Lean Approach in Knowledge Work

Journal of Industrial Engineering and Management JIEM, 2018 – 11(3): 429-444 – Online ISSN: 2013-0953 – Print ISSN: 2013-8423 https://doi.org/10.3926/jiem.2595 Lean Approach in Knowledge Work Hanna Kropsu-Vehkapera1, Ville Isoherranen1,2 1University of Oulu (Finland), 2Kerttu Saalasti Institute (KSI) (Finland) [email protected], [email protected] Received: February 2018 Accepted: April 2018 Abstract: Purpose: Knowledge work productivity is a key area of improvement for many organizations. Lean approach is a sustainable way to achieve operational excellence and can be applied in many areas. The purpose of this novel study is to examine the potential of using lean approach for improving knowledge work practices. Design/methodology/approach: A systematic literature review has been carried out to study how lean approach is realized in knowledge work. The research is conceptual in nature and draws upon earlier research findings. Findings: This study shows that lean studies’ in knowledge work is an emerging research area. This study documents the methods and practices implemented in knowledge work to date, and presents a knowledge work continuum, which is an essential framework for effective lean approach deployment and to frame future research focus in knowledge work productivity. Research limitations/implications: This study structures the concept of knowledge work and outlines a concrete concept derived from earlier literature. The study summarizes the literature on lean in knowledge work and highlights, which methods are used. More research is needed to understand how lean can be implemented in complex knowledge work environment and not only on the repetitive knowledge work. The limitations of this research are due to the limited availability of previous research. Practical implications: To analyze the nature of knowledge work, we implicate the areas where lean methods especially apply to improving knowledge work productivity. When applying lean in knowledge work context the focus should be using the people better and improving information flow. Originality/value: This study focuses on adapting lean methods into a knowledge work context and summarizes earlier research done in this field. The study discusses the potential to improve knowledge work productivity by implementing lean methods and presents a unique knowledge work continuum to frame previous research and give focus for future research. Keywords: lean, knowledge work, knowledge work continuum, knowledge work productivity, operational excellence 1. Introduction Given increasingly competitive workplace settings, organizations are seeking ways to improve their work methods. The importance and challenge of improving knowledge work productivity has long been discussed (Drucker, 1969; Drucker, 1999b; Holtshouse, 2010), especially since organizations tend to require knowledge more so than physical -429- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.2595 work (Newell, 2015). More complex production systems demand labor that is capable of handling, combining and creating new knowledge (Pyöriä, 2005). The challenge of knowledge work productivity has increased (Drucker 1999a; Laihonen, Jääskeläinen, Lönnqvist & Ruostela, 2012); this is further enhanced by slow economic growth, particularly in Europe. Many manufacturing jobs have moved to China and East Asia in the last decade, and these countries are highly cost competitive, putting more pressure on higher-cost ones to develop their operations. The pressure of cost savings has now moved towards knowledge work, and office workers now face the same challenges as factory workers did a decade ago: their work can be done at lower costs at foreign companies who pay lower wages. As such, knowledge work productivity and efficiency is a key improvement area for many companies. Operational excellence must be achieved not only in factories but also in office settings. Lean methods are a potential approach to solving this challenge (Stone, 2012), and the number of studies about implementing lean methods in different fields have recently increased (e.g. Hadid & Afshin Mansouri, 2014; Gupta, Sharma & Sunder, 2016). However, there is currently no standard method of applying lean values, principles and tools to the knowledge-based workforce, leaving many companies struggling to implement successful lean projects (Staats & Upton, 2011). These projects often fail to deliver value to organizations’ pursuits of productivity, operational excellence and competitive advantage. To employ lean thinking and approaches, it is crucial to understand the context of their application. For instance, the heterogeneity of the workforce makes it difficult to treat all service activities alike (Hadid & Afshin Mansouri, 2014) where knowledge work is only a part of the work. The diverse nature of knowledge work also affects lean implementation possibilities. As such, the key objective is to understand the different characteristics connected to the concept of knowledge work and how these characteristics affect lean implementation. The concept of knowledge work is often lightly touched upon in research articles when discussing the nature of today’s work; instead, such research often focuses on managing knowledge work, not managing the knowledge as a resource, which is typically the focus of knowledge management discourse (Aarons, Linger & Burstein, 2006). In this paper, we examine the definition of knowledge work and identify possible lean applications for improving knowledge work productivity. This paper is organized as follows. The first section presents definitions of knowledge work and knowledge work productivity with research propositions (Ps) that are consistent with the research aims. This is summarized and authors propose a new knowledge work continuum to understand the nature of knowledge work. The research approach section describes how this study was conducted. Then the findings on lean implementations in knowledge work was studied based on the analysis of secondary data. Finally, we conclude the implications and discuss how lean approaches improve knowledge work productivity. 2. Knowledge Work and Productivity The value of knowledge has been widely recognized in what we know as “the information age”. Societies’ and companies’ successes are linked to their use of relevant knowledge, thus making knowledge work critical in many organizations (e.g. Holsthouse, 2010). Although we frequently discuss “doing knowledge work”, the definition of knowledge work is complex and vague in nature (e.g. Pyöriä, 2005); the fact that all work demands knowledge to some extent poses a challenge in defining knowledge work concretely (Iivari & Linger, 1999). In this chapter, the definition of knowledge work is further examined. 2.1. Knowledge Work Definitions Drucker (1969) was the first author to define knowledge work as it is perceived today. The key focus of his definition is that knowledge work’s primary function is managing information. Iivari’s and Linger’s (1999) definition agrees with this and furthermore their knowledge work concept emphasizes a deep understanding the work’s content and outputs where knowledge is as an essential ingredient. As such, Iivari’s and Linger’s (1999) definition is knowledge-centred. Later, Davenport (2005) and Pyöriä (2005) outlined a more process-oriented approach to knowledge work. In their definitions, the real substance of knowledge work lies in its processes, not its results. Knowledge processes and connections in said processes are also regarded invisible and often more dynamic in -430- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.2595 nature than manufacturing work (Staats, Brunner & Upton, 2011). Design work is an example of such work. Table 1 summaries the key aspects of the much-used definitions of knowledge work and their key focuses. Key Focus of Knowledge Work Definition Authors Primary task is managing information. Drucker 1969 The work is based on the handling of the knowledge. Deep understanding of the work’s content. Knowledge is an important output ingredient. Collaborative in nature. Iivari & Linger 1999 Process-based viewpoint of handling knowledge. Davenport 2005; Pyöriä 2005 Dynamic in nature. Knowledge processes and their connections are invisible. Often contains design activities and exploration. Staats et al., 2011 Table 1. Key knowledge work definitions Based on the above the following proposition was developed: P1. In knowledge work, information handling and processing is a primary task and knowledge is the main output. Knowledge work is intangible in nature and sometimes defined as a service (Laihonen et al., 2012). Paton (2009) has assessed that knowledge work cannot automatically be associated to service work, made distinct from manual work, or descriptive of emerging work forms, although the term “knowledge work” is often used incorrectly in such contexts. As such, in many studies (e.g. Toussant & Berry, 2013; Gupta et al., 2016), the terms “knowledge work” and “services” are used synonymously without defining the context of knowledge work, thereby creating an inaccurate impression of what knowledge work is. A typical example is referring to simple office work, e.g. call centre work, as knowledge work even though it is more congruent with the manufacturing process (Bain, Watson, Mulvey, Taylor, & Gall, 2002). 2.2. Knowledge Work Continuum To develop knowledge work practices, we must better understand the nature of knowledge work. The difficulty in defining the concept or structure of knowledge work in general indicates that the work is diverse rather than uniform; it includes tasks that are different in terms of breadth and variety (Holtshouse 2010; Margaryan, Milligan & Littlejohn, 2011). This is also noted as a challenge in studies that seek ways to improve knowledge work performance (e.g. Laihonen et al. 2012; Waters & Beruvides 2012). The knowledge work process can be divided into different types of activities: finding, creating, packaging, distributing and applying knowledge (Davenport, 2005). These activities affect the nature of work and work management, whether it involves repeated activities or handling work without strict control or task descriptions. On the other hand, a person doing knowledge work will face a variety of activities where some tasks are more routine whereas others are more creative in nature (Iivari & Linger 1999; Aarons et al., 2006; Ramirez & Steudel, 2008); these tasks often vary in their intensity (Dahoiee, Afrazeh & Hosseini, 2011) and require multitasking (May, 2005). Staats et al. (2011) clearly states that the descriptive characteristic of knowledge work is its lack of repetition, which posits a decent definition of knowledge work. In addition to work structure (formal vs. fluid, consistency of routines, etc.), personal judgement and expertise are other basic aspects of knowledge work that determine a worker’s control over how an activity is done (Davenport, 2005; Ramirez & Steudel, 2008). When defining knowledge work, it is essential to recognize the role of knowledge itself in the working process. How knowledge is used in work must be understood (Paton, 2009). There is a large difference between someone applying information (e.g. guiding customer in a call centre) or creatively using information for example in developing new products or defining strategy. Knowledge is a primary ingredient in the latter case, but a secondary production factor in the former (Pyöriä, 2005). Davenport (2005) lists many jobs, such as sales, computer -431- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.2595 programming, accounting, medicine and engineering, in which the primary objective is to apply existing knowledge rather than give rise to innovation. The types of ideas handled in core activities also differentiate various knowledge work (Davenport, 2005): is the focus on developing radically new innovations, incremental changes or minor improvements? Such ideas can be clearly tied to different knowledge process activities (Margaryan et al., 2011) that can describe the complexity of the work involved. May (2005) defines knowledge work to be dynamic and complex, requiring strategic thinking and deeper problem solving where the capability processing information and ability handling the abstract sets of information (as opposed to simple transaction-based information) is key. Paton (2009) also states that one definitive criterion for knowledge workers should be their ability to add value to the organization. Collaboration in knowledge work entails the work to be divided between groups or individuals. Very often demanding knowledge work is connected to individual expertise. However, knowledge intensive organizations to succeed in demanding work requires high organizational knowledge, which requires strong experts who can work together in collaborative ways (e.g. Iivari & Linger, 1999; Holsthouse, 2010). Highly knowledge-intensive work may also require greater mobility (e.g. the ability to work in networks) and greater problem-solving skills (Davenport, 2005). Based on the above the following proposition is developed: P2. Knowledge work is multidimensional in nature. Within each dimension, there is wide variation in the essence of knowledge, level of working routines and standards, and persons own role in work. Margaryan et al. (2011) state that one reason why knowledge work concepts and typologies are difficult to apply tend to be conceptual rather than empirical, as they are difficult to fit into real-world contexts. Additionally, the fact that knowledge work is a spectrum more so than a rigid concept is clear when examining different research about knowledge work. Some researchers (e.g. Ramirez & Steudel, 2008; Dahoiee et al., 2011) have presented knowledge work as a continuum, where the basic assumption is that all jobs can be represented by this continuum. The challenge of these continuums is that they must include dimensions that are relevant to all types of work. For example, in Ramirez and Steudel (2008), one aspect of the continuum is physical effort required, but we challenge the relevancy of this factor in real knowledge work. Because of this, we have synthesized various aspects of the continuum based on earlier studies defining knowledge work (Drucker, 1969; Iivari & Linger, 1999; Davenport, 2005; May, 2005; Pyöriä, 2005; Aarons et al., 2006; Ramirez & Steudel, 2008; Paton, 2009; Dahoiee et al., 2011; Margaryan et al., 2011; Staats et al., 2011). By understanding knowledge work as a continuum comprised of different dimensions (Table 2), we can comprehend what type of aspects knowledge work may include. The knowledge work continuum is typically understood to be able to represent all jobs (e.g. Ramirez & Steudel, 2008; Dahoiee et al., 2011). Many authors’ continuums suggest that all work is knowledge work when at least one of the factors in the continuum (those on the left side of the chart above) is more than 0 percent. These viewpoints clearly differ from traditional definitions of knowledge work (Drucker, 1969; Iivari & Linger, 1999; Davenport, 2005; Pyöriä, 2005), where the key focus is the knowledge’s role in the work, the main ingredient of the output, and the process of how knowledge is handled. Knowledge is required in all jobs in terms of how tasks need to be done and how certain tools or machines are used, but jobs entailing tasks and tools are not knowledge work by default. Dimension Continuum Office work Knowledge work Level of routines (process orientation) Systematic Innovative repeatable Formal methods Standard Non-Standard Complexity of task Low High Use of knowledge Apply Create Knowledge as output ingredient Secondary production factor Main ingredient -432- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.2595 Dimension Continuum Office work Knowledge work Type of knowledge Facts, techniques, visions Philosophies, transactions Personal expertise and judgement Low High Role of collaboration/collaborative thinking Low High Table 2. The knowledge work continuum - the eight dimensions Our intention is not to state that all work is knowledge work, but rather underscore the heterogeneity of knowledge work. As a rough simplification, work profiles in knowledge work is presented in Figure 1, where the vertical axis describes the role of knowledge used in work and the horizontal axis the diversity of methods used. The role of knowledge is a combination of the dimensions of Use of knowledge, Knowledge as output ingredient and Type of knowledge (the dimensions are presented in Table 2). Methods is a combination of the dimensions of Level of routines, Formal methods, Complexity of task, Personal expertise and judgement and Role of collaboration. Based on the above the following proposition is developed: P3. The knowledge work continuum condenses the different aspects of knowledge work and provides a framework to understand the nature of knowledge work comprehensively. It proposes a classification where more routine and low complex work should handle as an office work and to more complex, innovative and knowledge output oriented work as knowledge work. Figure 1. Examples of work profiles in knowledge work 2.3. Challenges in Knowledge Work Productivity Discussions about productivity challenges in knowledge work have long been ongoing (Drucker, 1969; Drucker, 1999b; Holtshouse, 2010). Productivity is typically measured as output divided by input. In a knowledge work context, many relevant factors are intangible and qualitative in nature (Laihonen et al., 2012); the processes that transform inputs to outputs are often unstructured and are based on individual’s knowledge and ability to apply learned experiences (Antikainen & Lönnqvist, 2006), outputs are not standardized or even clearly determined, and the quality of worker output cannot be ignored (Davenport, 2005). The difficulty in defining knowledge work makes it more difficult to define productivity inputs, and the factors that can influence quantity and/or quality of output are thus challenging to analyze (Davenport, 2005). In knowledge work, evaluating performance in, e.g. creativity and problem solving, is also difficult but can tie into tangible measures, such as working hours (Davenport, 2005). Paying attention to these challenges, Laihonen et al. (2012) findings that surprisingly little research had been done about measuring productivity in knowledge work, is not so big surprise at all. Drucker (1999b) defined six factors to determine knowledge worker productivity: the task at hand, self-management and autonomy, continuous innovation, continuous learning, quality of output (which is at least important than quantity), and the worker being handled as an asset instead of a cost. In contrast, Antikainen and Lönnqvist (2006) approach knowledge work productivity drivers via a traditional input-process-output model. -433- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.2595 Davenport (2005) states that viewing knowledge work as a process can be an effective way of improving performance. The most common forms of intervention are participatory, incremental and continuous, e.g. much like in Lean Six Sigma. This approach requires work structuring and task definition - what is the focus of work and what is the required quality level. In their study, Davenport, Järvenpää and Beers (1996) found that the methods applied to developing knowledge creation versus knowledge application process can vary and that these types of intervention methods, were somewhat easier to apply knowledge application process than on than knowledge creation process. When a task is defined, Drucker (1999b) states that knowledge workers themselves tackle productivity challenges as part of their jobs. Such behavior points to self-management, continuous innovation and learning. The dimensions of knowledge work productivity are summarized in Table 3 below. Based on the above the following proposition is developed: P4. Knowledge work challenges the traditional productivity definitions. Many aspects of the knowledge work are intangible and thus difficult to measure. However, making knowledge work visible and defining the work makes possible to manage knowledge work productivity. Dimensions of Knowledge Work Productivity Approach Author Task Role of worker Output Management Assessing what the task is Self-management and autonomy, continuing innovation, continuous learning Quality of output Knowledge worker is an asset Drucker, 1999b Quantity Costs and/or profitability Timeliness Autonomy Efficiency Quality Effectiveness Customer satisfaction Innovation/creativity Project success Responsibility/ importance of work Knowledge worker’s perception of productivity Absenteeism Accounting for outputs and outcomes Accounting for profitability, costs, etc. Meeting deadlines, overtime needed, etc. Independence and how many things can be done at once Doing things right; meeting the task’s standards Level of the quality of the work Doing the right things and important tasks Product creates value for the customer Ability to create and improve productivity Overall results of the work; considers decision-making, team interaction, communication, documentation, etc. The importance of performing well at critical times Possible misinterpretation of other standard factors Results of average productivity measures; performing well overall Ramirez & Nembhard, 2004 Inputs Organisational inputs Personal inputs Process Outputs Human capital; innovative potential; organisational standards, practices and routines; information systems; quality of information; networks; time allocation; working environment; aim Motivation; job satisfaction; personal network; personal life affairs; physical fitness Organisation of work; division of tasks; organisation of decisionmaking; clarity of job descriptions; teamwork; knowledge sharing; delays and waiting; ability to affect own work Innovation; quality; utilisation of innovation; time-efficiency; fulfilment of customer’s expectations Antikainen & Lönnqvist, 2006 Table 3. The dimensions of knowledge work productivity 3. Research Approach In this study, we determine that a knowledge worker is a person whose work includes using knowledge intensively in his/her work, but the term is not necessarily a job title. The definition of knowledge work contains different dimensions as described in Table 2. In this study, we want to examine the work where knowledge is the heart of the -434- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.2595 work and the key output ingredient, as opposed to work where knowledge is only a secondary resource and is obtained instead of processed. We focus on studying knowledge work where employees work knowledgeably meaning they can differentiate between complex patterns of data and information and respond based on existing frameworks or personal experiences (Newell, 2015). We are interested in studying the applicability of lean methods, in the following circumstances: •When the knowledge is used for creating customer value •When the work entails problem solving and using knowledge to creating new things •When the work is based on strong personal competence/expertise. We are focusing only on the above circumstances and not interested in studying general lean services that are not indicated to specific types of work or do not focus on the knowledge process. A typical flaw in many lean service studies is the assumption that all service work is knowledge work, even work that is repetitive and simple in nature, although such work may fall into the left side of the knowledge work continuum where the lean implementation handles “service production flow” (e.g. patients) rather than information itself. Our purpose is to examine the potential to use lean applications for improving knowledge work practices. The research is conceptual in nature and makes use of earlier research findings (see Figure 2 for a research process illustration). A literature review was conducted to define knowledge work based on theoretical studies, we can conclude that knowledge work is a continuum. On the next phase, we study lean in knowledge work. We briefly touch upon basic lean philosophies and methods. After that, we summarize and discuss the research done on implementing lean practices in knowledge work and conclude which applications and methods could be especially helpful when implementing lean methods in knowledge work. Lean implementations in knowledge work were studied using a literature review. The review was done on the Scopus database and entailed searching for joint keywords “lean” and “knowledge work” in titles, abstracts or keyword fields. No other criteria were set. The search yielded 24 results. Due the low number of original publications, other searches with the same search terms were made in different databases (Web of Science, Ebsco and ProQuest) to assess the search’s validity. These additional searches did not return any additional articles for review. At first, the duplicate articles were removed. The next studies were eliminated from the review if they barely examined lean methods at all, as were articles in which knowledge work was only mentioned as a generic term without a clear description of how lean principles applied to knowledge work settings, much like in Kobus & Westner’s (2015) literature review that justified further research in lean IT management. A total of eight papers were used for the review, and the results of this analysis are presented in chapter 4.2. This is followed by a “discussion and implications” section in which the study’s implications and limitations are reviewed. Figure 2. The research process -435- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.2595 4. Lean in Knowledge Work 4.1 Lean Principles and Approaches to Knowledge Work The origins of lean philosophy have been widely disseminated by various scholars (e.g. Womack, Jones & Roos, 1990; Hines, Holweg & Rich, 2004; Liker, 2004), with Stone (2012) offering a review of relevant literature about the topic from the past four decades. Japanese management spawned this philosophy, the international Motor Vehicle Program and the management system known as the Toyota Production System (TPS) (Womack et al., 1990; Liker, 2004). Lean thinking combines years of practice and theory. The lean approach is based on the concept of customer value (Womack et al., 1990). “Lean thinking” is a set of principles that emphasize an organization’s actions towards creating value for customers through continuous improvement (Hines et al., 2004). Lean thinking is a cultural change that focuses on utilizing people as efficiently as possible. Lean approaches are still developing, but the main concept of lean, providing value to the customer while reducing or removing activities that do not add value, remains as a base. This can be achieved though techniques called lean tools, which are counter-measures for avoiding or reducing non-valuable activities, things like waste in the processes. Lean thinking as presented by Womack et al. (1990) can be condensed as follows: first, the customers’ values must be defined and understood. Second, their value stream must be plotted to include links between the activities and processes that creates the products customers wish to buy; they must outline the inherent value that ultimately fulfil customers’ requirements. Third, it is essential that there is flow between these linked activities so that there is process which produces the product or the service. Finally, there needs to be a pull in place; this pull refers to customers’ driven demands that control and pull products or services in the value stream. All these essential lean elements must be combined with continuous improvement, which in turn would support the company's operations and lead it towards perfection, operational excellence. In a knowledge work context, these lean thinking principles – which start and end with the customer – must be applied considering the special nature of knowledge work. The definition of value in knowledge work, which customers are ready to pay for, is often invisible and cannot be easily defined. The same problems exist in the concept of value streams and flow, which in knowledge work can be an iterative process consisting of loops. Oftentimes, value cannot be added without loops, and this is especially apparent in collaborative projects where each professional’s work jointly on product or service, and their input increases the value by iterating the final output. This highlights the role of collaboration in knowledge work. A simple example of such work is this journal article, which was co-written digitally by multiple authors, improved upon, and reviewed by journal editors and other reviewers. This research paper is presented to the reader (customer) in the form of a journal article, but its value stream and flow, if mapped, would show many loops and iterations. Finding 1. The Lean approach in knowledge work requires understanding the special nature of knowledge work; however, the universal lean principles can be applied. The lean implementation approach depends on a company’s existing level of organization and operational maturity. Maturity can be evaluated by the maturity model framework (Isoherranen, Niinikoski, Malinen, Jokinen, Kess & Karkkainen, 2016). Although lean approaches have a long history in manufacturing environments, its applications in the field of knowledge work are still young; certain tools and methods are either still developing or do not yet exist. The lean deployment approach needs to be planned according to an organization’s maturity, i.e. ability to adapt and learn. If change resistance is not considered, then the company’s gap in knowledge about lean thinking will likely slow down or prevent the introduction of lean thinking. This problem has been recognized by various scholars (e.g. Staats & Upton, 2011; Shah & Ward, 2007). An important aspect of knowledge work productivity is to view knowledge workers as assets and as those who owning the means of production, since the improvement of knowledge work largely depends on their involvement in developmental work (Davenport et al., 1996; Drucker, 1999b). Finding 2. To implement lean in knowledge work context highlight the role of workers. Lean implementation should thus start from philosophical level involving people rather than implementing specific tools that may also be impropriate to knowledge work context. -436- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.2595 4.2. Previous Research on Lean in Knowledge work Earlier research about lean systems in knowledge work is very scarce (Table 4). The studies are qualitative in nature and follow either case study or action study research protocols, which both support discovering new phenomena. Finding research that focuses on information processing as a key to value creation is challenging, since the context of the knowledge work involved is rarely described well. Kruger (2014) and Toussaint and Berry (2013) do not define knowledge work themselves, but they maintain the viewpoint that work done in the healthcare field is intrinsically knowledge-related. However, May (2005), Staats and Upton (2011), Staats et al. (2011), McDermott and Venditti (2015) and Rachman and Ratnayake (2016) are among the first authors who clearly focused on lean implementation cases where the core is information processing. Year Author Article Title Field of Study 2016 Rachman & Ratnayake Implementation of lean knowledge work in oil and gas industry – A case study from a Risk-Based Inspection project Engineering service (consultancy) 2015 McDermott & Venditti Implementing lean in knowledge work: Implications from a study of the hospital discharge planning process Healthcare 2015 Power & Conboy A Metric-Based Approach to Managing Architecture-Related Impediments in Product Development Flow: An Industry Case Study from Cisco Product development 2014 Kruger Lean implementation in the Gauteng public health sector Healthcare 2013 Toussaint & Berry The promise of lean in healthcare Healthcare 2011 Staats & Upton Lean knowledge work IT services/ engineering 2011 Staats, Brunner & Upton Lean principles, learning, and knowledge work: Evidence from a software services provider SW design/ general perspective 2005 May Lean thinking for knowledge work General; philosophy Table 4. Earlier research on lean approaches in knowledge work Finding 3. Earlier research on lean approaches in knowledge work is scarce. There is intriguing interest to apply proven effective lean methods to tackle knowledge work productivity and development issues. 4.3. Lean Principles and Methods in Knowledge Work Staats et al. (2011) and May (2005) discuss lean implementation in knowledge work on a more generic and philosophical level rather than applying specific tools and methods to a certain case. May (2005) sees that focusing on value, flow and continuous improvement are key lean principles that are also relevant in knowledge work. Power and Conboy (2015), Kruger (2014), Toussaint and Berry (2013) and both of Staats’ (2011) studies also discuss lean implementation holistically and without focusing only on single lean principles or methods. Although maintaining employee respect is a fundamental principle of lean theory, this factor is not seriously discussed in these papers. Toussaint and Berry (2013) are the ones clearly indicating people respect in their study. In other studies, people respect accompanies inclusive lean implementation methods, but is more so interpreted than explicitly indicated in any given case (Staats et al., 2011; McDermott & Venditti, 2015; Power & Conboy, 2015). Another lean principle, creating continuous learning/development culture, is in turn more practically handled. In the field of knowledge work, PDCA or PDSA (Plan-Do-Check/Study-Act), DMAIC (Define-Measure-Analyze-Improve-Control) and other hypothesis-driven methods of problem solving are applied to the practice of continuous improvement (May, 2005; Staats & Upton, 2011; Toussaint & Berry, 2013; Kruger, 2014). Value stream mapping (VSM) and eliminating waste are the first issues typically applied to knowledge work contexts. VSM assists in making intangible work process and tasks more concrete. Many knowledge work jobs tend to be unstructured and broad, requiring task specification while simultaneously presenting other multifaceted -437- Journal of Industrial Engineering and Management – https://doi.org/10.3926/jiem.2595 Shah, R., & Ward, P.T. (2007). Defining and developing measures of lean production. Journal of Operations Management, 25(4), 785-805. https://doi.org/10.1016/j.jom.2007.01.019 Staats, B.R., Brunner, D.J., & Upton, D.M. (2011). Lean principles, learning, and knowledge work: Evidence from a software services provider. Journal of Operations Management, 29(5), 376-390. https://doi.org/10.1016/j.jom.2010.11.005 Staats, B.R., & Upton, D.M. (2011). Lean knowledge work. Harvard Business Review, 89(10), 100-110. Stone, K.B. (2012). Four decades of lean: a systematic literature review. International Journal of Lean Six Sigma, 3(2), 112-132. https://doi.org/10.1108/20401461211243702 Toussaint, J.S., & Berry, L.L. (2013). The promise of lean in health care. 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