THE INFLUENCE OF CONTINUOUS IMPROVEMENT ON JOB
DEMANDS AND THE RELATIONSHIP BETWEEN JOB DEMANDS AND
READINESS FOR CHANGE
Harmen Otten S3033430
h.m.otten.1@student.rug.nl
Supervisor Thesis: Oskar Roemeling Co-assessor: Louk Paul
Word count (excluding appendices): 12.233
20-6-2017 Master Thesis MSc Change Management
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Abstract
Continuous improvement is often associated with an increase in experienced job demands. However, the underlying causes of this increase is job demands is unclear. This study investigates these underlying causes. The study shows that demands in terms of time pressure initially increase in the early stages of an continuous improvement approach. Additional tasks beyond existing work, process analysis, and mastering a new way of working appear to explain the experienced pressure. Still, in later stages, time pressure is reduced through process optimization, establishing priorities, and increased transparency. The same transition can be identified for mental load, which initially increases through additional learning requirements, coping with change, and having extra accountability. Yet later decreases, through standardization, structuring of processes to support employees and cooperation. Finally, the complexity of work tasks is reduced through standardization, transparency and simplified process design. This thesis also focused on how job demands influence readiness for change. The findings suggest that job demands negatively affect emotional readiness for change because a lack of time results in resistance and negative feelings. Cognitive readiness for change is positively influenced by job demands in which positive expectations and experience seems to play a moderating role. Finally, the relationship between job demands and intentional readiness can be positive (sense of urgency) or negative (lack of time).
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Table of Content
1. Introduction ... 3
2. Literature Review ... 4
2.1 Continuous Improvement and Job Demands ... 5
2.2 Job Demands and Readiness for Change ... 8
3. Methods ... 10
3.1 Experts and Unit of Analysis ... 10
3.2 Data Collection ... 12
3.3 Data Analysis ... 13
3.4 Quality Issues: Controllability, Reliability and Validity ... 13
4. Results ... 15
4.1 Continuous Improvement and Experienced Job Demands ... 15
4.1.1 Time pressure. ... 15
4.1.2 Complexity of work tasks. ... 16
4.1.3 Mental load. ... 17
4.1.4 Perceptions of increased job demands. ... 19
4.2 Experienced Job Demands and Readiness for Change ... 19
4.2.1 Emotional readiness for change. ... 19
4.2.2 Cognitive readiness for change. ... 20
4.2.3 Intentional readiness for change. ... 21
5. Discussion and Conclusion ... 22
5.1 Answering Research Questions and Developing Proposition ... 23
5.1.1 RQ 1: Continuous improvement and job demands. ... 23
5.1.2 RQ 2: Continuous improvement and readiness for change ... 26
5.2 Implications, Limitations and Future Research ... 28
5.3 Conclusion ... 29
References ... 30
Appendix I: Questions Interview ... 38
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1. Introduction
Organizations in the healthcare sector experience an increasing demand for change and continuous improvement (Jones and Mitchell, 2006). This need for change stems, for example, from continuously changing regulations by the government and insurance companies (Weinstock, 2008). A continuous improvement initiative that is gaining increasing popularity in healthcare is Lean (Mazzocato et al., 2013).
Although Lean in healthcare has positive consequences such as the reduction of waste (Womack and Jones, 1996; Melton, 2005), very few studies examined possible negative impacts of the Lean approach (D’Andreamatteo et al., 2015). In turn, this implies that the current literature of Lean Healthcare lacks insights in possible negative effects. One of these negative consequences is job demands, as Brett and Tonges (1989) found that Lean initiatives in healthcare increase experienced workload. However, these authors did not investigate the reasons (how) of this relationship. In addition to the lack of insights regarding negative impacts of Lean in healthcare, most studies in this field are conducted in hospitals and are not relatable to specialized care settings such as homecare (Mazzocato et al., 2010; D’Andreamatteo et al., 2015).
An important concept during continuous improvement initiatives is readiness for change. Since continuous improvement is an ongoing process of streamlining and redesigning processes (Bhasin, 2012). Cunningham et al.(2002) reported that active jobs positively relate to readiness for change. However, as an active job is characterized by work overload and time pressure (Bakker and Demerouti, 2007; Carayon and Zijlstra, 1999; Karasek, 1979), it is questionable if these high job demands play the same role in readiness for change in continuous improvement initiatives. Job demands “refer to those physical, psychological, social, or organizational aspects of the job that require sustained physical and/or psychological (cognitive and emotional) effort or skills and are therefore associated with certain physiological and/or psychological costs” (Bakker and Demerouti, 2007, p. 312).
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positively influence readiness for change, without investigating the reasons for this. This makes further research in this area necessary (Miller et al., 2006).
Based on the aforementioned gaps in the literature, the following research questions will be answered: 1) How does continuous improvement influence experienced job demands in healthcare and 2) how do these job demands influence readiness for change during continuous improvement?
Therefore, this study contributes to the literature of continuous improvement in healthcare because it gives insights into what causes job demands during continuous improvement. Accordingly, managers will be able to adjust work practices, arrangements and continuous improvement initiatives in order to decrease job demands. In addition, this study makes contributions in the field of workplace contributors to readiness for change since earlier studies in this domain are based on quantitative data (e.g. Miller et al., 2006; Hanpachern et al., 1998). This is the first qualitative study that investigates the relationship between job demands and readiness for change, which enables us to get deep insight into the reasons of the relationship (Eisenhardt, 1989). Subsequently, managers get insights in how job demands play a role during change and how to influence these job demands in order to increase subordinates’ readiness for change.
Besides aforementioned contributions, this study contributes to the literature of Lean Healthcare by focusing on possible negative impacts of Lean (i.e. high job demands), since almost all studies in this context focused on positive impacts (D’Andreamatteo et al., 2015). Moreover, we will conduct interviews in a wide variety of healthcare settings as further research in Lean is necessary in specific settings like homecare (D’Andreamatteo et al., 2015; Mazzocato et al., 2010). This setting is different from hospitals because Lean in hospitals is concerned with improving the patients’ flow resulting in reduced waiting times and shorter hospital stays (Ben-Tovim et al., 2007; Ng et al., 2010). Lean in homecare is not concerned with these issues as care for older people is required until they pass away, making reduced treatment cycle-times less relevant.
Overall, the objective of this study can be summarized as: revealing the reasons of the relationships between 1) continuous improvement and job demands and 2) job demands and readiness for change. This thesis is structured as follows. First we introduce the theoretical framework of this study. Next, the methodology used will be explained. Finally, the results are presented followed by the discussion and conclusion.
2. Literature Review
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2.1 Continuous Improvement and Job Demands
For organizations, reduction of costs and enhancing quality is crucial in today’s competitive environment. That is why continuously improving organizational processes is important for companies to remain competitive (Teece, 2007; Anand et al., 2009). Bhuiyan and Baghel (2005) define continuous improvement as a culture of permanent improvement aiming the removal of waste in all organizational systems and processes. In this way, continuous improvement is characterized by employee involvement in which everyone works together and collaborates in order to create improvements, without large investments in capital (Bhuiyan and Baghel, 2005). The nature of change during continuous improvement can be evolutionary and incremental as well as radical. Organizations that have implemented continuous improvement initiatives face plentiful incremental improvements (Bhuiyan and Baghel, 2005). These improvements are realized by using tools and techniques which constantly search and reduce causes of problems, waste and variation (Bhuiyan and Baghel, 2005). The literature distinguishes between different continuous improvement initiatives such as Lean Manufacturing, Six Sigma, Balanced Scorecard, and hybrid methodologies such as Lean Six Sigma (Bhuiyan and Baghel, 2005; McLachlin, 1997; Shah and Ward, 2003; Linderman et al., 2003; Pepper and Spedding, 2010).
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transportation of patients, booking processes, preparation time for operation and overcapacity (Kollberg et al., 2006).
There are many examples of positive consequences of Lean in healthcare, like enhancing the efficiency, pace, and reducing the costs associated with the administration and assimilation of data that is necessary to run a healthcare organization (e.g. patient information) (Aherne and Whelton, 2010). Lean in healthcare also helps to improve the patients’ flow, resulting in reduced waiting times and shorter hospital stays (Ben-Tovim et al., 2007; Ng et al., 2010; Brett and Tonges, 1989; Weinstock, 2008). A literature review of Mazzocato et al. (2010) revealed that all of the studies included in their study, focused on the successful application of Lean in healthcare. Hence, all of these studies only reported positive results, depicted in Table 1. The reason for showing these positive effects is to emphasize the lack of insights researchers has gained regarding negative effects of Lean. Another important finding of Mazzocato et al. (2010) was the “low number of studies specific to a certain setting and the limited data on contexts” (p. 381).
Effects of Lean in healthcare Study Decreasing errors and missteps
More calm and focused work environment Faster resolvement of errors
Savings of time Enhanced teamwork
Nelson-Peterson and Leppa (2007), Panning (2004). Ballé and Régnier (2007);
Furman (2005); Shannon et al. (2006). Bryant and Gulling (2005).
Fillingham (2007)
Table 1: Effects of Lean in healthcare (Adapted from Mazzocato et al., 2010).
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According to Bakker and Demerouti (2007), “job demands refer to those physical, psychological, social, or organizational aspects of the job that require sustained physical and/or psychological (cognitive and emotional) effort or skills and are therefore associated with certain physiological and/or psychological costs” (Bakker and Demerouti, 2007, p. 312). Job demands and work pressure will be used interchangeably during this study. This because work pressure is defined as “the perception of high job demands that never seem to diminish, that include tight deadlines and that people have a hard time in keeping up with” (Carayon and Zijlstra, 1999, p. 33). Job demands are not negative by itself (Schaufeli and Bakker, 2004). This because job demands can positively influence well-being of employees (Nilwik et al. 2003). High job demands can also stimulate positive emotions such as eagerness and can trigger active problem solving (Crawford et al., 2010). However, job demands become negative when meeting these job demands require much efforts and costs which evoke negative reactions like burnout and anxiety (Schaufeli and Bakker, 2004). As will be explained in the methodological section, job demands in this study are categorized in time pressure, complexity of work tasks and mental load. These concepts are defined in Table 2.
Job demands dimension Description
Time pressure Perceptions that time needed for work is higher compared to the time allocated, which results in time stress (i.e. people need more time than allocated) (Linzer et al., 2000).
Complexity of work tasks “The existence of several ways for accomplishing the task: a means-ends conceptualization” (Terborg and Miller, 1978; Campbell, 1988, p. 42). Complexity arises when there are more possibilities but only one is actually working and when the individual needs to find the best possible course of action (Terborg and Miller, 1978).
Mental load The amount of information processing (Kalsbeek and Sykes, 1967). Table 2: Job demands dimensions.
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costs. This was reflected in the sources for increased work pressure. For example, individual and team targets, whiteboards with individual production results, lack of variety, competing with colleagues and pressure from supervisor (Carter et al., 2013). We might not expect the same impact in healthcare environments, since Lean in healthcare is applied differently as the aim of Lean in this context is not about increasing productivity per se but on improving the quality of healthcare (i.e. increasing patient satisfaction) (Andersen et al., 2014; Weinstock, 2008). This will lead to different sources of work pressure.
2.2 Job Demands and Readiness for Change
Readiness for change is defined by Armenakis et al. (1993) as the “organizational members’ beliefs, attitudes, and intentions regarding the extent to which changes are needed and the organization’s capacity to successfully make those changes” (p. 681). It is a similar concept as the concept of unfreezing (Armenakis et al., 1993; Lewin, 1951) and is a critical factor for employees’ support with regard to the change (Armenakis et al., 1993; Armenakis et al., 1999; Bouckenooghe et al., 2009). Some authors (e.g. Kotter, 1996) have argued that a lack of readiness for change explains fifty percent of large-scale changes that are implemented unsuccessfully (Weiner 2009), which reflects the importance of this concept. Readiness for change is also an important precursor to implement changes in healthcare settings successfully (Hardison, 1998; Weiner, 2009; Kirch et al., 2005). During continuous improvement this readiness for change becomes even more important since continuous improvement is an ongoing process of streamlining and redesigning processes (Bhasin, 2012). This is also reflected in the study of Dickson et al. (2009) who reported that the improvement of patient care depends on the employees’ flexibility to change. Readiness for change consists of three dimensions: cognitive, emotional and intentional (Piderit, 2000; Bouckenooghe et al., 2009). These dimensions are described in Table 3.
Readiness for change dimension Description
Emotional Reflect feelings about changes
Cognitive Beliefs and thoughts employees have with regard to the results of changes.
Intentional Employees’ exertion and energy that they want to invest in the process of change
Table 3: Readiness for change dimensions (Piderit, 2000; Bouckenooghe et al., 2009).
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is about exhibiting “a proactive and positive attitude that can be translated into willingness to support and confidence in succeeding in such an initiative” (Vakola, 2013, p. 98). Readiness for change at the meso-level (i.e. group-meso-level) is defined as collective perceptions and beliefs that the change is required, the organization is able to deal with the change in an effective way, the outcomes of the change will be beneficial for the group and the group has the potential to deal with the change demands (Vakola, 2013). Finally, organizational level of readiness for change (i.e. macro-level) ranges, according to Eby et al. (2000), on a continuum “from viewing the organization as capable of successfully undertaking change (high perceived organizational readiness to change) to realizing that the organization is not ready to be engaged in such an effort (low perceived organizational readiness to change)” (Vakola, 2013, p. 100). This study focuses on the individual level of readiness for change because experts will reflect on individual employees’ willingness to support and their attitudes to changes.
Many studies investigated factors that influence readiness for change (Oreg et al., 2011). For example, employees’ trust in management and perceptions of supervisory and managerial support (Eby et al., 2000; Coyle-Shapiro and Morrow, 2003) and organizational commitment (Madsen et al., 2005) positively influence readiness for change (Oreg et al., 2011). It is beyond the scope of this study to mention all factors related to readiness for change, but it is important to note that the literature is inconsistent with regard to another job characteristic, namely job demands. This because Miller et al. (2006) reported no significant relationship between job demands and readiness for change, while Hanpachern et al. (1998) revealed that lower job demands increase readiness for change. Furthermore, Cunningham et al. (2002) reported that active jobs positively relate to readiness for change. In addition to these opposing results, all of these studies were quantitative, which results in a lack of understanding of the underlying reasons of the relationship between continuous improvement and readiness for change (Eisenhardt, 1989).
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1993; Cunningham et al., 2002, p. 379). Finally, employees performing an active job are more confident about their capability to manage change and are more able to participate during organizational change interventions (Spreitzer, 1995; Armenakis et al., 1993; Beer and Walton, 1987; Neumann, 1989; Cunningham et al., 2002).
We summarized the focus of this study in a framework, depicted in Figure 1.
Figure 1: The focus of this study.
3. Methods
As mentioned earlier, the underlying reasons of the relationship between Lean and job demands, and job demands and readiness for change are not explained in the literature yet. That is why this study aims at theory development. After all, theory development is required “when the literature related to the business phenomenon is still very exploratory in nature” (Van Aken et al., 2012, p. 14.). We selected thirteen experts in the field of Lean in healthcare who will be interviewed. The following sections will give a detailed overview of the experts and how data is collected and analysed. Furthermore, the final section explicitly focuses on the steps taken to improve the controllability, reliability and validity of this study.
3.1 Experts and Unit of Analysis
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Expert Expertise and experience
Mental Healthcare 1 Accomplished Black Belt course. Guided several Lean projects.
Mental Healthcare 2 Accomplished Black Belt course, introduced Lean in multiple teams and guided several projects.
Mental Healthcare 3 Educated and nine years of experience as Lean advisor, provides training in Lean, former board member of the foundation ‘Lean in healthcare’ and accomplished several Lean courses such as Black Belt. Currently working as a program manager of Lean.
Homecare 4 Accomplished a course to learn all tools and techniques of Lean, guides people during Lean.
Homecare 5 Worked seven years as Lean consultant and accomplished AOG School of Management Lean in Healthcare.
Various Healthcare Settings 6
Researcher and implementation advisor in the field of Lean. Coaches people during Lean.
Hospital 7 Educated in Lean Six Sigma, guides Lean projects and provide trainings about continuous improvement.
Hospital 8 Eight years of experience with Lean, writes and publishes books (e.g. management books) about Lean and guided projects.
Hospital 9 Accomplished Green Belt and Black Belt training, guided projects and has experience with a number of analyses. Currently working in an improvement department.
Hospital 10 Accomplished Green Belt and Black Belt training, provide trainings (e.g. Green Belt) and currently guiding own projects.
Hospital 11 Seven years of experience with Lean, introduced Lean Six Sigma, provide trainings (e.g. Orange Belt, Yellow Belt) and performs and guides projects.
Hospital 12 Accomplished Green Belt, performed several projects and currently working as an improvement coach.
Hospital 13 Eleven years of experience with Lean, accomplished several Lean courses (e.g. Yellow Belt, Black Belt) and wrote management book about Lean. Currently working as Lean consultant/coach in order to educate and perform projects and guide people during these projects.
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3.2 Data Collection
Primary data will be used in this study. This data will consist of qualitative data (semi-structured interviews), which is necessary in order to investigate the underlying reason of relationships (Eisenhardt, 1989). That is why qualitative data is useful, since this study targets at revealing how Lean affects job demands and how job demands influence readiness for change, Therefore, thirteen experts in the field of Lean healthcare will be interviewed. The eighteen questions of the interview can be found in appendix I.
Questions about readiness for change are based on the questionnaire developed by Bouckenooghe et al. (2009). These quantitative questions capture the different dimensions of readiness for change (i.e. cognitive, emotional and intentional). Because Armenakis et al. (1976) mention that readiness for change can be assessed through an interview, the questions are converted to qualitative interview questions (Armenakis et al., 1993). Several questions have been selected for conversion for each of the dimensions. This selection process is conducted in conjunction with two MScBA students -with knowledge in the field of Change Management- who were asked which quantitative questions best capture the essence of the dimension. The outcomes of this process were six interview questions regarding readiness for change. For example, “can you give an estimation of the feelings of employees regarding Lean?” covers the emotional dimension of readiness for change. Follow-up questions -such as: “How does work pressure influence this feelings/perceptions/efforts?”- were asked in order to investigate the relationship between work pressure and the different dimensions of readiness for change. The questions regarding readiness for change were asked in the context of a Lean implementation and the continuous changes that results from Lean.
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content was transcribed within 24 hours to reduce research biases (Eisenhardt, 1989). Finally, the interviews of Experts Mental Healthcare 1 and 2 were jointly performed because they work for the same healthcare organization.
Figure 2: Categorization of job demands, based on Van Baardewijk (2007) and De Jonge et al. (1993).
3.3 Data Analysis
After collecting the data, we use some of Eisenhardt’s (1989) recommend steps for data analysis. This implies starting with analyzing (read, code and interpret the interviews) each expert. The coding process consists of inductive as well as deductive coding. Examples of deductive codes are autonomy and standardization. The complete codebook can be found in appendix II. After analysing each expert, these experts will be compared with each other. Based on their different insights, we want to give a more complete understanding of the relationships under study. The results will be compared to conflicting as well as similar literature. Enfolding the literature is helpful because it coerces us to think more creatively and it sharpens the generalizability of this study (Eisenhardt, 1989). Finally, propositions will be constructed, based on the data, that can be tested in future research.
3.4 Quality Issues: Controllability, Reliability and Validity
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presented as accurate as possible (Swanborn, 1996; Van Aken et al., 2012). This is achieved in conjunction with another MScBA-student who was asked to read the results section with a critical look. Based on his comments, results were refined to make them more precise and accurate. Also improvements towards reliability are addressed. Reliability means that the results are “independent of the particular characteristics of the study and can therefore be replicated in other studies” (Yin, 2003; Swanborn, 1996; Van Aken et al., 2012, p. 206). Based on the advice of Van Aken et al. (2012), the interviews are semi-structured (i.e. standardized) and a ‘friendly stranger’ helped with the coding of the results in order to reduce biases of the researcher. These steps make the study less dependent on the researcher, which improves reliability (Van Aken et al., 2012). Reliability is also served because interviews were conducted at different moments in time (i.e. early morning as well as late in the afternoon) to make the study more independent on the different circumstances, which contributes to reliability (Van Aken et al., 2012).
Steps to improve validity, which “refers to the relationship between a research result or conclusion and the way it has been generated” (Van Aken et al., 2012, p. 209), have also been taken. First, construct validity is addressed because the data collection methods measure what they are intended to measure (Van Aken et al., 2012). This because the qualitative questions regarding job demands are based on Likert scale questions that have been validated in Dutch samples of employees in healthcare (De Jonge and Schaufeli, 1998) (see section ‘data collection’). Moreover, the experts that are interviewed have a body of knowledge, expertise and experience in the field of Lean healthcare (Table 4). This implicates that they are able to give well-grounded answers on the questions asked. Finally, all experts reviewed the transcripts of the interview to check whether the content was correct (Braster, 2000). Internal validity, which refers to “conclusions about relationships that are justified and complete” (Van Aken et al., 2012, p. 211), is improved by using multiple theoretical perspectives during this study (Van Aken et al., 2012). This is reflected in this study as we enfold literature and used different perspectives (e.g. psychological and change management) to develop our propositions.
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4. Results
This section presents the results of the thirteen interviews that were conducted. Firstly, the relationship between continuous improvement and experienced job demands (time pressure, complexity of work tasks and mental load respectively) will be discussed. Then, the effect of experienced job demands on the different components of readiness for change (i.e. emotional, cognitive and intentional respectively) will be addressed.
4.1 Continuous Improvement and Experienced Job Demands
4.1.1 Time pressure. The interviews indicated that there is a clear relationship between Lean and experienced time pressure. Most of the experts agreed that Lean increases time pressure because time needs to be invested when Lean is implemented in an organization. Firstly, time is being invested to analyse processes, which is illustrated by Expert Mental Healthcare 2: “It takes time when you stop the process and analyse what is going on. ‘Pulling the cord at Toyota.’ At that moment, it will increase work pressure.” Secondly, time is being invested to learn since continuous improvement requires a new way of working. This reflected in the following quote of Expert Hospital 7: “It is just a new way of working and a new way of learning. Imagine that you are trying out to ride a single-wheeler, that is hard. Initially, it will take more time.” Finally, the extra tasks that are executed during Lean such as day-starts are often performed beyond normal work. This means that Lean is added on top of an already busy job which creates time pressure.
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errors
Expert Hospital 12: “We see a lot of things going wrong, so you will have to execute recovery actions and that is always extra time. […] Lean can help by setting up a process very well, by eliminating all those minor errors and recovery costs.”
Reduced waiting times
and waiting lists
Expert Hospital 13: “The starting point [in that process] was 15 minutes per patient. […] There was an enormous work pressure for employees because it takes about 20 minutes per patient. So at beforehand, you know that […] as the day progresses, you have more dissatisfied patients because they have been waiting longer for their appointment in the waiting room. There […] a project was performed […] to improve the process. [Afterwards] they said: “It is easy to complete it in a quarter, the work pressure is gone […] and we think that […] treatment times can be shortened further.””
Faster resolvement
of errors
Expert Mental Healthcare 3: “We saved few hours of time within each schedule disturbance.”
Removal of waste
Expert Homecare 4: “But Lean can sometimes also provide solutions for high work pressure by […] eliminating waste, which reduces workload.”
Table 5: Process optimization.
The contradictory relationship between continuous improvement and time pressure can be explained by the phase of implementation. There seems to be a clear transition period in which Lean ultimately reduces time pressure, although it is experienced as an increase in time pressure when it is introduced in the organization. Many experts mentioned this transition, for example Expert Hospital 13: “You need a certain amount of time before it gains time […]. But passing the first hurdle... that adds work pressure.[…] You need to take the time in order to really investigate problems, rather than solve it immediately. […] It takes time to perform that and in the beginning some extra time to learn that.” Because time is needed in the beginning of Lean, management support seems to play a moderating role, which is also mentioned by Expert Homecare 5: “[…] and the organization has to make space for that time too, in order to make sure that time is available.” Also other experts mentioned the support of management as an important factor to ensure that less time pressure is experienced during Lean.
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eliminating unnecessary process steps. Simplicity is also achieved by standardization, which is the second reason for a reduced complexity. Standardization can be applied for more simple tasks, such as injecting and administration, as well as for more complex tasks, as explained by Expert Various Healthcare Settings 6: “I think complexity really reduces. […] I think you can apply standardization very well for those standard actions. […] At the same time, for those more difficult tasks ... I think that you can also look at: Which subcomponents can I simply standardize?” Expert Hospital 13 provides a clear example of standardizing these subcomponents in the context of complex tumor treatments: “What kind of gradation of a tumor do you give or not? When and when not? You just have to do that and you have to measure it. […] At one point you can objectively determine that, if a tumor is in a certain advanced stage, it does not make sense anymore. Point. Then that is your standard.” Transparent processes is the third reason for reduced complexity as it is clear what needs to be done during work, which is illustrated by the following quotation: “[…] you will find everything better, processes are more streamlined and it is clear what is going to happen. That ultimately makes it less complex!” [Expert Homecare 11].
4.1.3 Mental load. The interviews illustrate that experts have different opinions about the influence of Lean on mental load. Three experts argue that there is no clear link between these two, while eight experts mentioned that Lean causes less mental load. However, three of these experts -that mentioned a reduction of mental load- also argue that Lean can cause an increase in mental load. Finally, one expert mentioned that Lean only causes an increase in mental load. What we can conclude from this is that the relationship is positive as well as negative. The interviews indicate that an increase in mental load can be explained by three reasons, namely having too much accountability, coping with many changes and the great amount of learning required. These reasons are presented with quotations in Table 6.
Too much accountability
Expert Homecare 4: ““So, besides my regular work, I also need to get my team on track and you also ask whether I want to do the team tasks.” That is how [work pressure] is experienced.” […] “They feel very responsible. […]: “We are the communication channel, we are responsible for our results, we also need to help people who are not going well and, by the way, we have to do another 17 tasks...””
Coping with many changes
Expert Homecare 5: “When you are not very happy with changes, and your standards are removed and you need to do something new while you feel scary, you will really put pressure on the employee's mental load.” […] “Many things are added in one moment while all other work continues. Is that possible? It will definitely increase your mental load.”
Learning Expert Various Healthcare Settings 6: “Well, switching to standards… […] To learn otherwise or to learn again is very difficult.”
Expert Hospital 10: “I notice that Lean is a completely different way of thinking. […] They suddenly have to learn what KPI’s are. […] That takes a lot of energy.”
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As Table 6 shows, it seems that two of these reasons (coping with many changes and learning) are especially relevant in the early stages of Lean. After all, you have to cope with many changes when Lean is introduced and you have to learn a completely new way of working. Therefore, like the relationship between Lean and time pressure, it seems that there is again a transition period in which mental load increases when Lean is introduced, but reduces in the long-term when the organization reaps the benefit of Lean. This is explained by Expert Various Healthcare Settings 6, who mentions that switching to standards and coping with many changes cause mental load in the beginning, but “Lean is based on the removal of […] muri (overburden). Therefore, if you interpret and apply Lean in the right way, then you […] also take any stress/overload signals very seriously.” […] “[…] the idea is that, through Lean, work is better balanced and people are not overloaded with work. […] In short: By better balancing of work and standardization of tasks, but also by better training (as resource), work pressure will decrease over time.” [Expert Various Healthcare Settings 6].
So like in the relationship between Lean and complexity of work tasks, standardization plays an important role in reducing mental load because you have to think about less aspects and hassle, which reduces the amount of information processing (i.e. mental load). Expert 13 provides an excellent example of reduced mental load through standardization by comparing it with driving a car: “[brake in a car] is always left to the accelerator pedal. You always give gas with your right foot, and if you need brakes, you should pick up the right foot of the gas and put it on the brake pedal. Because that is the standard. […] If you do not have standardized that and you drive in someone else's car, you have to think about it all the time: “Where is the brake again?” […] So the mental load of driving in a car with the brake in another place is huge. […] So what you can standardize, you have to standardize. You do not have to think about that anymore.”
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Previous findings addressed different relationships between continuous improvement and job demands. These relationships are visualized in Figure 3. In short, the findings hint at what could be considered a maturity effect in which job demands initially increase when Lean is introduced but, in the long-term, reduce as organizations reap the benefits of Lean.
Figure 3: Proposed relationships between Lean and experienced job demands.
4.1.4 Perceptions of increased job demands. Now it is clear that Lean can increase experienced job demands in the early phases of Lean, it is interesting whether employees perceive this increase as positive or negative. According to four experts (Experts Hospitals 7, 9, 10 and 11), this can be positive as well as negative. Experts Hospital 7 and 11 argue that these perceptions differ per person. “Of course, you have the adopters and the laggards. The adopters like it, want to make time available and are willing to walk a step faster. The other group thinks something like: […] “I really do not work with it”” [Expert Hospital 11]. Four experts mention that employees perceive the increase in job demands as only negative because people are afraid of the extra workload, or they find it complicated or too demanding.
4.2 Experienced Job Demands and Readiness for Change
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Healthcare 3
“If people already [have high work pressure] then sometimes nothing can be add on top of that. So if we ask them: “How would you organize your work in a different way?” They react: “So we have to do this on top of!?””
Expert Various Healthcare
Settings 6
“If you are busy […] then you are less enthusiastic about the change that comes on top of.” […] “Because people just have a lot of work, I think that every time you come up with a development program -whether it is called Lean or otherwise-, it just generates resistance.” Expert
Hospital 7
“We already have no time. I do not do it today because there is no time.”
Expert Hospital 8
“Yes, you will see [negative feelings due to high work pressure] in the early stages of our transformation, which shows that one is especially negative because it comes on top of…” Expert
Hospital 10
“So it really does feel as something extra. That is also the case in the beginning, because you just have to learn another way of working and that takes time.” […] “That is not resistance because they do not want to try it, but because they really do not have time for it.”
Expert Hospital 11
“So much resistance: “it takes too much time.””
Expert Hospital 13
“This cannot be added anymore. It is really impossible that this is added on top of.”
Table 7: Resistance given time pressure
4.2.2 Cognitive readiness for change. Although experienced job demands seem to have a negative relationship with emotional readiness for change, this is different for the relationship between job demands and cognitive readiness for change. Eight experts argue that people with high job demands have more positive beliefs and thoughts regarding the outcomes of Lean and the resulting changes. The main reasons for this are that employees either expect that their work will improve (i.e. lower job demands) when Lean and its changes have been implemented, or actually experience that their work is improved.
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However, this also highlights that changes actually should aim at reducing job demands to create these positive beliefs and thoughts. This is recognized and mentioned by Expert Homecare 5 and Experts Hospital 7, 10 and 11, illustrated by the following quotation: “If you can reduce work pressure by decreasing that complexity, it will of course have a positive effect. If that is not the case, if you cannot quickly show things that improve, then it feels like extra” [Expert Hospital 7].
All in all, it seems to be the case that there is a positive relationship between job demands and cognitive readiness for change, because people have expectations or the experience that work will be improved (i.e. less job demands) due to the change. However, this implicitly suggests that these expectations and experience are moderating variables. Because when a change does not aim at reducing job demands, people will less probably experience or expect that work pressure reduces and, thus, people will have less positive beliefs and thoughts regarding the outcomes of change.
4.2.3 Intentional readiness for change. The relationship between job demands and the final dimension of readiness for change is complicated. This because most experts suggest a positive as well as a negative relationship. Table 8 provides selected example quotations of some of these experts. The table shows that people with high job demands are more willing to invest exertion and energy in Lean and its changes because job demands create a sense of urgency. Furthermore, according to four experts, an environment with low job demands is not an optimal climate for changes because people do not see the need for change.
However, the relationship can also be negative: People with high work pressure do not want to invest exertion and energy in Lean and its changes, because people are too busy and have no time to contribute. The interviews did not reveal when a person wants to contribute due to a sense of urgency, or when he/she does not want to contribute given the lack of time. According to three experts (Expert Mental Healthcare 1, Experts Hospital 7 and 8), it depends on the person (e.g. personality) which ‘route’ is taken. However, further data to determine what kind of personality or character is associated with the positive and negative relationship is missing.
Expert Positive: Sense of urgency Negative: Too busy to contribute Mental
Healthcare 1
“If you couple it with urgency. […] So: “I see that you are very busy, can we look together to make your work more easy?”” […] “People grab it when they see the urgency [of having high work pressure] and the utility that you can improve and that you are supported.”
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Healthcare 3
“If there is [low work pressure] […] you do not think sufficiently about improving constantly.”
““I am already very busy. Ask someone else.” That is what you hear.”
Homecare 4
“Sometimes [high work pressure] is a positive catalyst. […] Then they are very ready and the amount of [work pressure] is a pressure mechanism to get through or to move on.”
“It can also be negative. […]. Because then there is so much pressure to do the things that are being asked. […] Then the pressure is too high.”
Hospital 7
“[When you have high work pressure] you may have the reason to do it. In addition, people with too low work pressure are often completely careless.”
“I think that, initially, you will always get that reaction [“I am too busy to cooperate”].”
Hospital 8
“A high workload can just urge you to say: “We have to do this now to finally get our workload down.””
“No, the high workload means we do not have time to work on improvements. This is all on top of.” Table 8: Relationship between job demands and intentional readiness for change.
Overall, the findings indicate that there are different relationships between job demands and the different dimensions of readiness for change. In short, job demands reduce emotional readiness for change as resistance is created due to a lack of time, whereas cognitive readiness for change increases when expectations and positive experiences are created. Finally, job demands can increase intentional readiness for change because job demands create a sense of urgency. However, intentional readiness for change can also reduce as people are too busy to contribute.
5. Discussion and Conclusion
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5.1 Answering Research Questions and Developing Propositions
5.1.1 RQ 1: Continuous improvement and job demands.5.1.1.1 Time pressure. The results show that time pressure is ultimately reduced by continuous improvement through process optimization, transparency and by establishing priorities. Optimization of processes is expressed in a reduction and a faster resolvement of errors, which reduces recovery time during work. We find support in the literature, as Nelson-Peterson and Leppa (2007) and Panning (2004) found that Lean reduces errors and missteps for employees in healthcare. Furthermore, Furman (2005) and Shannon et al. (2006) revealed that Lean leads to a faster resolvement of errors. Optimization of processes is also expressed by an elimination of waste whereby processes can be executed in a more efficient way, which creates time savings during work. This is not surprisingly given that the ultimate goal of Lean is the elimination of waste (Bhuiyan and Baghel, 2005). Finally, process optimization is illustrated by reduced waiting lists and waiting times, which reduce pressure for employees as full waiting rooms can be perceived as pressure. Also Lodge and Bamford (2008) reported that Lean reduces waiting times, while Hobson (2007) mentioned reduced waiting lists in her study. Earlier studies did not explicitly mention that time pressure is reduced by a reduction or faster resolvement of errors, or a reduction of waste. However, as these factors clearly create time savings it could be assumed that this lead to a reduction in time pressure. Waiting times, on the other hand, lead to time pressure in the study of Choi et al. (2006).
Establishing priorities, the second factor that emerged in the results of this study, reduces time pressure because tasks are prioritized during work. This causes a work environment that is more calm. Also Ballé and Régnier (2007) mentioned that the environment in Lean organizations is much more calm in which people are more focused. Current literature does not associate establishing priorities directly with time pressure. However, setting priorities and goals is a type of time management behaviour (Macan. 1994) which enables employees to “experience control over what can be done” and has, in turn, positive consequences on job-induced tensions (Macan, 1994; Claessens et al., 2007, p. 265). Transparency is the final reason for reduced time pressure, because time pressure may sometimes be unjustified when real time pressure is lower than perceived time pressure. Also Jimmerson et al. (2005) argue that in Lean “problems become more transparent when activities are specified according to content, sequence and timing” (p. 251).
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reaps the benefits from continuous improvement. Also Bessant and Francis (1999) recognized phases, as they revealed an evolution of continuous improvement performance in which five stages can be distinguished. At phase three, organizations start reaping the benefits of continuous improvement and accomplishes, for example, time savings. In contrast, in phase 1 and 2, when an organization is less mature in working with continuous improvement, employees start to participate, develop ideas, train and invest time to learn. Therefore, Bessant and Francis (1999) argue that space and time need to be made available for employees in order to move to level 3. Also Andersen et al. (2014) stresses the importance of the availability of sufficient resources during Lean. Since our results section also highlights that the availability of time to improve and learn can reduce time pressure, we propose management support as a moderator in the experiences of time pressure. Overall, we developed the following propositions:
Proposition 1: Time pressure 1) increases when continuous improvement is introduced and 2) reduces in the long-term, when an organization is more mature in working with continuous improvement and starts reaping the benefits of it.
Proposition 1a: This effect of time pressure is moderated by management support, such that time pressure increases to a lesser extent in the early phases of continuous
improvement with management support, and reduces to a larger extent in the later phases of continuous improvement with management support.
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5.1.1.3 Mental load. The results show that the transition period for time pressure can also be identified for mental load. As an organization introduces Lean, mental load increases as employees have to learn and cope with many changes and get more accountability. It is confirmed in literature that learning is important during change as any change is an information process and requires information (Fiol and Lyles, 1985; Macdonald, 1995). In addition, learning demands working-memory capacity (Kirschner, 2002) and information processing such as information acquisition, distribution and interpretation (Huber, 1991). It is therefore not surprisingly that organizational change is recognized as a stressor for employees (Ashford, 1988; Schweiger and DeNisi, 1991; Judge et al., 1999). Because continuous improvement involves continuous changes (Bhasin, 2012), we might expect that mental load stays at a high level given the amount of learning required. However, the results show that mental load decreases over time. This might be explained by distinguishing higher-level (double-loop) and lower-level (single-loop) learning. The latter focuses on one part of the organization, relies on routines and happens in contexts that are well understood, while higher-level learning focuses on changing overall rules and norms and impacts the entire organization (Fiol and Lyles, 1985; Argyris and Schon, 1978).
In the context of our results, an organization that introduces continuous improvement requires a completely new way of working in which new overall rules have to be learned (i.e. double-loop learning). When employees have learned these new rules and norms, the changes that flow from continuous improvement initiatives focus on small facets within the organization that only require single-loop learning. Although no studies mention that single-loop learning requires less information-processing, this could be assumed given the fewer impact on the organization and because it involves a less cognitive process (Fiol and Lyles, 1985). The results section shows that mental load decreases over time due to standardization, cooperation among employees and structuring of processes to support employees. We again refer to the phases of maturity of Bessant and Francis (1999) to emphasize this maturity effect in the long-term. Also a relief that improvement is possible is mentioned as a way that decreases mental load, but we do not consider this final reason because we do not expect and find no support in literature that this decreases the amount of information handling. Based on the findings and literature, we developed the following proposition:
Proposition 2: Mental load 1) increases when continuous improvement is introduced and 2) reduces in the long-term, when an organization is more mature in working with continuous improvement and starts reaping the benefits of it.
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studies were in their pre-mature phase of Lean and were only in the beginning of the transition period. However, the methodological sections of those studies did not mention when the organization implemented Lean. Only Carter et al. (2013) mentioned it (their case implemented Lean six years ago when studied), but this study was entirely focused on a production environment, which makes it hard to compare with Lean in healthcare (see literature review). Previous findings and propositions are summarized in Figure 4 and are the answer of research question 1. The following section will answer the second research question.
Figure 4 : Proposed relationships between continuous improvement and job demands (RQ 1).
5.1.2 RQ 2: Continuous improvement and readiness for change
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difficult.” (Rundall et al., 2002, p. 960). Resistance to change is an important reason why changes are not successful and can cause negative attitudes to change (Vakola and Nikolaou, 2005). On the other hand, Ford et al. (2008) argue that resistance is valuable because it can be used as feedback. In this way, change agents need to listen to complaints and criticism in order to make adjustments and make improvements to the change.
5.1.2.2 Cognitive readiness for change. The results indicate that job demands are positively associated with cognitive readiness for change. The reason for this is that people with high job demands will expect or experience that work pressure decreases after the change. These positive expectations and experience seems to moderate the relationship between job demands and cognitive readiness for change. This means that the effect is stronger when the change actually aims at decreasing job demands. Otherwise, employees will have less positive beliefs and thoughts about the outcomes of change. Creating positive expectations is very important in order to create change momentum and readiness for change (Eden, 1986; Bernerth, 2004). We further find support by Portoghese et al. (2012) who reported that positive expectations about the change are positively related to commitment to change. This is confirmed by Yuan and Woodman (2007) because employees with positive expectations believe in the benefits that will result from the change. This emphasises the importance of creating positive expectations during change.
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All in all, our findings indicate positive as well as negative relationships between job demands and readiness for change. This conflicts with the study of Vakola and Nikolaou (2005), who showed that work overload is only associated with negative attitudes towards change. In contrast, Cunningham et al. (2002) reported that active jobs is only positively associated with readiness for change, as mentioned before. Moreover, Miller et al. (2006) found no significant relationship between job demands and readiness for change, while Hanpachern et al. (1998) revealed that lower job demands increase readiness for change. An explanation of these different results might be the measure of readiness for change, since all these studies did not distinguished the different dimensions of readiness for change. For example, Miller et al. (2006) implicitly mixed emotional readiness with intentional readiness for change, while our study showed that the relationships between job demands and these dimensions are different. We summarized our main findings in Figure 5, which is the answer of research question 2. In addition, we developed the following proposition:
Proposition 3: The nature of the relationship between job demands and readiness for change depends on the dimension of readiness for change.
Figure 5: Proposed relationships between job demands and readiness for change (RQ 2).
5.2 Implications, Limitations and Future Research
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different dimensions, which might be an explanation for the opposing results. Future studies about readiness for change should therefore take the different dimensions into account. A second implication is that continuous improvement does indeed lead to an increase in job demands, as showed by earlier studies (Brett and Tonges, 1989; Lewchuk and Robertson, 1996; Carter et al., 2013). However, job demands decrease in the long-term when organizations are more mature in working with continuous improvement and start reaping the benefits of it. This emphasizes that a maturity perspective is important and that future studies should try to provide insight into the experience or maturity of the Lean approach. Finally, this is one of the first studies that revealed a possible negative impact of continuous improvement since job demands initially increase.
An important implication for practice is that managers should provide sufficient resources to employees when introducing continuous improvement. Moreover, managers should not immediately stop with continuous improvement when they recognize an increase in job demands, as there seems to be a clear transition in which job demands ultimately decrease. In addition, given the findings of this study, managers should create a sense of urgency in which they emphasize high job demands as a reason to change. Furthermore, in an environment with high job demands managers should first implement changes that have an immediate positive effect on job demands, because this creates positive expectations and experiences. Creating positive expectations can be further strengthened by communicating potential benefits of the change (e.g. reduced job demands). This in turn will have a positive effect on readiness for change.
Some limitations and opportunities for future research are relevant in this study. Firstly, we were not able to capture the real experience of job demands and readiness for change of employees since we only interviewed experts. Future research should address this by interviewing employees that actually work with continuous improvement. Furthermore, we only interviewed experts with experience in healthcare settings. This makes the results not generalizable towards other settings. We recommend further research in other settings, such as manufacturing, to research the relationships explored in this study. Moreover, the propositions provided in this study have to be tested in future research. In addition, our findings did not reveal when job demands ultimately decrease, which is an opportunity for future research. Finally, a limitation of this study is that we were not able to reveal when someone with high job demands contributes to a greater or lesser extent to changes. Therefore, future research is recommend to explore if, for example, personality characteristics are relevant in this case.
5.3 Conclusion
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in Figure 4 and 5. Different theoretical and practical implications and contributions of this study are discussed. Finally, this study provides opportunities for future research. We are convinced that this study has contributed to the currently underexplored areas of continuous improvement, readiness for change and job demands. Hence, we hope that this study encourages other researchers to contribute in order to continuously improve our knowledge in these less mature fields.
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