Enhancing the order-to-delivery process with real-time performance measurement based on digital visualization

ABSTRACT

This study examined the order-to-delivery (OTD) process that employ real-time performance measurement based on digital visualization (DV). It was performed as a longitudinal case study using the design science approach. The case company delivers customized technology solutions to its customers, with a specific focus on the OTD process of maintenance services. DV, it was found, is a powerful tool capable of enhancing the performance measurement of the OTD process. Determining the focal points that DV-based real-time performance measurement focuses on facilitates the implementation of the performance implications of the process. Further, these performance implications are the result of an appropriate interplay between real-time performance measurement and DV. The study addresses the voice of workers to avoid possible bias concerning the views of management or the limited visibility of certain areas of the company. This study is among the first to examine performance measurement that uses novel technologies to enhance decision-making.

KEYWORDS:

• Performance measurement
• digital visualization
• order-to-delivery process
• real-time performance measurement
• industrial services

1. Introduction

Presently, companies are operating in a challenging manufacturing landscape, one where uncertain environment, increased competition, and volatile demand pressurize traditional companies to reevaluate their operations (Mourtzis et al., 2021; Verhoef et al., 2021). One driver of this change is the evolving digital technology under the Industry 4.0 paradigm, which has enabled companies to creatively reconsider their operations and processes to achieve improved performance (Boffa & Maffei, 2023; Mourtzis, 2020). To do so requires a willingness to change and to innovate and invest in novel digital technology, such as cloud, artificial intelligence, machine learning, connectivity technologies, the Internet of Things, digital twins, and robotics (Mourtzis et al., 2021). By enhancing companies’ internal processes and helping them offer advanced products and services, technological advancements offer companies new strategic paths, thus paving the way for a digitized manufacturing environment (Boffa & Maffei, 2023; Holopainen et al., 2023). For example, digital twins can promote continuous improvement through desired functionalities, such as real-time performance measurement and visualization (Holopainen et al., 2021). Moreover, mass customization allows companies to offer customized and personalized products that can better meet customer needs (Mourtzis, 2022). However, the transformation toward digitalized manufacturing often causes difficulties for companies, as it is the most pervasive management challenge that must be explored in more detail (e.g. Nadkarni & Prügl, 2021; Saunila et al., 2022).

The order-to-delivery process (OTD) usually involves large amounts of production data, multiple parties from different areas, collaborative interactive activities, and iterative processes. All these combined with the different stages of the process – from ordering to design to execution and delivery – render the process quite complicated (Atan et al., 2016; Zhang et al., 2010). The process thus demands efficient planning and control to minimize failures that delay deliveries and cause service errors. One way to effectively manage the processes involved in OTD and their performance, it has been suggested, is to creatively use novel technologies (Horváth & Szabó, 2019; Yom-Tov et al., 2021). For instance, these technologies can be used to monitor the real-time performance of processes (e.g. Papanagnou, 2020; Robert et al., 2022) and thus improve production and operation management.

The complex OTD process can be made more effective and efficient by integrating prior phases through real-time performance measurements, which refers to the digital process of determining the status of an object using real-time information, thus allowing decisions to be made in real time. Technological developments have changed the role of performance measurement, enabling the real-time performance measurement of progress in learning, developing, and nurturing important skills to generate desired behaviors (Nudurupati et al., 2016, 2021). For example, digital twins are revolutionizing the manufacturing (Qi et al., 2021), offering value-added functions such as monitoring, performance analysis, simulation, visualization, verification, virtual experimentation, optimization, and digital education (Qi et al., 2021; Tao et al., 2018).

Thus, technological developments, such as digital twins, have ushered in new ways to visualize processes and their performance while production and operation management. The significance of visualizing process performance has been proven, and technological developments have enabled even more advanced measurement systems – for example, using real-time simulation and optimization to prioritize performance measures, setting target levels for all process measures simultaneously, and visualizing process information and measures in a format that is easy for users to understand.

However, how the OTD process can be facilitated by real-time performance measurement remains unclear. This study thus aimed to contribute to the performance measurement research on the use of novel technologies, such as digital visualization (DV), to enhance decision-making and management. A longitudinal case study using the design science approach was conducted. Since the theoretical underpinnings of this study were based on performance measurement, DV was considered a tool for implementing performance measurement and the OTD process a context in which performance measurement takes place. Thus, this study improves the theory by investigating the OTD process of industrial services through DV-based real-time performance measurement. The following research question was developed:

• In what circumstances and how should DV be used for real-time performance measurement of the OTD process of industrial services?

This paper is structured as follows. Section 2 details the literature review we conducted on visual real-time performance measurement and the management of processes using novel technologies. Section 3 describes the design science approach we used in our longitudinal case study. Moreover, it describes the case selection, presents the research context, and discusses how DV-based real-time performance measurement of the OTD process of industrial services can improve performance. In Section 4, the study results are evaluated, the focal points of the OTD process are presented, and the design proposals for the measurement entities are developed. Finally, in Section 5, the study phenomena and study contributions vis-à-vis previous research are discussed.

2. Literature review

We examined the literature on performance measurement by taking into account different perspectives. First, we studied performance measurement and management from the process perspective. We then explored literature related to performance measurement and management in the context of digital transformation, which was strongly related to the real-time and visual functionalities enabled by digital technologies (especially digital twins). Our review methodology included three main phases (Mourtzis, 2020) using mainly Scopus as a scientific database. First, to search for the relevant studies, we used words such as ‘performance measurement,’ ‘performance management,’ ‘real-time,’ and ‘visualization.’ To search for more detailed information, we used context-specific search words, such as ‘digital manufacturing’ and ‘digital twins.’ Second, after the search was completed, the relevant articles were identified by reading their abstracts. Finally, those articles that were to be fully read were selected and divided based on their topic.

2.1. Performance measurement and management of processes

Technological development has offered new high-quality maintenance services for customers, enabling them, for example, to evaluate a process’s performance in a new way by better use of data to support decision-making (Mourtzis et al., 2021). Performance measurement, which has been studied for many decades, has recently been defined as the process of setting and developing performance measures and collecting, analyzing, evaluating, and reporting performance data (Melnyk et al., 2014). In addition, performance measurement and management can be viewed from the perspective of organizational control theory by considering its technical and social mechanisms, where technical control (i.e. performance measurement) determines how tasks are performed and social control (i.e. performance management) includes behavioral aspects (Nudurupati et al., 2021; Smith & Bititci, 2017). Regarding the performance measurement of processes, Garengo et al. (2005) argued that existing performance measurement systems should be re-evaluated and that, as a result, actions should be taken to replace functional performance measurements with process-related measurements. Researchers have also suggested the introduction of process-oriented performance measures to ease process simulation. They have also highlighted the deficiency of functional organizations and the advantages of performance measures in decision-making (Beretta, 2002; Garengo et al., 2005).

However, according to van der Aalst et al. (2016), process models are helpful only if they really assist in improving processes; models that are sound but not used to configure a business process management system do not enhance performance. Therefore, the authors advocate focusing on the process rather than on the process model, as a better process is one that helps the most in fulfilling a company’s strategic goals. Moreover, they proposed that a variety of key performance indicators (KPI) – also called process performance measures – could be used to measure process improvements. They can be thought of as quantities that can be clearly determined for a specific process, provided that the calculation data for these performance measures are obtainable (Dumas et al., 2013). They can be divided into different dimensions, such as cost, time, flexibility, and quality. This means that time can be measured by utilizing waiting time, cycle time, or non-value-adding time; cost by utilizing waste, cost per execution, and resource utilization; and quality by utilizing customer satisfaction, error rates, and service level agreement violations (van der Aalst et al., 2016).

Process management and the performance measurement of processes also affect organizational decision-making. According to Fullerton et al. (2014), decisions should be passed from managers to teams that are closely working with the processes. Moreover, with project-powered improvements guided by managers, an organization is changed from a traditional orchestration to a top-down one. A genuinely authorized process team should play a prior role in designing the measurement system for the process, and since a team is liable for the value creation process that includes several functions, it must create measures to monitor the process (Parry & Turner, 2006) in real time.

2.2. Real-time performance measurement

The exploitation of information and communication technology (ICT) in the field of manufacturing has been gaining increased interest because of its developments (Liu et al., 2018; Saunila et al., 2022; Korsen and Ingvaldsen, 2022). The ICT developments, including Industry 4.0 technologies, can automate the collection and analysis of large amounts of data and enable more real-time and user-friendly access to information throughout an organization (Korsen & Ingvaldsen, 2022; Nudurupati et al., 2021; Saunila et al., 2022). A revolutionary technology that is undergoing digital transformation in the manufacturing field is digital twins (Aheleroff et al., 2021; Fan et al., 2021; Qi et al., 2021), which can, for example, promote continuous improvement through desired functionalities, such as real-time performance measurement and visualization, and offer different benefits to various stakeholders (Holopainen et al., 2021). Aheleroff et al. (2021) explored Digital Twins as a Service (DTaaS) and its significant advancements, including intelligent scheduled maintenance, real-time monitoring, remote control, and predictive functions. Saunila et al. (2022) investigated digital twins in a service context, highlighting that they can act as a communication platform that enables learning and socialization, thus effectively acting as a social and technical control mechanism.

Therefore, unique capabilities that are hard to replicate and that are needed to govern the rate of change in a company’s operations are needed (Nasiri et al., 2020; Teece, 2014). This has resulted in the emergence of the research stream of real-time performance measurement (e.g. Holopainen et al., 2021). Real-time performance measurement refers to the digital process of determining the status of an object with connected and real-time information, thus allowing decisions to be made in real time. The object can be a product, a machine (Romero et al., 2018), a production concept (Papanagnou, 2020), or a service (Aheleroff et al., 2021), as long as it allows real-time tracking and reporting. Real-time performance measurement is thus applicable to different levels of operation.

By making employee performance measurement easier, digital technologies facilitate managers’ decision-making and employee performance evaluation (e.g. Horváth & Szabó, 2019). For example, using IoT technologies, the real-time status of processes and machines can be monitored via smartphones (Zhong et al., 2017). By monitoring employee motivation, managers can better assign employees tasks and assign resources to the tasks accordingly, resulting in better overall performance (Škec et al., 2017). Real-time performance measurement also facilitates team-level evaluation (Robert et al., 2022), enhancing team collaboration by providing flexible operation, interconnected ways of action, and possibilities for real-time feedback (Y. Yin & Qin, 2019). Moreover, in terms of firm-level operation (Horváth & Szabó, 2019; Wetzstein et al., 2008), real-time performance measurement offers rapid reactive ability (Hwang et al., 2017; Rezaei et al., 2017). It helps, for instance, in controlling assets and production (Hwang et al., 2017; Papanagnou, 2020; Rezaei et al., 2017), verifying whether the desired quality standards are met (Horváth & Szabó, 2019; Romero et al., 2018), enhancing productivity (Hwang et al., 2017), and monitoring the progress of business goals (Wetzstein et al., 2008). All these actions are necessitated by an increase in a firm’s capacity to incorporate, store, and shape data (Rezaei et al., 2017).

Real-time performance measurement is also efficient in the context of supply chains, supporting the collection and sharing of data and information through the ICT developments (Kamble et al., 2020; Nudurupati et al., 2021). Performance measurement enabled by IoT technologies is efficient in monitoring and managing the whole supply chain in real time; moreover, IoT enables real-time data collection, data efficiency, and effective communication within the supply chain, which, in turn, improves integration and cooperation (Dweekat et al., 2017). This results in more effective collaboration in supply chains and networks and helps to meet customer needs more quickly (Nudurupati et al., 2021). However, conducting real-time performance measurement, since it is a digital process, is not an easy task for firms. A useful way to cope with the process is through visualization.

2.3. Visual performance management and measurement

Though visualization is not a new concept, technological development has made its implementation more efficient – for example, real-time monitoring can be done via smartphones through graphical dashboards (Zhong et al., 2017). Visualization refers to the presentation of information, data, and knowledge in a graphical form that facilitates the provision of insights, the recreation of lively images, the evolution of comprehension, and the transmission of experiences (Lengler & Eppler, 2007). It also refers to a visible expression that describes a group rather than an individual. (Greif, 1991). Visualization’s benefits have been studied by many researchers (e.g. Eppler & Platts, 2009). As part of the management activities of companies, visualization supports decision-making (Al-Kassab et al., 2014), promotes communication (Bititci et al., 2016; Eaidgah et al., 2016; Larsson et al., 2017), enhances information flow (Eaidgah et al., 2016), and supports continuous improvement (Bititci et al., 2016; Eaidgah et al., 2016; van Assen & de Mast, 2019).

Visual performance management and measurement have been defined as a set of practices in which visual techniques are utilized to offer timely information to the right stakeholders about the performance of processes (van Assen & de Mast, 2019). Using visualization techniques in performance management and measurement has been shown to positively affect management activities (e.g. Al-Kassab et al., 2014; Bititci et al., 2016). Using case studies of seven manufacturing small- and medium-sized companies all over Europe, Bititci et al. (2016) studied the influence of visual performance management systems, demonstrating that such systems support strategic actions, promote performance management activities, engage people, enrich collaboration, enhance communication and integration, and encourage a culture of continuous innovation. Further, the survey by van Assen and de Mast (2019) showed that visual performance management and measurement improve operations when mediated by lean practices and concluded that it should be an infrastructural practice that strengthens an organization’s overall condition. Moreover, Al-Kassab et al. (2014) found that visualization can support decision-making, improve organizational effectiveness, and create business value, thus making it a useful method to tackle the information challenges of industrial processes.

Technological developments have ushered in new ways to visualize information about processes and their performance while supporting production and operation management (e.g. Fan et al., 2021; Zhong et al., 2017). For example, Bahrar et al. (2021) focused on designing a real-time security system that utilized visual means and could be controlled by a smartphone. In addition, Fan et al. (2021) studied digital twins and their visual capabilities to monitor production lines in real time as well as historical events. Moreover, the rise of new visualization techniques has resulted in new platforms to visualize processes and their performance and enabled the rapid reactive ability of performance measurement systems (cf., Horváth & Szabó, 2019; Y. Yin & Qin, 2019). Thus, the DV of a process seems to be an excellent initiative for real-time performance measurement, as it can offer process information and KPIs in real time.

However, there is a lack of research on how the OTD process can be facilitated by real-time performance measurement. Thus, this study contributes to the performance measurement research on the use of novel technologies in terms of DV to enhance decision-making and management.

3. Methodology

3.1. Design science approach as a research process

This study examined how to enhance the OTD process of industrial services with novel technologies that support the design and introduction of a DV-based real-time performance measurement system. To this end, a longitudinal case study was conducted using the design science approach. This approach is used to create general knowledge and assist in finding solutions to field problems (Denyer et al., 2008; Oliva, 2019; van Aken & Romme, 2009). Design science research occurs in various fields: for instance, in management, design science research is employed to resolve improvement problems by designing interventions and to solve construction problems by designing systems and processes (Denyer et al., 2008; Oliva, 2019). This study followed the call of Oliva (2019) for design intervention to be used to test existing theories. Our design science approach is illustrated in Figure 1.

Figure 1. The design science approach as a step-by-step research flowchart.

In the first part of the study, the research problem was examined in its context, and the research question was formed. According to the design science approach, research questions are driven by field problems (van Aken & Romme, 2009). Since the case company had difficulties managing and monitoring the OTD process in real time, the research question was structured as follows: In what circumstances and how should DV be used for real-time performance measurement of the OTD process of industrial services?

The second part of the study concerned interventions that helped design the DV-based real-time performance measurement. Design interventions are used to solve improvement problems – that is, to improve the practices and effectiveness of organizations. With interventions, there is also the opportunity to influence behavior (Denyer et al., 2008). The interventions included various steps that resulted in the measurement entities supporting real-time performance measurement and management of the OTD process. Observations were then used to review the functioning of the process and identify the useful measures the case company already has and the measures that might need to be added to maximize the benefits of the measurement entities corresponding to the focal points of the OTD process.

The third part of the study consisted of a revisit to observe how the designed solution was developed from the longitudinal case study. Longitudinal case studies have proven to be suitable for design science research (e.g. Kaipia et al., 2017). Finally, amendments and improvements to the theory were proposed (Oliva, 2019).

3.2. Case selection and description

Operating in a technology industry, the case company delivers customized technology solutions to customers, including maintenance services for its own products and those of others. Its maintenance service is a continuously growing segment, generating a significant portion of the company’s annual turnover. Its strong growth and complexity resulted in the need for continuous business improvement. For a few years, the case company thus used lean production principles and methods. However, to ensure continuous improvement in the future and to meet the challenges of maintenance services, there was a need to find new ways and tools for process development. This provided a fruitful context for conducting the present study and addressing this field problem by designing and evaluating new digital techniques for process development.

The study focused on the OTD process of maintenance services. The process comprises 21 main steps, beginning with the customer service request and product receipt and ending with product delivery and billing, and the responsibility for conducting these steps is shared among different departments. Sometimes, not all steps are necessary. It is important to note that suppliers and customers also influence the process, which affects process management. As the maintenance service business continues to grow and complexity increases, the company needs new ways to manage the process. This provided an interesting and valuable problem context for studying how DV-based real-time performance measurement of the OTD process of industrial services can enhance business performance.

3.3. Data collection and analysis of the research process

Data collection was divided into four phases – studying the problem in its context, designing intervention, observing outcomes, and revisiting (Table 1). Several qualitative data collection methods were utilized in these phases, and the role of the researcher varied. According to Holmström et al. (2009), involving theoretically minded researchers in the early phases of design science research can generate benefits, such as improving the solution design and steering efforts toward fruitful theoretical insights. In the first phase of the research process, the study problem in its context was discussed in a focus group meeting. The initial planning of the context of the intervention was conducted with representatives from the case company and the external service provider company that offers DV solutions to customers. The researcher’s role was to act as a facilitator and conduct the analysis. This analysis revealed that, in the focus group, there were several challenges in the industrial service process, mainly in managing and monitoring. The topics of DV and real-time performance measurement were presented in the first focus group with the help of the external service provider who confirmed the case company’s interest and commitment to the research process.

Table 1. The data collection phases and research methods.

Data collection phase	Method	Researcher’s role	Informants	Themes
Studying the problem in context	Focus group 1 for initial planning (context of the intervention)	Facilitators and providing analysis	CEO, factory manager, sales manager, and sexternal service provider company member	Aim of the intervention, and definition of the key concepts
Designing intervention in collaboration with practitioners	Focus group 2 for designing the pilot and participants (content of the intervention)	Facilitators	Factory manager and service manager	The key objectives of the intervention
	Utilization of secondary data	Providing analysis		The key steps of the process, and the existing performance measurement of the process
	Focus group 3 for presenting the intervention protocol	Facilitators, and providing analysis	Operational level: Two service technicians, two service engineer, dispatcher, and service manager Sales: Two sales engineers and two area sales managers. Management: Sales manager, factory manager, and CEO	Presenting the aim, the key objectives, and the designed intervention protocol to the participants
Observing outcomes	Two weeks’ observation of the service process	Observer	Different process step workers	The key steps of the process in practice, the functionality of the process in practice, and the development needs
	Semi-structured interviews	Interviewer	Operational level: Two service technicians, two service engineers, dispatcher, and service manager Sales: Two sales engineers and two area sales managers. Management: Sales manager, factory manager, and CEO	Current state: Information needs and The challenges of employees and managers in daily operations Target state: Development targets of daily operations, required process information, possible indicators to monitor and control the process in real time, and data availability
Revisiting to observe how solution developed	Focus group 4 for reflecting the pilot	Facilitators	Factory manager, service manager, and external service provider company member	Further development of the concept

The second phase of the research process focused on designing an intervention in collaboration with practitioners. The data collection methods consisted of focus group 2, using the company’s own secondary data, and focus group 3, which helped design the pilot project and determine its participants (the content of the intervention) and present the intervention protocol. Described precisely in the intervention phase, the focus was on the research problems to be solved and the research objectives to be achieved. The researcher’s role was to facilitate, promote, and support the focus group discussions. This phase, through the focus groups and the analyses of discussion and secondary data, helped design an intervention of a DV-based real-time performance system.

The third phase of the research process involved observing the outcomes. Two weeks of observing the service process helped in developing a preliminary comprehension of the key phases of the process in practice, its functionality, and the development needs. One researcher analyzed the observations. The revelation of the mentioned themes supported in preparing and conducting the interviews. Semi-structured interviews at three process levels complemented the observations. The interviews were aimed at gathering information about the current state of the industrial service process and its possible target level, including the possible indicators of the real-time monitoring and control of the process. The first part of the interview focused on the kinds of information needs employees and management in different service departments of the company have and the challenges they face in their daily operations. In addition to exploring the current state of the process, its possible target state was determined. This focused on determining the targets of daily operation, the process information, the potential indicators to monitor and control the process in real time, and data availability.

In total, 13 interviews were conducted in the company’s office. The aim was to enable the maintenance service process to be viewed from different perspectives of department levels and process steps to ensure that the voices of workers were heard. The interviewees were divided into three areas: operational level, sales, and management. All the interviews were recorded and transcribed and lasted between 40 and 80 minutes. The interview data was analyzed using content analysis, considering the predetermined themes as a coding model. The transcribed interview data was coded using an iterative process aimed at filtering and gathering essential information. In addition, within-case and cross-case analyzes were conducted (Eisenhardt, 1989; R. K. Yin & Yin, 2018). The within-case analyses enabled to explore how each interviewee approached the predetermined themes and identified the main points of view. The cross-case analyses enabled us to investigate the replication logic and identify repeated patterns. This process resulted in a description of the focal points of the process as well as a framework for real-time performance measurement. Afterwards, there was an open discussion between the three researchers about the results of the case, and possible corrections were made. Finally, the results were analyzed and discussed until a consensus was reached, after which suggestions were made.

The last phase of the research process was a revisit to observe how the designed solution developed. The aim of focus group 4 was to reflect on the designed pilot solution for the case company and the external service provider company. The future development of the concept was also discussed. Based on the outcomes of the four data collection phases, the final actionable design proposals for a real-time performance system based on DV were structured.

4. Research outcomes

4.1. The focal points of the OTD process

In terms of outcomes, we identified the focal points of the OTD process (Table 2). The focal points are the points of the process on which the measurement should specifically focus when developing the process to maximize the benefits of real-time performance measurement based on DV. Next, we examined in more detail what the focal points mean from the process point of view, what the key issues are, and what part of the process they mainly affect.

Table 2. The focal points of the OTD process.

Category	Focal point	Description
External	Customer impact on the process	Communication
		Customer responsiveness
		Customer access to the process
	Supplier impact on the process	Communication
		Responsiveness of suppliers
		Supply of spare parts
	Fluctuations in demand	Variation in the number of maintenance products
		Variation in the size of maintenance products
		Dynamic nature of the maintenance service
Internal	Interfaces between departments	Dialogue
		Understanding
	Non-basic operations	Quick work
		Work done at the customer’s place of business
		Work other than basic processes
	Resources	Shortage
		Traceability
		Flexibility
	Workload	Amount of workload and its variability
		Uncertainty and traceability
	Lead times	Measurement of the lead times and target times
		Traceability of lead times and achievement of target times
	Information acquisition	Information is scattered across different locations
		Information is hard to find
		Case-by-case traceability of information
		Poor reliability of information
	Human factors	Employees’ ability
		Communication and information sharing

4.1.1. External focal points

Service processes require customer involvement, which complicates management; therefore, the first external focal point was customer impact on the OTD process. The customer has a role to play in the OTD process, thus influencing the process operation. To be exact, the customer must accept the offer before the necessary spare parts for the product can be ordered. Therefore, the customer response time has a direct influence on the progression of the process. Discussions with the customer are also conducted at other stages of the process. Such communication was often incomplete and slow, making the process and maintenance operations challenging. Moreover, the customer can modify and delay the process with their own actions affecting, for example, maintenance planning. These directly influence the functioning of the process, which was reflected in an increase in the lead times of the maintenance products.

The company has several supplier relationships. While some of them ran smoothly, allowing suppliers to respond quickly to the company’s order requests, others were more challenging, particularly the relationships with occasional suppliers. However, these suppliers are necessary for the operation of maintenance services. In addition to supplier responsiveness, there were also problems with the spare parts supply, including availability, slow delivery, and the delivery of incorrect parts. The effectiveness of supplier relationships plays an important role in maintenance service, as the assembly phase cannot start before the right spare parts are delivered.

Fluctuations in demand, another focal point, refer to the variations in the number of maintenance products and in the size of maintenance products. They caused internal challenges in managing the OTD process, such as the need to prioritize and optimize resources and difficulty in meeting target times. They are related to the dynamic nature of maintenance services. Maintenance situations may vary within a day; for example, a customer’s non-urgent maintenance request may suddenly become urgent. The dynamic nature of the maintenance service required a constant need for prioritization and the ability to manage changes the new DV-based real-time performance measurement system could support.

4.1.2. Internal focal points

When looking at internal focal points, it is good to notice that a company can more easily tackle these focal points compared to external focal points. It is also crucial to find that internal and external focal points are interconnected. For example, fluctuations in demand can lead to a shortage of resources, or customer impact on the process may increase non-basic operations and thus affect the functionality of the process.

The company’s maintenance service includes different departments that perform their own process-stage tasks. The internal issues of the departments themselves were not perceived as difficult as the interfaces of the departments within them. The interactions between these departments were sometimes perceived as cumbersome and deficient. In addition, the focal points between the departments were dialogue between departments, understanding the process from the perspective of another department, and understanding the process tasks of different departments. These focal points led to uncertainty between departments.

The OTD process of industrial service covered two types of maintenance, basic and extensive, which differed in the level of requirements. In addition, the company’s maintenance service included work done at the customers’ place of business, quick work done at the factory, and all work other than the basic process. These other works took resources away from the basic process, could stop the operation of the entire basic process, and thus could affect customer satisfaction and extend the delivery time for other products.

The next internal focal point is resources, particularly in terms of shortage, traceability, and flexibility. The shortage of resources was affected by various factors, such as fluctuations in demand, work that deviate from the basic process, and the customer’s impact on the process, which have been addressed previously. In the planning stage, resource shortage problems were highlighted, which affected the functionality of the process. The shortage of resources is related to their traceability. Challenges were also experienced in terms of resource flexibility, as their flexibility was not at the same level as workload variability. In such a situation, it is important that prioritization is implemented successfully so that workers can perform the proper tasks at the right time.

Some interviewees saw workload as one of the major challenges in the operation of the process. The focal points were uncertainty and poor traceability of the workload, which led to the incorrect allocation of resources to tasks. In addition, the variability of the workload was considered another challenge. To reach this focal point, it would be important to have real-time information on the workload at distinct stages of the process and on the whole process to resolve potential bottlenecks.

The company considered it important to monitor the lead times of the OTD process and set target times for service product lead times. The lead times of the OTD process were also linked to the reward system. The company faced challenges in defining target times and measuring the real lead times of the products. The definition of the target times was perceived as ‘loose.’ Their actual measurement was performed manually based on a specific sample, and the results were presented as an average, which did not paint an objective picture of reaching the target.

Information acquisition was another focal point of the process that complicated day-to-day management. Its main challenges were that information was scattered in several places and difficult to find, information traceability was conducted manually and case by case, and information had poor reliability. Information on the needs of employees and management was located in several systems, and finding the right information required time and effort. There were also perceived shortcomings in the reliability of the information. When analyzing the shortcomings concerning information reliability, discrepancies in the information available to different stakeholders were also noticed.

Human factors, the last focal point, include employee ability and internal communication. The company saw that various internal factors brought variation to the process and made it unstable. One reason for this was the different skill levels of the employees. Some of them found using information systems and finding information easy, while others found it challenging. In addition, various communication and information-sharing problems affected the process.

4.3. Design of a real-time measurement system based on digital visualization

The first major step in performance measurement is designing the measures. In this part of the study, we developed our design proposals for real-time performance measurement based on the DV of the OTD process of industrial service. When designing a performance measurement system and facilitating its successful implementation, a company’s employees, processes, infrastructure, and culture must be considered. As part of the design process, we identified the focal points of the OTD process to maximize the benefits of real-time performance measurement based on DV (Table 2).

In the designing phase, the information needs were analyzed, which revealed that information needs differed between users at different stages of the OTD process. In addition, information needs vary between management and operators and between departments, and they were classified as product-specific, process-specific, user-specific, customer-specific, and supplier-specific. From the research point of view, process-specific information needs were prioritized. The needs varied depending on the employee’s job description and position in the company. For example, operators focusing on their own process-stage tasks were more interested in information on individual maintenance products, while the company management was interested in comprehensive information on all the maintenance products of the process, whereas the sales department was interested in sales indicators and product-tracking information.

When developing design proposals for real-time performance measurement based on the DV of the OTD process of the industrial service, we also considered the case company’s existing measures and measurement systems. The company was using the balance scorecard, which was linked to the maintenance service business. One measure of the OTD process of the maintenance service focused on measuring the lead time of the first stages of the OTD process. Measuring the lead times was performed manually using a specific sample, and the results were presented as an average, which did not offer an objective picture of reaching the target. In addition, the measurement information was always presented from a historical perspective, in which case the real-time information on the functionality of the OTD process was not available. Other indicators related to the operation of the OTD process were employee satisfaction measures (happy or unhappy), process deviation measures, work safety measures, random customer satisfaction surveys, and various automatic reports from the information systems. In addition, the sales department has its own measures that reflect the sales situation, the sales budget, the number of sales initiatives, the lead time of order processing, and the number of email orders. The focus on the company’s current measurement was mainly from a historical perspective. The sales budgets and sales forecasts, which were done manually, gave an idea of future operations. Overall, the measurement of the OTD process of the maintenance service was more of a management tool, and the employees felt it was removed from their daily work: ‘We get virtually no information on anything and there are no indicators visible to us anywhere.’

The results of the designing process were obtained considering the focal points of the process, the information needs of the different stakeholders, and the company’s existing measures and measurement systems. The designed measures, shown in Table 3, were divided into seven dimensions – maintenance product, resources, workload, warehouse, process, employees, sales and finance, and customer. In addition, they were classified into three measurement entities.

Table 3. Visualization framework for real-performance measurement: Entities, dimensions, and measures.

Dimensions	The designed measures (entity 1)	The designed measures (entity 2)	The designed measures (entity 3)
Maintenance product	Specific product information Type, category, etc. Type of maintenance Basic maintenance, extensive maintenance, re-manufacturing, scrapping, etc. Process steps information Current status (e.g. received, disassembled) Status change Timeline of status progression Lead times compared to target times Location Spare parts and subcontracting information Ordering information Arrival information
Resources		The amount of human resources required Weekly, monthly Assembly, disassembly Resource availability People, machinery Rate of reserve	Workload compared to capacity
Workload	Waiting lists Workload Work hours Number of maintenance products	Future maintenance
Warehouse			Number of products Work in progress Product position and status WIP Status of warehouse locations Free/booked
Process	Lead time Individual Product categories Overall Offers On-time deliveries	Deflection information Internal Customers Suppliers Jobs other than the basic process	Performance Productivity Overall Personal 5S Safety/accident Flexibility Employees Organization Specific theme information
Employees		Presence At work/away On holiday Business trip	Employee satisfaction Capability
Sales and finance		Orders received Order book Billing Profit margin Maintenance-specific Salesperson-specific Overall	Sales forecasts Upcoming maintenance Need for extra resources Sales budgets Track achievement Salesperson-specific customer development Economic outlook Net sales Costs Profitability Operating profit
Customer			Reclamation Customer feedback

The first entity is composed of measures that help implement real-time monitoring of the products and the OTD process. They provide information on the product under maintenance, the product status/phase, the product location, the product progress in the process, the lead times of different stages, and the workloads in different stages. All the stakeholders considered information on this aspect important in helping to conduct their process-stage tasks. The second entity comprises measures related to the profitability of the maintenance function, providing more detailed information on the situation and functionality of the OTD process. More detailed measures provide information on the resources of the process, future maintenance, deflections in the process, the presence of employees, and sales. The third entity comprises measures that are less significant in the real-time monitoring of the OTD process; they play a complementary and supportive role in managing the process, offering information regarding the safety of the process, the satisfaction of the stakeholders, the overall performance of the process, and so on.

5. Discussion of study outcomes and propositions

5.1. Performance measurement in the context of an OTD process

In existing performance measurement theories, it is widely accepted that process characteristics must be acknowledged in the design of performance measurement. For example, according to Garengo et al. (2005), actions should be taken to replace functional performance measurement with process-related measurement. Moreover, van der Aalst et al. (2016) suggested that a variety of key performance indicators (KPIs) (i.e. process performance measures) could be used to measure process improvements. These process-specific performance measures can be considered quantities that can be clearly determined for a specific process, providing that the calculation data for these performance measures are obtainable (Dumas et al., 2013) and they can be divided into different dimensions, such as cost, time, flexibility, and quality (van der Aalst et al., 2016). However, the results of the current research show that the gap between understanding the process characteristics and performance measurement is too wide. According to our study, prior to the definition of process characteristics (the context of the OTD process in this study), the essential focal points of the process should be determined, as they direct and guide the overall performance measurement process. The focal points describe the points of the process on which the measurement should specifically focus to maximize the benefits of DV-based real-time performance measurement. This research shows the importance of understanding the salient focal points of the process to be able to manage the entire process through DV-based real-time performance measurement. For this reason, the first proposition of the study is as follows:

P1. Determining the focal points on which real-time, DV-based performance measurement focuses facilitates the implementation of the performance implications of the OTD process.

This study contributes to performance measurement research by presenting the focal points of the OTD process in which DV-based real-time performance measurement should be considered by a company. The OTD process with different stages contains large amounts of production data and involves multiple parties from different business areas – making it complex to manage (Zhang et al., 2010). The process thus requires efficient planning and control to minimize failures that could cause delivery delays and service errors. This is where digital twins, by enabling process monitoring and control in real-time, can revolutionize the manufacturing industry (Qi et al., 2021).

The results of the present study reveal that, due to the complexity of the OTD process, its effectiveness and efficiency can be developed by using DV-based real-time performance measurements for its prior phases. According to Bititci et al. (2016), visualization, as a part of the management activities of companies, supports strategic actions, promotes performance management activities, engages people, enriches collaboration, enhances communication and integration, and promotes a culture of continuous innovation. This is supported by the results of this study in terms of the focal points on which the measurement should specifically focus when developing the process to maximize the benefits of the DV-based real-time performance measurement. The observed external and internal focal points enhance this stream of research by classifying the external focal points as customer impact on the process, supplier impact on the process, and fluctuations in demand in the industrial service business, and the internal focal points as interfaces between departments, non-basic operations, resources, workload, lead times, information acquisition, and different human factors. Further, this study reveals that the benefits of DV can be enhanced by integrating the system into other inter- and intra-organizational systems. This includes integrating the continuous development of the company, including taking into account the roles of customers and suppliers. This is in line with Eaidgah et al. (2016), Nudurupati et al. (2016), and Kamble et al. (2020). Eaidgah et al. (2016) concluded that visual management can offer an efficient solution to foster the flow of information, and for its benefits to be maximized, it should be integrated into the company’s performance management and continuous improvement activities. Nudurupati et al. (2016) stated that technological development will require companies to refocus their performance measurement initiatives to cover networks of several stakeholders. Moreover, Kamble et al. (2020) stated that novel technologies can support the collection and sharing of information in the supply chain context.

It was concluded that focal points must be determined for the measurement of the OTD process to be adequate. Once the focal points are determined, then the measurement entities and measures of the process can be defined by considering a company’s workers, processes, infrastructure, and culture to facilitate the successful implementation of a performance measurement system. This study shows the measurement entities that produce benefits for a company when introducing real-time performance measurement based on the DV of the OTD process. This perspective offers a theoretical contribution to the literature on visual management systems and its notion that visualization has several supportive functions in performance measurement (Al-Kassab et al., 2014; Bititci et al., 2016; Fan et al., 2021; Robert et al., 2022). van Assen and de Mast (2019) showed that visualization combined with performance management and measurement should be an infrastructural practice that strengthens an organization’s overall condition. The results of the present study complement past study results by demonstrating the applicability of DV-based real-time performance measurement in various aspects of a company’s operation process. The entities are related to the products and the OTD process, the profitability of the entire maintenance function, and the complementary and supportive initiatives in managing the process.

The study also highlights the information needs of different users at different stages of the OTD process. An evaluation of the outcomes revealed that information needs differed between users at different stages of the OTD process and that, in addition, information needs varied between management and operators and between departments. This is also reflected in previous research that suggested that real-time performance measurement is applicable for different levels of operation, such as employee-level performance measurement (Horváth & Szabó, 2019; Škec et al., 2017), team-level performance measurement (Robert et al., 2022; Y. Yin & Qin, 2019), firm-level performance measurement (Horváth & Szabó, 2019; Wetzstein et al., 2008), and performance measurement in supply chains (Dweekat et al., 2017; Kamble et al., 2020; Nudurupati et al., 2021). The present study revealed that information needs were either product-specific, process-specific, user-specific, customer-specific, or supplier-specific. This is in line with Nudurupati et al. (2016), who found that traditional measures should be supported by behavioral measures that reflect the level of engagement of various stakeholders, and with Garengo et al. (2005), who asserted that actions should be taken to replace functional performance measurements with process-related measurements. In summary, the designed measurement entities will help the case company obtain the benefits of the real-time performance measurement system based on DV and to respond to the focal points and information needs of the OTD process, thus supporting continuous improvement of the process.

5.2. Interplay between performance measurement and digital visualization of process management

We studied the development of a DV-based OTD process measurement method. Our evaluation of the outcomes highlighted an interplay between performance measurement and the DV of process management. In this study, we considered DV as a tool for implementing performance measurement, and the OTD process as a context in which performance measurement takes place. Our study experience revealed interesting synergies between performance measurement with DV and process management. Past studies have noted that the utilization of visualization techniques in process performance measurement positively affects management activities (e.g. Al-Kassab et al., 2014; Bititci et al., 2016; Holopainen et al., 2021). As part of the management activities of companies, visualization supports decision-making (Al-Kassab et al., 2014), promotes communication (Bititci et al., 2016; Eaidgah et al., 2016; Larsson et al., 2017), enhances information flow (Eaidgah et al., 2016), and supports continuous improvement (Bititci et al., 2016; Eaidgah et al., 2016; Holopainen et al., 2021; van Assen & de Mast, 2019). Recent studies have also highlighted the potential of technological developments in process management (Horváth & Szabó, 2019). Creatively using novel technologies has been suggested as one way to effectively manage processes and to enable the rapid reactive ability of performance measurement systems (cf., Horváth & Szabó, 2019; Robert et al., 2022; Y. Yin & Qin, 2019).

Our research combined process management and measurement with DV. An evaluation of the outcomes revealed the impact that the interplay between performance measurement and DV had on the management and measurement of the OTD process. While performance measurement provides relevant information on performance, its implications are traditionally determined by its use (i.e. performance management). Our findings revealed that the combination of performance measurement and DV can significantly affect behavior. As previous studies have shown, visualization positively affects management activities and behavior (Al-Kassab et al., 2014; Bititci et al., 2016; Eaidgah et al., 2016; van Assen & de Mast, 2019). With our research, we update this existing theory by showing that DV-based performance measurement itself brings management effects without human intervention directing operational activities. When metrics are displayed and visualized in an easy-to-understand format visible to all process stakeholders in real time (e.g. Robert et al., 2022), measurement information is utilized more efficiently, and the measurement effect is self-evident without managers’ influence. Thus, the implementation of performance measurement is facilitated through the utilization of DV. Research has demonstrated that the implementation of DV to improve the applicability of performance measurement has resulted in more effective performance management of the OTD process. Thus, the second proposition of the study is as follows:

P2. The performance implication of an OTD process is the result of an appropriate interplay between real-time performance measurement and digital visualization.

The development of ICT and visualization techniques present an effective way to leverage DV to support the management of process performance (Bahrar et al., 2021; Fan et al., 2021; Zhong et al., 2017). We propose that the DV of the OTD process by utilizing, for example, digital twins, is an excellent initiative for real-time performance measurement, as it offers process information and KPIs in real time (Aheleroff et al., 2021; Holopainen et al., 2021; Qi et al., 2021). Regarding the case company, the focus on its current measurement was mainly from a historical perspective; the process information was always presented from a historical perspective, which means that real-time information on the functionality of the OTD process was not available. In addition, the measurement of the OTD process of the maintenance service was more of a management tool, and the employees felt that it was removed from their daily work. Our study experience showed that DV could be a powerful tool for implementing performance measurement and developing an OTD process. As a tool, DV enables a company to implement real-time and automated performance measurement, provide easy-to-use information to various stakeholders, facilitate real-time process monitoring and control, and improve management in the context of an OTD process.

6. Conclusion

This study examined the OTD process of industrial services through DV-based real-time performance measurement. To explore in what circumstances and how DV should be used for the real-time performance measurement of the OTD process of industrial services, we studied the development of OTD process measurement involving DV. The main contributions of this study are as follows:

First, this study contributes to the existing performance measurement literature. It demonstrates the importance of understanding the salient focal points of the process in order to be able to manage the entire process through real-time performance measurement based on DV. Determining the focal points which DV-based real-time performance measurement focuses on facilitates the performance implementation of the OTD process. Identifying the focal points of DV-based performance measurement constitutes this study’s contribution to performance measurement research. The study also confirmed that DV is a powerful tool for enhancing the performance measurement of the OTD process, as the implementation of DV to improve the applicability of performance measurement results in more effective performance management of the OTD process. The performance implication of an OTD process is the result of an appropriate interplay between real-time performance measurement and DV. Performance measurement via DV itself produces management effects without human intervention, facilitating the transition from performance measurement to performance management. The study thus contributes to performance measurement research on the use of novel technologies to enhance decision-making and management.

Second, several studies have demonstrated the benefits of visual management systems. In this study, a DV system that combines performance measurement and visual management was evaluated. The designed measures, it was found, produced inputs for digitally implemented visual management. Identifying the measurement entities that produce benefits for a company when introducing real-time performance measurement based on DV is thus a contribution to the literature on visual management systems.

Third, this study contributes to the research on the OTD process in terms of its management and measurement. The study revealed the information needs of different users at different stages of the OTD process. The identified information needs, an important aspect of defining the measures of the process, were classified as product-specific, process-specific, user-specific, customer-specific, and supplier-specific. In addition, they vary between operators, management, and different operations.

A significant novelty of this study is that it directly assessed the operators’ point of view. In addition, examining the voice of workers helped the study avoid possible bias relating to the views of management or the limited visibility of some areas or aspects of the company.

The study also provides interesting opportunities for future research. First, to generalize our findings, future research could include more in-depth case studies on various industrial processes. Another interesting line of research would be an understanding of what elements are emphasized in real-time performance measurement based on DV in various industrial processes; this would be beneficial to provide further theoretical and practical implications. In addition, the effects of real-time performance measurement and related DV on a company’s operations should be clarified in more detail. Finally, since digital twins are shaping the industry (Qi et al., 2021) but are still unknown to many companies, it would also be important to study the different types of digital twins that have been implemented in practice.

Disclosure statement

No potential conflict of interest was reported by the authors.