Manufacturing Revolution Boosts People Issues: The Evolutionary Need for ‘Human‐Automation Resource Management' in Smart Factories

Stein, Volker; Scholz, Tobias M. Article — Published Version Manufacturing Revolution Boosts People Issues: The Evolutionary Need for ‘Human‐Automation Resource Management' in Smart Factories European Management Review Provided in Cooperation with: John Wiley & Sons Suggested Citation: Stein, Volker; Scholz, Tobias M. (2019) : Manufacturing Revolution Boosts People Issues: The Evolutionary Need for ‘Human‐Automation Resource Management' in Smart Factories, European Management Review, ISSN 1740-4762, Wiley, Hoboken, NJ, Vol. 17, Iss. 2, pp. 391-406, https://doi.org/10.1111/emre.12368 This Version is available at: https://hdl.handle.net/10419/230087 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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SCHOLZ Chair for Human Resource Management and Organizational Behavior, University of Siegen, Am unteren Schloss 3, 57072, Siegen, Germany Driven by significant innovations in manufacturing on the edge of a ‘second machine age’, automation will play a pivotal role in turning the world of work upside down. Digitized manufacturing is fundamentally changing relations between human and machine. The expected symbiosis has not yet been systematically organized, since human resource management has widely ignored the topic of automation. If HRM fails to answer the final call, it will lose its influence in smart factories, ultimately being replaced by other functions. Our theoretically derived concept of human-automation resource management (HARM) discloses a possible way out by specifically tackling the conjunction between humans and machines. We will sketch HARM as the combination of HRM and automation management and, therefore, as the next evolutionary step in the advancement of HRM. After supporting the strategic integration by means of its synergistic benefits, we will determine the tasks HARM is expected to fulfill at the automation-people-nexus. Keywords: human resource management; automation; future of industrial labor; manufacturing; smart companies Introduction: people and the automation of manufacturing –A mutual exclusion? Imagine the smart factory of the future: completely modularized manufacturing processes, monitored, largely data-optimized, with blockchain-based payment flows, and steered by decentralized cyber-physical systems that generate as many autonomous real-time decisions as possible. People from the core workforce as well as from the working cloud create the computerization infrastructure and provide for higher-order decisions, conflict solution, and meaning in terms of business model and value creation. Many people-related challenges arise: from factory layouts and manufacturing interoperability to skill shifts, life-long learning, corporate cultural sustainability, work ethics, etc. Will the interests of robots and humans be played off against each other? Who decides on that? Who can, who will take the lead in transforming smart factories? Ever since our ancestors crafted primitive tools out of stone, innovations in manufacturing have continuously led to changes in the working world, and to work itself. Today, the innovative contribution of technology to manufacturing lies within its automation (Chryssolouris et al., 2008), applying robots (Engelberger, 2012), sensor systems (Meijer et al., 2014), and full software support (Xu, 2012) to advanced production processes (Zhong et al., 2013), material handling (Wang and Shih, 2016), payment transactions (Dieterich et al., 2017), and quality control (Ghosh, 2014). While automation optimizes production processes and allows for transformation towards a knowledge-based society with high energy efficiency, the collateral damage of collaborating robots is the potential destruction of jobs (Worstall, 2013). Similar to the era of industrialization of the 18th and 19th century, the definition of work has been changing and will continue to change rapidly again in the 21st century. Human-robot-teamwork (Nourbakhsh et al., 2005) brings about an increasing determinability of Correspondence: Tobias M. Scholz, Chair for Human Resource Management and Organizational Behavior, University of Siegen, Am unteren Schloss 3, 57072 Siegen, Germany, Tel.: +49 271 740 3228. E-mail [email protected] European Management Review, Vol. 17, 391–406, (2020) DOI: 10.1111/emre.12368 © 2019 The Authors. European Management Review published by John Wiley & Sons Ltd on behalf of European Academy of Management (EURAM) This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. location, flexibility, and efficiency of work (Angerer et al., 2012). In today’s working world free of boundaries and limits (Ohmae, 1990), with the human brain remaining the main source of innovativeness (Brynjolfsson and McAfee, 2012), automation leads to a digitizationoriented shift in the needs of employers (Levy and Murnane, 2012; Collin and Palier, 2015) and thus to a growing imbalance in the supply and demand of required qualifications (Cappelli, 2012). Researchers paint the picture of a race of humans against machines (Brynjolfsson and McAfee, 2011). Sennett (2005, p. 83) even describes working people as afflicted by a ‘specter of uselessness’. Examples such as Foxconn replacing workers with one million robots (Ackerman, 2011) or Watson, IBM’s artificially intelligent computer program winning at Jeopardy, strengthen this belief. Defeated by Watson, the contestant Ken Jennings stated: ‘I, for one, welcome our new computer overlords’(Markoff, 2011). The prevalent discourse structure on the future relationship between humans and robots resembles an either/or discussion (PwC, 2017; Elliott, 2018): when one rises, the other one falls. The protagonists of this either/or view adduce comprehensible reasons: in favor of the humans, researchers invoke that only real people can be creative, judging, socially empathetic, and situationally valuable (e.g., McAfee, 2014; Wu, 2015; Pistrui, 2018), and they refer to the recent failure of Tesla’s fully-automated not at all ‘smart’factory (Edwards and Edwards, 2018). In favor of the robots, researchers argue that only machines can work constantly, error-free, technologically sustainably, and cost-efficiently (e.g., Deloitte, 2015; Wingfield, 2017). Reviewing this discussion, its underlying problem cannot be overseen: it is a play-off against each other, leading to a rather destructive win-lose result or even lose-lose result of the inherent conflict of distribution of work (McKinsey Global Institute, 2017). As it is wellknown from negotiation methods such as principled negotiation (Fisher and Ury, 1981), striving for a winwin-result allows for the combination of the qualities of each side. This gives rise to a synergistic view in terms of a symbiotic both/and relationship of working humans and working robots (e.g., Flemming, 2019), which is still a neglected topic in research, especially lacking a theoretical framework. The research gap consists of the specification of the automation road ahead for businesses in four exploratory fields: (a) the business function/s that organize/s the concomitant transformation; (b) the existence of synergies between working humans and working robots as part of the changing automation reality and of the automation narrative; (c) the task areas for the exploitation of synergies on condition of minimal collateral damages; and (d) the ways to balance the cost of renewal and profitability. However, the literature on the humans’way of handling automated manufacturing from a human perspective is scarce and reflect a distant, apprehensive position: ‘Today, people treat most robots in the workplace like wild lions: caged and approached only by trained staff’(, p. 15). Only a few papers focus on people’s reaction to robotmade decisions (Borenstein and Arkin, 2016; Geiskkovitch et al., 2016), the social and emotional perceptions (Sauppé and Mutlu, 2015), the people’s employability (Davenport and Kirby, 2015), and the competences required to deal with this change (Bremer, 2015; Gallina et al., 2015). They all are rather selective and concentrate on specific points of interest, but without bringing together the theoretical foundation and conceptual clarification of how, in the near future, humans and robots will presumably be working as a team (Beer et al., 2014). Therefore, it will be essential to shape the human role within the automated world before it becomes obsolete. This paper contributes to the existing but scarce literature in both theory and practice. Up to now, general discourse sees automation as a force that will lead to significant turmoil concerning labor, especially as it is driven by technology rather than by the humans. At variance with those opinions, this paper underlines the synergistic potential of combining humans and robots. This understanding signifies the theoretical anchoring in the capabilities-oriented strategic management perspective with the focus on the resource-based view (Barney, 1991). The management of a business utilizes any resources to achieve a sustainable competitive advantage. This competitive advantage is usually based on the combination of valuable, rare, imperfectly imitable, and non-substitutable internal resources (Barney, 1991) and capabilities, best developed as first mover on the market. As knowledge about technological innovations and improvements is quickly circulated, the resource focus nowadays incorporates these accelerating dynamics. Consequently, Helfat and Peteraf (2003) refine the strategic management of organizational resources and capabilities towards the ‘dynamic’ resource-based view. This paper, therefore, evaluates the strategic alternatives of dynamically managing categorially different organizational resources in future labor regimes. Furthermore, we aim at deepening the debate in which the human perspective will retain importance in this context. The human factor will remain the crucial source for creating competitive advantages for a business and for ensuring its social harmony. It is not by chance that human resource management (HRM) has evolved as a business function to concern itself with issues such as work ethics (Sloan and Gavin, 2010), sustainability (Jabbour and Santos, 2008), and responsibility (Shen, 2011), and, therefore, is predestined to answer crucial 392 V. Stein and T.M. Scholz © 2019 The Authors. European Management Review published by John Wiley & Sons Ltd on behalf of European Academy of Management (EURAM) questions regarding the future of labor. But as to be shown below, HRM has thus far failed to evolve as a driver for the definition of a future automation-peoplenexus. This paper’s objective is to outline a fruitful integration of the resource-related management of humans with automation. Our theoretical foundation will substantiate the evolutionary need for functional integration with HRM to include automation, perceive it as a coequal work-related management challenge in future manufacturing companies, and to consequentially bridge the gap between humans and automated systems. As a result, HRM takes the road to being transformed into the integrated corporate function of humanautomation resource management (HARM). We will conceptually design the HARM function including its synergies and tasks, thus discussing its functional significance within smart factories. Outdated: separate business functions as serving key players Automation resource management In the history of manufacturing automation, technological progress transformed the social reality of production systems, with the underlying explanation following the theory of technological determinism (e.g., Blauner, 1964; Smith and Marx, 1994) according to which the cause of change is technology, and its effect is social adaptation. Technological determinism identifies technology as the decisive force behind social change, the key mover in history (Kunz, 2006), and Postman (1992, p. 7) states ‘Theusesmadeoftechnologyare largely determined by the structure of the technology itself, that is, that its functions follow from its form’.Karl Marx who recognized ‘The handmill gives you society with the feudal lord; the steam-mill, society with the industrial capitalist’(Marx, 1971, p.109) already criticized this deterministic view and broadened it towards social productive forces (MacKenzie, 1984). This was seized by industrial sociology, pointing out that any technological system is inevitably shaped and coconstructed by society (e.g., MacKenzie and Wajcman, 1999; Degele, 2002). Nowadays, digitization could once more trigger a change: societal influence is still formative but diminishes with increasing autonomy of applied digital technology and the immersive dependence of the business model on interconnected value chains –a phenomenon that is already coined ‘technological momentum’(Hughes, 1994) in times of early computerization. Current developments in self-driving cars, unsupervised algorithms, and artificial intelligence prompt that technology may become a fully automated actor and at the same time an integral player in shaping the societal consequences. In line with technological determinism, the notion of potentially no longer requiring human interaction at all is rooted in the actor-networktheory, as highlighted by the basic statement that there are ‘only actors –some human, some non-human, some skilled, some unskilled –that exchange properties’ (Latour, 1992, p. 236). Automation represents one of the most influential transformations of manufacturing. Derived from the Greek term ατόματος(automatos: acting of one’sown will, of oneself), associated expectations concern the increase of productivity, quality, process reliability, and labor cost-effectiveness (Mital and Pennathur, 2004; Wünsch et al., 2010; Baily and Bosworth, 2014). While automation has led to more humane jobs (Klotz, 2012) by superseding monotonous or physically exhausting and dangerous work (Brown, 1996), it has nonetheless gained the reputation of being a job killer. Especially science-fiction depicts dystopian futures that often contain sinister automation scenarios –such as ‘The Matrix’from 1999. The factual history of automation paints a different picture. Already the weaving machines marking the beginning of automation at the end of the 18th century, created more new jobs at that time than killing old ones. In spite of ‘technological unemployment’(Keynes, 1963), that is, that some skills became obsolete during industrialization, it is a popular misconception held by workers, unions, and economists that any task that can be performed more effectively by a machine, will inevitably be automated (Frey and Osborne, 2013). This misconception, though undoubtedly containing some truth in terms of structural efficiency enhancement, leaves out the free entrepreneurial decisions concerning work design as well as the necessity of social legitimacy. Researchers expect automation to have a neutral or even positive impact on the labor market (Miller and Atkinson, 2013; BAIN, 2018; World Economic Forum, 2018), with the collaboration of humans and machines to be far superior to human–human or machine–machine (Kelly, 2014; Ford, 2015). In line with Moore’s Law (Moore, 1965), automation seems to be growing exponentially. In our present ‘second machine age’(Brynjolfsson and McAfee, 2014), programmatic concepts such as computer-integrated manufacturing (CIM) from the 1970s (Harrington, 1973), ‘Industry 4.0’,bigdata,andRFIDaimatthe interconnection and autonomous interaction of machines. Those concepts have become an obligatory part of ‘smart’ factory (Radziwon et al., 2014) design. Already a reality (Zuehlke, 2008), smart factories are self-evidently shaping the factory landscape in several countries, for example, in the US (Hessman, 2013), Germany (Bryant, 2014), the Netherlands (Smart Industry, 2014), China (Malkovich, 2015), and South Korea (Ji-Yoon, 2015). They differ fundamentally from classical factories. Machines and Human-Automation Resource Management 393 © 2019 The Authors. European Management Review published by John Wiley & Sons Ltd on behalf of European Academy of Management (EURAM) related manufacturing processes have become more and more ‘intelligent’or ‘smart’(Batchelor and Waltz, 2012) and have begun to open the ‘lion cage’(Dietsch, 2010) in the sense that, in certain fields, humans and machines are already working together in symbiosis (Mertens, 2015) or that smart factories no longer require any human labor at all (Alessi and Gummer, 2014). Automationrelated changes are induced by information systems. They are located at the ‘confluence of people, organizations, and technology’(Hevneret al., 2004, p. 77) which enables them to communicate and interact (Goodhue and Thompson, 1995). Information distribution and data processing are essential for the management of automation, which is still on the verge of increasing in intricacy and complexity. Interestingly, this process itself cannot be automated or outsourced to machines –or, if so,onlytoacertaindegree. We label this process of organizing and managing automation ‘automation resource management’(ARM). ARM is concerned with overseeing, designing, coordinating, and controlling machines and adapting them to the given production systems and corporate business processes. In contrast to traditional operation management, ARM will be essential for every type of organization that depends on information system-driven machines (e.g., computer-aided engineering, CNC systems, 3-D printer, etc.) and will not be limited to the manufacturing industry. Obviously, ARM does not cover the human side of automation, so that it would bear an inherent deficit if put into responsibility as separate silo function. ARM may be fitting for certain operational aspects of the automation, but in a strategic management approach it is barely sufficient. Human resource management People issues tend to follow the narrative of social determinism (Green, 2001) with social shaping (Williams and Edge, 1996) and social construction of technology (Bijker et al., 1987; Winner, 1993). Related theories identify people and their corresponding societal needs as drivers of technological change. Society or social groups attribute meaning to technology and its usage. For this reason, ‘technology is a very human activity’(Kranzberg, 1986, p. 557), influenced by a variety of social factors such as history, economics, and ideology (Giddings, 2006). Following upon this idea, technology has been developed to saturate societies’needs, thus overcoming human limitations (Solus, 2012). Human Resource Management (HRM) tackles the broad range of tasks and problems concerning humans within an organization (e.g., Cascio, 2012; Dessler, 2013). In recent years, information technology and information systems have infiltrated numerous employee-related as well as leadership-related processes. Electronic HRM (e-HRM) and Human Resources Information Systems (HRIS) (Lengnick-Hall and Moritz, 2003; Strohmeier, 2007; Waddill and Marquardt, 2011) reflect the technical digitization of HRM work. Technological progress has concurrently brought along an increase in atypical employment (Bosch, 2004) and labor displacement right up to cloud work (Ruggieri et al., 2016) as well as unemployment, which also needs to be dealt with by HRM. Businesses are trying to become more flexible and adaptable to change by reflecting the supporting role of HRM (Alagaraja, 2013; McDermott et al., 2015) –and not only with regards to the management of IT personnel (Kaplan and Lerouge, 2007). One of the recent foci of HRM lies in the employability of the workforce (McQuaid and Lindsay, 2005; Clarke, 2008; de Lange et al., 2015): modern HRM tries to empower employees to achieve or retain individual qualifications and knowledge-related preconditions for their career or to find adequate employment in the given circumstances. While updated knowledge has grown to be the most important factor for individual employability, technological dynamics are on the edge of rendering updated knowledge obsolete (Majchrzak et al., 2013). Companies are trying to overcome this inherent discrepancy by means of training and development in order to counteract the erosion of knowledge (Sung and Choi, 2014). Particularly focused on automation, human resource development is compelled to match its strategies with the research & development department, which has become a stakeholder of increasing importance to HRM. Especially in the context of smart manufacturing, HRM is facing a potentially dire development. Due to digitization, many work-related processes are to be automated, rendering HR less relevant. On top of the common practice of outsourcing of HR, the HR department in manufacturing companies is sometimes even completely entirely outsourced (Weber and Feintzeig, 2014). HR departments as traditionally separate business functions are seen as being at a breaking point (Heneman, 2013): they can either serve as a lobby for the ‘the human role’as part of this technological world of automation, digitization, and big data (e.g., Scholz, 2017), or become obsolete as something to be replaced by those functions that shape automation via IT and technology. Eroding and even erasing HRM could cause people to fall behind as well. This could show dire consequences as the core functionality of HRM remains essential while dealing with those people issues which are boosted by the revolution of smart factories. Therefore, functional integration of HRM and automation is an evolutionary matter of survival for people issues in cyber-physical systems. 394 V. Stein and T.M. Scholz © 2019 The Authors. European Management Review published by John Wiley & Sons Ltd on behalf of European Academy of Management (EURAM) Theoretical foundation of the integrated ‘human-automation resource management’function The practice of analyzing the effects of automation on human resource management and vice versa is rooted in technology studies (Quan-Haase, 2013). A distinct theory to describe the tangled interaction between technology and humans, however, has yet to be composed (MacKenzie and Wajcman, 1999). Consequently, in order to achieve a better understanding of the interaction of humans and automated technology in smart factories, we require organizational theories to grasp this modern organizational phenomenon. What are the theoretical constituents for the conceptional integration, both in regard to the strategic integration of ARM and HRM towards HARM, and in regard to the operational linkage? And what does theory contribute to the question of social acceptance of this emerging fundamentally changed social system reality? In the following, the strategic anchoring focuses on strategic organizational sense-making, the operational anchoring relies on transaction cost economics, and the social acceptance is linked with new institutionalism. The strategic integration of the up-to now separated functions is required in order to challenge the required transformation in the work environment. Automation will change the way how people will work and which role these people will play in smart factories. Consequently, people will have to understand the necessity of these changes. It must become apparent to anybody within the organization, that it makes sense to automate and, by that, link the HRM function with the ARM function. The theory of organizational sense-making (e.g., Weick, 1995) is tackling this question of how to deal with such a situation by addressing the way people attribute individual as well as collective meaning to their experience, therefore, reducing ambiguity in mutual communication. This theory is especially relevant for the employee perspective from within an organization as it affects the extent to which structural changes within an organization are perceived as rational choices (Schoemaker, 1993). Concretely, pointing out the positive effects of an ongoing automation and the consequential strategic integration of ARM and HRM on the value model of the business strategy, can be used as a way to convince the workforce to accept these changes (Jones et al., 2005) as well as to commit themselves individually (Herscovitch and Meyer, 2002). This leads to the chain of reasoning in which the assumption of the inevitability of the dynamic resource-based view in today’s business world, in particular in smart factories, mandatorily means the necessity of more dynamic resource reconfigurations (Teece et al., 1997). The more categorically diverse resources are available, the more effective the accelerating resource reconfiguration will become. The resulting competitive advantages will be more sustainable since automation-related advantages are fairly quickly imitable, but uniquely combined with human resources, they are not. Additionally, this requires to frame the automation narrative as a credible success story with reasonable, realistic milestones for performance progress. In the course of a sense-making process, people make use of several aspects that lead to a changed interpretation of reality (Weick, 1995): the collective creation of a joint identity as actors, an ongoing process of retrospection and enactment in order to build a new narration on real developments, and a process of shared acceptance of plausible explanatory patterns. The goal is to change the mindset into the idea that collaboration, ‘if we handle it wisely, […] can bring immense benefits’(McCorduck, 2015, p. 51). This organizational sense-making goes beyond the operational implementation of automation by highlighting the strategic importance. From the operational perspective, it is important that the effectiveness expectations are met, that is, that the integration resulting in a single HARM function will turn out to be profitable for the organization. It is necessary to be capable of comparing the increase in efficiency created by integrating human and automation into one distinct function. The transaction cost economics (Williamson, 1981) seem an appropriate approach to tackle this concern. Although bearing in mind that the principalagent-relationship among humans and robots is widely unpredictable and dynamically changing, still, in the transaction cost view, functional integration is profitable (Silverman, 1999) due to several aspects: first, transaction costs for the organization are declining with an increase in standardization. The related standards developed for a smart manufacturing business utilize the potential of humans as well as that of automation (similar to humancomputer-interaction, see Dix, 2009). They are solidified by the constant repetition of processes, drawing a transaction cost profit from a higher frequency of similar coordination tasks (Jones and Hill, 1988). Second, resources that had been untapped before are potentially utilized in new and converted ways: automatic units and robots will possess an abundance of sensors that track a variety of conditions and influences. These sensors track the environment and, along the way, humans as well, transferring them into one single and transaction costeffective steering logic. The better the robots and humans ‘know’each other in advance, the less are the hidden characteristics, the quality uncertainties, and in the end the adverse selection. Third, the minimization of risks, which is to be achieved by integrating both functions into one, leads to the reduction of transaction costs related to uncertainty avoidance (Sutcliffe and Zaheer, 1988). Even though human-robot-collaboration appears to increase complexity at first glance, humans and robots will Human-Automation Resource Management 395 © 2019 The Authors. European Management Review published by John Wiley & Sons Ltd on behalf of European Academy of Management (EURAM) eventually learn from each other (Sklar et al., 1998; Ikemoto et al., 2012), and seeing through some of the hidden intentions will consequently reduce potential risks and therefore transaction costs (Chiles and McMackin, 1996). Fourth, the reduction of information asymmetries (Jensen and Meckling, 1976; Balakrishnan and Koza, 1993) has to be considered. Managing humans and robots separately would be inefficient due to information asymmetry with each of them only having limited information at their disposal, resulting in higher agency costs, while integrating both functions would reduce said asymmetry by uncovering some of the hidden actions such as shirking. In order to address social acceptance (Sagie et al., 1990) of such an emerging social system reality, a discussion about its legitimacy (Suchman, 1995) is necessary. Specifying the question of legitimacy that is part of the new institutionalism (DiMaggio and Powell, 1983), means to ask why it is justifiable that human and automation are unified into one distinct HARM function, especially as this may, supposedly, lead to a loss of jobs. Assessing this legitimacy debate from a meta-level, the tone of the discussion is shifting dramatically in comparison to former times. People no longer only talk about the fight of ‘us against them’–as it had archetypically been propagated by the Luddites, an antitechnological-progress movement of the early 19th century –even though today’s discussion often takes place in a populist fashion, polarizing the ‘race against the machine’(Brynjolfsson and McAfee, 2011). Meanwhile, people’s more positive attitudes towards robots, viewing them as team-members, assistants, or colleagues (Mutlu and Forlizzi, 2008), gives robots a new quality of legitimacy. This is especially the case due to robots’ability to communicate, and their growing symbiotic autonomy (Rosenthal et al., 2012) in terms of multifunctionality that allows modern smart factories to produce many parts needed for their products on their own. Furthermore, botsourcing (Gore, 2013; Waytz and Norton, 2014) reduces the need for outsourcing to lowcost countries. There is an obvious potential that automation leads to a benefit for the employees as well, be it the idea that people no longer have to lift heavy items or that people can work with the robots even better together in a team. Highlighting the benefit from the symbiosis will lead to a basic change in social norms, driving normative isomorphic change, as well as the mimetic isomorphism as the tendency of organizations to imitate expectably beneficial structures (DiMaggio and Powell, 1983), and in the end to an increase in legitimacy. All three theories fill the theoretical void of understanding and integrating the originally separated HRM and ARM functions, and theory-driven highlight the importance as well as the advantages of such integration. Conceptual integration: human-automation resource management Strategic sense: synergy Technological determinism and social determinism ascribe a strong cause and effect logic to the relationship between technology and society. Indeed, the two aspects are not isolated from each other but have shaped each other mutually (Quan-Haase, 2013). In the sense of duality, technology influences society and is influenced by society (MacKenzie and Wajcman, 1999). Both are strongly intertwined and ‘both society and technology […] are made out of the same “stuff”: networks linking human beings and non-human entities’(Mackenzie and Wajcman, 1999, p. 24). They are relational to one another as ‘equal’objects (Bryant, 2011). For that reason, ‘we are no longer looking at just a “technology”and its “users”but the event of their relationships, of their reciprocal configuration’(Giddings, 2006, p. 160). However, it is crucial to balance to these relations and establish a conjoint system of social and technological influences. The goal of such a system is to sustain the delicate socio-technological balance (Solus, 2012). Achieving synergy sounds promising, but in order to gain a realistic picture, it helps to review the existing synergetic interactions between HRM and ARM. One root emerged as the concept of e-HRM. In this framework, information technology was designated to improve the work of HR, however today, IT predominantly drives HR (Ruël and van der Kaap, 2012), and has led to standardization (Voermans and van Veldhoven, 2007) or to outsourcing of the HR function (Farndale et al., 2009). Although e-HRM is not entirely linked to automation, it marks a significant shift of sense-making of the HR function from strategic to operative. Similar developments were observed in the computer-integrated flexible manufacturing systems which were first discussed within strategic HRM (Snell and Dean, 1992), but today are integral parts of operational HR planning (Novas and Henning, 2014). Cyber-physical systems, Industry 4.0, and man-machine interaction are currently researched in the field of strategic industrial & labor relations (Spath et al., 2013) and might result in the organization of operative work process relationship that is up to now covered by ARM. Therefore, HARM makes sense in terms of synergy. One crucial change currently shaping the future relationship between human and robots relate to their communication patterns. In the past, humans have given directives to machines. The general issues were humanhuman-interaction and human-machine-interaction. For this reason, HRM and ARM effectively worked in separation with real interaction between humans and machines at a minimum. In recent years, however, 396 V. Stein and T.M. Scholz © 2019 The Authors. European Management Review published by John Wiley & Sons Ltd on behalf of European Academy of Management (EURAM) machines have been taught to talk to each other, which is known as machine-machine-interaction (Ford, 2009), and, more importantly, to talk back to humans. Machines can ask for help, and are now part of teams (Rosenthal et al., 2012). Figure 1 depicts the shift between these two worlds of communication, revealing the need for new accommodation tools. Something that intensifies this new situation is the machines’capability of learning with or without human help. Training and development are no longer reserved for human employees but are also required for machines. The modern non-human-centric communication network implies that machines can teach humans just like humans can teach machines. Evidently, the traditional and well-established ARM and HRM methods are limited to a certain point of assumed separation while both worlds require a merged function that unlocks the synergistic potentials. This leads to the discussion of ‘symbiosis versus synergy’(Stein, 2014). Symbiosis had been the leading paradigm in creating value from the interdependence of people and computers, as Licklider’s (1960) term ‘man-computer symbiosis’emphasizes. According to this paradigm of mutualism, ‘human operators are responsible mainly for functions that proved infeasible to automate’(Licklider, 1960, p. 4), which leads to a symbiotic co-existence with a clear division of tasks. HARM, however, exceeds the idea of mere symbiosis: the resource management of two different areas is merged into one integrated resource management, causing additional value to emerge from the ‘collaborative advantage’(Huxham and Macdonald, 1992, p. 51), learning effects, the creation of additional knowledge, economies of scope, and the mutual compensation of the other’s weaknesses (Figure 2). Procedurally, it is necessary to recognize demands from both ARM and HRM that have to be accepted simultaneously in the future of an integrated HARM function. A merging process based on the least common denominator has to be avoided on all accounts. Regardless of their former preferences, the two partners will have to pursue the same organizational goals and will have to share their resources, especially information. Information systems will obviously be the major enabler of the HARM merger by improving joint communication and establishing a shared language. Moreover, it is necessary to formulate a joint vision, coordinate strategies, share knowledge, use material resources together, concentrate bargaining power, consolidate the governance of risks, and finally increase the value creation (Tantalo and Priem, 2014). The ‘natural enemies’of this type of synergy are a culture of secretiveness, inappropriate incentive structures, mistrust, dominant employees, and an underdeveloped performance orientation (Gold and Campbell, 2000). Because functional integration is a change process which involves the risk of job cuts, emotional resistance (Ford et al., 2008) is likely to emerge and has to be dealt with by means of a mutual learning process (Dass and Parker, 1999). At the same time, acceptance of the new HARM function has to be created by overcoming former rivalries between ARM and HRM. Integrative and synergistic HARM work has to be practiced especially due to different cultural roots in problem solving. In its ‘competitive acceptance model’(Scholz and Stein, 2013), intercultural management shows how to unveil Figure 1 Shift of communicative interaction between humans and machines Figure 2 Synergistic logic of the merger of ARM and HRM to HARM Human-Automation Resource Management 397 © 2019 The Authors. European Management Review published by John Wiley & Sons Ltd on behalf of European Academy of Management (EURAM) competitive strengths of one culture and apply them to another in order to generate competitive advantages while avoiding cultural clashes. Using the basic logic of this competitive acceptance approach, HARM has to identify competitive strengths of both ARM and HRM and decide which of them should be maintained in HARM, for example automation process management from ARM and skill development from HRM. Operational tasks: automation-people-nexus The prevalent HARM task consists in the integrated configuration of any technological and human resources related to automation. It is oriented towards the essential preconditions needed for the digitization of the manufacturing process in smart factories. This means at least programming, information systems infrastructure such as cloud technologies, and also process and data security (Friess, 2013), the provision of skills, the psychology of human-machine collaboration, and leadership. With regard to this, the related financial investments have to be made. This corresponds to the main objective of creating a resilient automation-peoplenexus while lowering transaction costs. In order to achieve a systemic integration and to fully exploit the synergistic potential, certain critical success factors need to be addressed. Critical success factors are organizational actions that improve the success of the business and increase the competitiveness (Rockart, 1979). Especially in the context of HARM, the critical success factors have to be related to the specific change process requirements at the intersection of humans and robots. In their recent research, de Sousa Jabbour et al. (2018) derive a framework from existing literature focusing on the synergy between Industry 4.0 and environmentally-sustainable manufacturing. While de Sousa Jabbour et al. (2018) are looking at the ecological dimension of sustainability, the model can also be applied to the social dimension of sustainability, as both are crucial pillars for sustainability development (UN, 2005). It contains the following 11 critical success factors that need to be considered for successful synergy: management leadership, readiness for organizational change, top management commitment, strategic alignment, training and capacity building, empowerment, teamwork and the implementation team, organizational culture, communication, project management, and national culture and regional differences. In the following, we will adopt these critical success factors for the operational tasks of HARM integration. 1Enhancing management leadership effectiveness (Samani et al., 2012). Pursuant to the ‘Three Laws of Robotics’(Asimov, 1942), any type of automation has to serve humans unconditionally. According to Brynjolfsson and McAfee (2014), meanwhile, automation has become the leader with decisions made by a robot being superior to those made by a human (Lisi, 2015). It is, therefore, essential to lead a differentiated discussion of leadership design both of individuals and of teams. Humans and robots work ‘elbow to elbow on the shop floor’(Bourne, 2013, p. 39) and team dynamics will be heavily affected. As an interesting example, humans have started to develop emotional connections to robots: some humans even name their vacuum cleaner (a machine) and view it as a member of their household (Biever, 2014). 2 Making the organization ready for change (Jones et al., 2005). Especially for the humans, the transformation of smart manufacturing will be extensive. Work procedures will transform, and many new skills will be required. At the same time, some jobs will become obsolete, new jobs will emerge. It is a time of uncertainty (Magruk, 2016), therefore, it will be essential to tackle individual as well as collective change readiness (Rafferty et al., 2013). 3 Achieving long-term commitment of the top management (Young and Jordan, 2008). Smart manufacturing incorporating HARM integration will lead to extensive changes and, furthermore, will be a long-term project for the organization. It will be decisive, how the top management behaves and communicates their actions to the employees (Dong et al., 2009). Without a long-term commitment to the vision behind HARM, employees will lose faith in this organizational change. 4Aligning integration strategy with the general strategy (Burn, 1993). Especially the development of new technologies in the context of smart manufacturing is often de-coupled from the general strategy and predominately determined by technological necessities. This is dangerous in times of increasing automation as organizations lack competitiveness without a strategic alignment (Avison et al., 2004). The adoption of new technologies requires a fit with the organizational goals and, therefore, strategic fit is essential to sustain organizational survivability. 5Training and capacity building for humans and robots (Katz and Margo, 2013). Job-related knowledge requirements that have become obsolete need to be replaced with knowledge requirements becoming more relevant to the automation of the new smart manufacturing environment. HARM will not only have to revisit all job descriptions but also to accompany all employees in their life-long learning (Mavrikios et al., 2013) and their capability of adapting to new technologies more intensively (Weinberg, 2002; Khanagha et al., 2013), increasing 398 V. Stein and T.M. Scholz © 2019 The Authors. European Management Review published by John Wiley & Sons Ltd on behalf of European Academy of Management (EURAM) problem-overestimating-automation-underestimating-humans95388 (). Pfeffer, J. and G. R. Salancik, 1978. 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