasingly leverage information technology to convert traditional processes into web-based systems, enabling detailed data collection that enhances process analysis through a method known as process mining. This study focused on redesigning the logistics process at a private bank, utilizing three process mining techniques: discovery, adaptation, and improvement, with Disco 2.14 software. Data was extracted from the bank’s automation and administrative correspondence systems, allowing for a comprehensive analysis of the software outputs. The study identified process indicators, evaluated the adaptation of existing processes, and extracted values using an optimal process. Finally, the research provided suggestions to improve these processes, highlighting the potential of process mining in enhancing efficiency and effectiveness within organizational frameworks. The findings underscore the importance of adapting business processes to meet evolving market demands and leverage technology for improved operational performance.

process mining

business process redesign

logistics process

banking

Processes are primarily designed in organizations based on predetermined activities and plans. Tasks replace processes in line with the growth of organizations due to the adaptation of processes to activities. In this case, the overhead costs increase, activities are complicated, and organization stagnates, resulting in a decrease in services and product quality and customer dissatisfaction. At this level, the necessity of fundamental changes is felt in the organization. [1–2, 3]. This has resulted in the development of several quality management methods or frameworks related to process improvement, one of which is business process reengineering [4]. Process redesign focuses on an increase in productivity and an increase in process productivity leads to an increase in the productivity of the organization since the processes in organizations are in charge of all the affairs [1–2, 3]. Organizational process management has emphasized the potential of information technology, coinciding with its growing use across various fields. Consequently, processes are frequently executed web-based, leading to the integration of process information and enhanced decision-making [5]. In today’s digital era, the capability to log all activities makes process mining a vital method for assessing the current state and boosting productivity [6]. By implementing the information systems, event logs can be easily accessed. In process mining, it is possible to discover and capture all meaningful business knowledge using event logs [7]. The goal of process mining is to improve operational processes and increase their productivity through the systematic use of event data [8].

The implementation of process redesign in any organization such as bank is inevitable due to the above-mentioned factors to achieve process efficiency. Banks define and implement different processes due to their geographical size, organization size, variety of products and services, quick changes in laws, etc. Some of these processes lose their efficiency over time and should be aligned with the current requirements and technologies. This study focuses on improving the logistics process in one of the private banks of Iran by using re-engineering methodology and process mining techniques is considered and aims to answer the questions.

How can logistics processes be redesigned using process mining?

What are the process indicators in each part of the logistics process?

What is the existing status of indicators and bottlenecks in logistics processes? (existing situation)

To what extent does the logistics process workflow adapt to the designed process?

What is the status of the logistics processes after the redesign? (Ideal situation)

Business process re-engineering

An organization is a social goal-based institution which has active and coordinated systems and is related to the external environment. Most organizations had gradual and small changes to take the advantage of the emerging opportunities in the past when the environment was somehow stable [9]. However, organizations have understood that to survive, they must sometimes undertake fundamental changes over time, which requires adopting methods such as business process reengineering [10]. According to Dalmaris et al., process improvement has been developed with the cooperation of thinkers such as Davenport, Hammer, and Chambi since 1990. According to Hammer, process improvement is considered as a structured approach for improving performance focused on the systematic design and precise execution of processes [11].

In re-engineering, the current tasks of the organization are replaced by the main business processes and the organization moves from a task-oriented state to a process-oriented one. For this reason, the business process is accelerated and costs reduce, resulting in the competitiveness of the organization [9].

Process re-engineering seeks more effective and efficient business, more flexibility and accountability of organizations for shareholders, customers and employees, use of the organizational structure to facilitate the workflow in more appropriate way, and better production and service of organizations [12].

Re-engineering identifies activities which fail to create added value in the organization and replaces them with new processes using basic processes and fundamental changes in the organization. In this regard, the energy of organization has focused on value-creating activities, resulting in productivity improvement, speed increase, quality improvement, service improvement, and cost price reduction [13]. Improving system flow can be achieved by reducing major bottlenecks, implementing process changes, and eliminating non-value-added activities [14]. Reengineering cannot be planned and implemented carefully in small cautious steps. [15] The positive advantages of quality management have encouraged many companies to adopt quality management systems [4]. Re-engineering after some trivial reforms in the current situation is impossible without changing the main architecture and structure. Re-engineering means leaving traditional methods and achieving the new methods which are required for processing the products and services of the company and transferring something valuable to the customer. Reengineering is considered as the onset of everything from scratch [16,17]. Business process reengineering is based on the fundamental redesign of an organization's structure to enhance its efficiency by optimizing processes and reducing costs [18]. Business process redesign involves the change management approaches to mitigate the risks and barriers but increase agility [19]. In the definitions, process, phenomenal results, radical thinking, and radical design were more highlighted compared to the others. Reengineering aims to achieve phenomenal results. It means achieving a considerable leap which can only be possible with fundamental transformations and major reforms. Fundamental thinking means leaving the accepted assumptions of the past and answering the question of how to do what should be done and radical design refers to the redesign of something from scratch.

Business process management

Business process management is considered as a management idea and organizations have better performance when they pay special attention to their business processes from the beginning to the end. Every process is implemented in different sectors, specializations, geographical situations, and management levels. Thus, business process management is of paramount significance [20]. Business management is considered as a required approach for improving business performance, competitiveness, and more flexible response. BPM is based on the integration of activities into processes compared to traditional functional management which is based on functions and division of labor. BPM is more complex than BPR and aims to manage or align the business processes for improving their effectiveness [21]. BPM is an integrated continuous process dealing with both technological and organizational considerations which includes the stages of strategy definition, process description, and process implementation. BPM implementation involves significant activities such as analyzing processes, defining the structure between processes, selecting a management method, modeling and optimizing processes, and determining performance measurement and diagnosis system. In addition, the main goal of BPM is to improve the organizational effectiveness in achieving goals. [22] Therefore, Process mining relates to business process management, as both aim to gain insights into business processes [23]. The advantages of business process management are improving the alignment of all aspects of the organization's internal rules and transparency, increasing customer satisfaction, improving business productivity, and utilizing employees in a maximum way, all of which result in improving product quality and reducing costs [22]. Based on a definition proposed by Gažová et al., business process management shows a comprehensive approach which emphasizes the process change with balanced development of human, organizational, and technological aspects, focuses on stakeholder participation, considers the invisible perspectives (psychological-social) and the results of the past (operational/strategic) and acts in form of slow changes [21]. Furthermore, Draghici provided a similar definition and considered business process management as a holistic management approach based on the continuous improvement of processes, change management, and the use of modern information and communication technology systems. Such an approach aims to create an optimal balance between the dynamics of the organization's external environment and the functions of its internal processes according to innovation, flexibility and agility. Further, it helps organizations achieve business results by addressing continuous process improvement requirements and developing them beyond the organization [24].

Process mining

There are some definitions for process mining, some of which are discussed below.

Aalst considered process mining as the extraction of valuable and process-related information from the event report. In his opinion, process mining is complementary to the current approaches in business process management. Process mining analyzes the behavioral aspects of process data [25]. Process mining is a set of techniques which are used in a variety of fields to retrieve valuable knowledge from event reports [26]. Process mining is a field of research focusing on developing innovative methods for collecting knowledge from event reports. In addition, it has been used for various purposes to stimulate evidence-based process improvement [27]. In fact, the purpose of process mining is to bridge the gap between process management and workflow management, on one hand, and data mining, business intelligence, and machine learning, on the other [28]. Process mining aims to construct complete process models from execution data logs [29]. This discipline utilizes process science, which encompasses various methods for enhancing operational processes, including business process management and simulation, as well as data science techniques that extract value from data, such as machine learning and artificial intelligence [30]. Process analysis encompasses various types, including performance analysis, comparative analysis of multiple processes, forecasting, and the initiation of improvement actions [31]. In this regard, the process extraction needs all of the event records for a process and the events log needs the structure as shown in Fig. 1 [34].

Process mining techniques

Process mining techniques extract data from the process history in information systems and convert them into usable knowledge [25]. Here is the study of three process mining techniques. Process discovery is one of these techniques. There are three perspectives for discovery business processes: the process perspective, which focuses on the flow of control between business activities; the organizational perspective, which describes the organizational structure; and the case perspective, which focuses on describing each process implementation [7]. Process mining can discover and create the real and current process in the organization from a set of related data [5]. In this technique, the event is created as an input and an output model without any previous information. Process discovery is considered as the most common process mining technique [25]. Process mining techniques have been used in various industries such as healthcare, manufacturing, logistics and finance [30]. Another technique is adaptation checking where the current process is compared to the pre-designed model using the history of events. Adaptation checking means checking the answer to the question: “Are the events consistent with the current process model or not?”. This technique is used for identifying and measuring the gaps and deviations [25]. In addition, process mining is used for redesigning and improving workflow by identifying process bugs, shortcomings, and bottlenecks [5]. Identifying areas for improvement can be a useful part of process improvement, especially when this activity is included in the continuous improvement process [32]. This technique aims to use the information in the actual running processes and the recorded events of such processes for improving or developing the current processes. This technique copes with the development or change of a previous model [25]. According to a field test, process mining effectively identifies process compliance and improvement opportunities, enhancing productivity [14]. Process analysis encompasses various types, including performance analysis, comparative analysis of multiple processes, forecasting, and the initiation of improvement actions [33].

Fig. 2 displays the input and output of each of these three techniques.

Process mining covers various aspects. From the flow control point of view, the main focus is on flow control such as the order of activities. Finding good attributes of all possible routes is considered as the purpose of exploring this aspect. Organizational discovery focuses on uncovering hidden resources within an organization and understanding the roles involved, including how they interact and relate to one another. Nevertheless, a process example can be specified by using corresponding data elements. When events are time-stamped, it is possible to identify bottlenecks, measure service levels, monitor resource utilization, and predict the remaining processing time of current instances [25].

Table 1 indicates some of the studies in the field of business process reengineering and process mining.

Table 1. A summary of the studies on process mining and business processes reengineering

Field	Authors	Tools	Year	Subject
Process mining	Ghasemi Kalateh [35]	Excel and ProM	2018	Bottlenecks and process deviations of Tehran emergency call center
	Saeidi Moin [36]	Interview and questionnaire	2018	Analysis and improvement of the patient referral process to the imaging department
	Taei et al. [37]	-	2017	The processes of the emergency department in triage, dispatch, CT scan and discharge
	Dolou [38]	-	2016	Health and medical systems of the specialized radiotherapy center
	Akhavan Moghadam [39]	R software	2019	Bottlenecks, waiting time, and idleness of resources in the patient flow process
	Falahatgar [40]	ProM	2013	Patient flow in a hospital
	Taghizadeh [41]	-	2011	Bottlenecks of the patient care process
	Najafpour [42]	-	2019	Process discovery and adaptation in a hospital
	Muhammadi [43]	Excel and ProM	2017	Processes of a short-term inpatient ward in a hospital
	Kazemi [44]	Statistical techniques and clustering algorithm	2015	Analysis and extraction of barriers and process deviations, call center 122 of water and sewage organization in Tehran province
	Firouzi [45]	-	2019	The process of paying third party financial insurance claims in one of Iran's insurance branches
	Ahmadi [46]	ProM and Disco	2016	The process of implementing the foundations at Behbahan Combined Cycle Power Plant
	Amiri [47]	easyfit	2016	Processes of research and education vice-chancellor at Shahrood University of Medical Sciences
	Hosseini	Excel and Disco	2018	The promotion process of faculty members of Persian Gulf University
	Kang et al.	ProM and Disco	2013	Bottlenecks in the risk management process of Volvo's information technology department
	Çelik et al.	ProM and Disco	2016	The completed problems of information technology at Volvo company
	Aalst and Boss	ProM	2019	The processes of a hospital ward in the Netherlands
	Bautista et al.	ProM and Disco	2019	The process of granting a personal loan in a financial institution in the Netherlands
	Buehler et al.	-	2019	Effective models in ITIL related processes
	Fanderham	Disco	2019	The process of building permit application in the municipality of a city in the Netherlands
	Checoli and Santos [48]	Data mining	2021	The effect of process flow decisions on indirect attributes
	Rafiei and Aalst [49]	-	2021	Techniques related to privacy
	Placidi et al. [50]	pMineR	2021	Optimizing the motion flow of the palliative patient in the radiation therapy department
	Chiò et al. [51]	-	2021	Data collected from production system sensors for automatic detection of changes
	Roldán et al. [52]	Disco	2019	Improving the assembly process and training to industrial operators
	Elhadjamor, and Ghannouchi [53]	ProM	2019	The key performance indicators of the medical care process
	Cherni et al. [54]	-	2019	Configuration and improvement of processes and processing of key performance indicators
Business process reengineering	Kianizadeh		2016	Shirt production processes at Hacoupian company
	Taghavifard et al. [55]	ED	2017	Improvement of the service process and reduced waiting time of customers in a bank
	Esmailpour and Soltani [56]	ProM and Alpha Plus Plus, Alpha and Genetic Algorithms	2015	The adaptation of the registration process and dealing with customer complaints
	Khakpazan	Fuzzy DEMATEL and fuzzy ANP	2017	The critical success factors of Bank Mellat for the implementation of business process reengineering and providing a tool for evaluating the readiness of the organization

Process mining is one of the subjects which has recently been used in different fields of process management. The studies mentioned in Table 1 include most of the industries and different processes. However, this method has not been used in the banking industry. In addition, the use of process mining in business process redesign has not been observed in other studies.

Process management currently focuses on large sets of processes. The problem of large dimensions occurs by increasing the number of processes and their features [57]. event logs may have challenges such as heterogeneity, large volume, correlation with other processes, and missing data; on the other hand, there is a wide variety of innovative techniques in the mining process, which makes the blind application of these techniques ineffective in real, complex, and very flexible processes. In fact, it is necessary to adapt the chosen approach to the characteristics of each case study and frame its application with an understanding of the problem in question [58].

In this regard, a number of 35642 data related to 16490 workflows in the logistics process of Ayandeh Bank during the six months of 2020 were extracted from the automation and correspondence system of bank offices. To select the extracted data analysis tool, a list of the most common process tools used in the 2019 process mining competition held at the University of Lisbon is shown in Table 2. As observed, Disco, ProM and Excel tools are used frequently. In this study, Excel software and its Power Query feature were used to refine and prepare. Furthermore, Disco 2.14 software was used for analyzing the event graphs

Table 2. Common tools of process mining [59]

The present study was considered descriptive in terms of the information analysis method. In addition, this study was applied since this study aimed to improve the logistics processes of the bank. This study was data-driven based on the nature of the study which was the use of logistics process data.

Data analysis

Data preparation is considered as one of the most significant parts of data analysis. A small error at this level can change the final result of the study completely and avoid correct results [60].

Findings

After entering the information and running the software, Fig. 3 was extracted as the actual diagram of the process.

Implementation of discovery technique

After running the software, 23 independent workflows were extracted for this process. Table 3 presents the ratio of workflow and included activities along with the number of their repetitions.

Table 3. Analysis of discovered workflows

No.	Ratio of activities	Ratio of workflows	Number of repetitions
1	63%	68%	11248
2	17%	12%	2042
3	5%	10%	1807
4	3%	3%	559
5	<1%	<1%	287
6	<2%	<1%	137
7	<2%	<1%	117
8	<1%	<1%	84
9	<1%	<1%	53
10	<1%	<1%	37
11	<1%	<1%	26
12	<1%	<1%	25
13	<1%	<1%	19
14	<1%	<1%	12
15	<1%	<1%	11
16	<1%	<1%	7
17	<1%	<1%	7
18	<1%	<1%	3
19	<1%	<1%	3
20	<1%	<1%	2
21	<1%	<1%	2
22	<1%	<1%	1
23	<1%	<1%	1

It should be noted that no new workflow or activity is observed, which was predictable since the automation and administrative correspondence system does not allow any other workflow or activity except the predetermined items in the system.

Implementation of checking and adaptation technique

Table 3 indicates some points about the primacy and recency of activities. As a result, 596 product requests have not followed the predetermined rules of the process. Such non-adaptation can be categorized into six groups.

Implementation of improvement techniques

Improvement is considered as one of the techniques of process mining which is used in the redesign and improvement of a workflow by identifying the process bugs, shortcomings, and bottlenecks [5]. This technique aims to use the information in the actual running processes and the recorded event charts of the process for improving or developing the processes [61].

Analysis of input and output

The number of input and duration of each activity are among the parameters used in process mining. Table 4 shows the number of inputs for each activity in the logistics process of the bank.

Table 4.The number and ratio of input for each activity

Row	Activity	Number of incoming demands	Ratio of total demands
1	Submitting the product demand	16490	100%
2	Checking and determining the amount by electronic banking	2798	17%
3	Registering a purchase demand	521	3%
4	Sending to purchase process	521	3%
5	Registering the order	518	3%
6	Registering the purchase invoice	380	2%
7	Registering the warehouse receipt	374	2%
8	Sending products to the warehouse	307	2%
9	Issuing the warehouse remittance and delivering to the customer	13733	83%

Process duration analysis

Checking the process duration is one of the most effective points in process mining. Fig. 4 displays the actual average duration of the logistics process.

Figure 4 shows an overview of the process. The maximum time interval between the two activities is 15.5 days which is related to issuing warehouse remittance and delivering to the applicant, as well as checking and determining the amount by electronic banking. This demand is practically removed from the data range since it is identified as a demand for defective products in the adaptation technique. Accordingly, the maximum time interval between the two activities is 15.4 days which is related to the two activities of sending to the warehouse and registering the warehouse receipt. Based on the software output, the average total process implementation for completed demands is 5.7 days. Table 5 presents the from-to process of activities related to the logistics process of the bank along with the total spent time. As shown, the calculation of the defective workflow identified in the adaptation technique is avoided.

Table 5. From-to process of logistics

Row	From	To	Amount	Total spent time
1	Submitting the product demand	Checking and determining the amount by electronic banking	2620	23.4 year
2	Submitting the product demand	Registering a purchase demand	521	21.7 day
3	Submitting the product demand	Issuing the warehouse remittance and delivering to the customer	11255	157.5 year
4	Submitting the product demand	Checking and determining the amount by electronic banking	170	41.5 month
5	Submitting the product demand	Sending to purchase process	350	73.3 month
6	Checking and determining the amount by electronic banking	Issuing the warehouse remittance and delivering to the customer	2042	22.5 year
7	Checking and determining the amount by electronic banking	Sending to purchase process	171	20.1 day
8	Sending to purchase process	Registering the order	518	10.8 year
9	Registering the order	Registering the purchase invoice	380	13.9 year
10	Registering the purchase invoice	Sending products to the warehouse	307	29.9 month
11	Sending products to the warehouse	Registering the warehouse receipt	302	12.7 year
12	Sending products to the warehouse	Issuing the warehouse remittance and delivering to the customer	101	50.3 week

The average period of each activity can be obtained from the data shown in Table 5. Such information is summarized and displayed in Fig. 5.

Fig. 5. The average period of each activity

The maximum average period is for "registering the warehouse receipt", "registering the purchase invoice" and "registering the order" which is one of the activities related to the process of purchasing products and services.

Analysis of categories and subcategories

Tables 6 and 7 show the delivery time for each category and sub-category was extracted.

Table 6. Average delivery time by categories

Row	Category	Number	Average completion time (days)*	The number of delivery	The ratio of delivery
1	Properties	1409	9.6	571	40.5%
2	Securities	4940	5	4631	93.7%
3	Consumption	7336	5.4	6400	87.2%
4	Bank cards	2636	4.8	2124	80.6%
5	Bank stamps	129	0	0	0%
6	Others	40	3.4	7	17.5%
*This period is calculated for completed demands.

Based on the results, none of the demands for products in the category of bank stamps have reached the stage of issuing a warehouse remittance and delivering to the customer. In addition, the maximum delivery rate is related to securities, consumption, and bank cards, respectively. Finally, the maximum delivery time is related to properties.

Table 7. Average period of sub-categories

Category	Sub-category	Number	Average completion time (days)*	The number of delivery	The ratio of delivery
Properties	Electronic appliances	715	10.2	302	42%
	Stationery	49	5.8	34	69%
	Essentials	152	6.7	90	59%
	Others	6	0	0	0%
	Furniture and fixtures	189	18.8	47	25%
	Furniture	298	7.5	98	33%
Consumption	Electronic	2084	5.7	1781	85%
	Stationery	2059	5.3	1783	87%
	Essentials	2904	5.3	2661	92%
	Others	212	4.4	172	81%
	Furniture and fixtures	61	1.5	2	3%
	Furniture	16	1	1	6%
*This period is calculated for completed demands.

Analysis of undelivered items

Unfinished requests are those which have not reached the stage of issuing a warehouse transfer and delivering to the applicant. Fig. 6 displays the workflow flow chart of the process without considering the activity of "issuing the warehouse remittance and delivering to the customer". As shown, 2757 demands for products have not reached the stage of warehouse remittance and delivery to the customer. A number of 2757 product demands failed to reach the end of the process and the desired product was not delivered.

In this regard, it is necessary to evaluate the unfinished demands separately for each activity. Table 8 presents the number of unfinished demands from each activity and their corresponding figure. Each of these demands for product has not been completed because of a specific reason. Some bottlenecks in the process can be identified by analyzing these causes from another point of view.

Table 8. The number of unfinished demands from each activity

Row	From activity		Number of unfinished
1	Submitting the product demand		1807
2	Checking and determining the amount by electronic banking		559
3	Registering a purchase demand		3
4	The process of purchasing goods and services	Order registration	110
		Registering the purchase invoice	1
		Sending products to the warehouse	4
5	Registering the warehouse receipt		273
Total			2757

In the logistics process of banks, there are two stages for reviewing the demand and determining the amount conducted by the support deputy and the electronic banking deputy depending on the type of products. Based on the results, 391 demands for products failed to be completed after passing the stages of reviewing the demand review and determining the amount and the desired products have not been delivered to the customers. A number of 273 demands were stopped in the stage of registering the warehouse receipt which is the stage before the stage of issuing the warehouse remittance and delivering to the customer. Table 9 presents the 10 undelivered demands which passed the longest time since their last activity.

Table 9. Ten demands with the longest time

Row	Last stage	Number	Date of the last stage	Category	Sub-category	Delay time
1	Registering the order	1	2020/4/20	Consumption	Essentials	423
2	Registering the order	1	2020/4/21	Consumption	Essentials	422
3	Registering the invoice	2	2020/4/26	Properties	Essentials	417
4	Registering the order	38	2020/5/2	Bank stamp	Bank stamp	411
5	Registering the invoice	2	2020/5/3	Properties	Furniture and fixtures	410
6	Registering the invoice	2	2020/5/5	Consumption	Stationary	408
7	Registering the order	5	2020/5/6	Properties	Furniture	407
8	Registering the invoice	1	2020/5/7	Properties	Electronic appliances	406
9	Registering the order	1	2020/5/10	Consumption	Essentials	403
10	Registering the invoice	2	2020/5/12	Properties	Electronic appliances	401

As observed in Table 9, there are undelivered demands which have been over 400 days since their last activity. The average period of the last activity until the date of receiving the report for 391 undelivered demands is about 315.7 days. The category and sub-categories of these demands are one of the factors which can help in deciding to improve the process as shown in Tables 10 and 11.

Table 10. Number and average duration of uncompleted demands by categories

Row	Category	Number	Average period (days)
1	Properties	163	317.3
2	Securities	0	0
3	Consumption	181	294
4	Bank cards	0	0
5	Bank stamps	38	411
6	Others	9	322.3

As shown, there is no uncompleted approved demand in the securities and bank cards categories. In other categories, the average duration of the last activity is not a desirable condition. It is worth noting that 38 demands are available for products from the category of bank stamps, which are all demanded at the same time but not all of them reach the customers after approval.

Table 11. Number and average period of unfinished demands by sub-categories

Category	Sub-category	Number	Average period (days)
Properties	Electronic appliances	68	326.1
	Stationary	1	93
	Essentials	14	328.4
	Others	3	238
	Furniture and fixtures	56	307.9
	Furniture	21	315.6
Consumption	Electronic appliances	89	298
	Stationary	8	375.1
	Essentials	33	297.1
	Others	9	323.8
	Furniture and fixtures	34	244.6
	Furniture	8	331.75

The status of the sub-categories is similar to the categories, and the rest of the items are not in a desirable condition except the stationery sub-category in the properties category.

In this study, discovery, adaptation, and improvement as three common techniques in process mining (were used to evaluate the event graphs of logistics process in the bank. The use of process mining provides us with information and facilities which can be used for discovering the degree of adaptation and improvement in the process and redesigning the process. Such information and facilities are as follows:

Describing the process and precise knowledge of the details
Identifying bottlenecks separately and the use of improvement measures in that area
Recognizing errors and non-adaptations created in the implementation of the process and changing the process or using preventive approaches
Measuring process performance indicators precisely
Evaluating the effectiveness of changes in the process after a certain period

Some suggestions for improvement were extracted using the above-mentioned issues as follows.

Evaluating the warehouse inventory and registering the purchase demand by the deputy of electronic banking
Reviewing the names of products in the system, as well as the categories and sub-categories
Adding the required restrictions to comply with the dates and not allowing the user to submit the demand without taking the previous steps
Increasing the seriousness of the process owner and the required training for system users
Reviewing and clarifying the documents and rules of product allocation to departments of the organization

To measure the process indicators, it is required to define some indicators based on the price, quality, and speed, as shown in Table 12.

Table 12. Suggested indicators of the logistics process

Row	Title	Description	Measurement method
1	Process duration	Average time interval between demand and delivery of delivered products	Total number of demands / total (time of product demand - time of product delivery)
2	Fulfillment ratio	Ratio of delivered demands	Total number of demands / Number of delivered products
3	Purchase ratio	Ratio of demands which require purchase	Total number of demands / number of demands which require purchase
4	Waiting time	Average time interval of demand until now/ Unfinished demands	Average (product demand time - present time)

Table 12 shows quality and speed but it is impossible to provide and measure the indicators related to the price field due to the limitation of information. Such indicators can be measured and presented separately by product type or organizational unit, which can be used in the desired analysis. Table 13 indicates the current status of the measured indicators and bottlenecks of logistics processes in the bank.

Table 13. Measurement of the suggested indicators of the logistics process

Row	Title	Value
1	Process duration	5.7 days
2	Fulfillment ratio	83.3%
3	Purchase ratio	3.2%
4	Waiting time	315.7 days

The highest activity time for finished demands (demanded delivery) is related to the activities of registering the purchase invoice and registering the warehouse receipt, both of which are a part of the process of purchasing products and services. Therefore, the duration of the entire process can reduce by reducing the time of these activities.

The first question is related to what extent the workflow of the logistics process in the bank confirms the designed process. As shown in Table 4, 3.6% of product demands have followed the predetermined process.

During the mining process, the analysis can be performed at any time without incurring extra costs. Consequently, improvements can be continually refined based on the continuous assessment of the effects of changes [10]. By implementing the provided solutions, it is expected that the level of non-adaptation in the logistics process of the bank move to zero and increase the speed of providing services. To provide an accurate answer to this question, it is required to implement the improvement cases and use process mining techniques similar to those used in this study after a certain period (e.g. six months).

Suggestions

The data used in this study were extracted from the database of automation and administrative system in the bank. However, more data can be collected and analyzed from other sources such as financial system.
Due to limited data access, this method was used for logistics process in the bank. This method can be used in other processes, especially those in direct contact with customers by extending this method to other bank processes (in case of appropriate data).
Conducting studies in future periods and measuring the effects of the improvement suggestions given in the implementation process can be considered.

Limitations of the study

Conducting such studies always causes numerous problems for researchers, especially in the field of data supply due to the lack of integration in information systems and resistance of employees to change. Regardless of general issues, the data extracted from the database of the bank's automation system and administrative correspondence can be studied. Thus, researchers cannot suggest more variables, especially in the field of price. Thus, the general conclusion of this study is merely based on the available data because of not having access to all of data in the organization.

Suggestions for future studies

In general, the existing method can be improved in future studies by eliminating the limitations of this study. For this purpose, the following suggestions are provided for future studies.

Using a scientific method to classify and cluster the products in the warehouse
Using machine learning methods to optimize the processes.

Author Contribution

Hamid Asadinia served as the primary author and analyst, responsible for the conception and design of the study, data analysis, and the drafting of the manuscript. Mohammad Taghi Taghavifard acted as the supervising professor and provided final editing and revision of the manuscript to ensure clarity and coherence. Iman Raeesi Vanani served as the consulting professor, offering guidance and insights throughout the research process.

Acknowledgement

I would like to express my heartfelt gratitude to my parents, whose unwavering support, love, and encouragement have been instrumental in my academic journey. Their sacrifices and belief in my abilities have provided me with the strength and motivation to pursue my dreams. I am profoundly thankful for their guidance and unconditional support, which have been invaluable throughout this research process.

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No competing interests reported.

An Application of Process Mining in Organizational Process Redesign

Status:

Version 1

Abstract

Figures

Introduction

Literature Review

Research background

Research Method

Results

Discussion

Declarations

Author Contribution

Acknowledgement

References

Additional Declarations

Status:

Version 1