Guest editorial: Learning capabilities for future work practices

Citation

Svensson, A., Lundh Snis, U. and Bernhard, I.C. (2023), "Guest editorial: Learning capabilities for future work practices", Journal of Workplace Learning, Vol. 35 No. 6, pp. 465-469. https://doi.org/10.1108/JWL-08-2023-198

1. Learning capabilities for future work practices

Learning how to thrive in the new landscape of work and professional contexts, where digitalization and sustainability are two main driving challenges for contemporary organizations, becomes vital. Research indicates that work patterns and jobs will become more digital with a focus on sustainability, where issues of responsibility and empowerment are fundamental (Battistella et al., 2021). This may affect certain groups more than others, which calls for inclusive and multi-disciplinary approaches. Creating conditions and opportunities for innovative approaches of integrating learning aspects in work contexts nowadays also needs to be set in the perspective of sustainability in all three dimensions (e.g. ecologic, economic and social sustainability). The UN Report from May 2021 tells us that it is not too late to make a difference. It calls for a transformative change, a fundamental, system-wide reorganization across technological, economic and social factors, including paradigms, goals and values, but “only if we start now at every level from local to global” (IPBES Chair, Sir Robert Watson). Organizations’ ability to support a sustainable development of both human and technical capabilities will be the outstanding success. Furthermore, how values and efforts regarding employees’ learning capabilities are taken into account when designing and managing the organization’s financial and technical resources will be of special interest.

Knowledge, learning and continuous development of workforce competencies are of vibrant importance for a sustainable society (Battistella et al., 2021). This implies not only knowledge management, together with a critical reflection in action but also commitment and participation in cross-sector and inter-organizational actions. For example, demographic development is a major challenge for the health-care sector, and the artificial technologies are posing challenges for human empowerment and judgement in the industrial sector and in the society (Shahlaei and Lundh Snis, 2022). These challenges call for innovative ways of organizing for new capabilities to learn and innovate (Gjellebæk et al., 2020).

Digital technology fundamentally changes the way organizations operate – the emergence of the new as well as the transformation of the existing – and is often seen as a disruptive driver of change (Drechsler et al., 2020; Kallinikos et al., 2013; Lyytinen et al., 2016). Hence, digital transformation calls for new logics of organizing and learning. Organizing and learning for digital transformation involve the understanding of revolutionary and continuous changes in operations that affect both managers and staff (Svensson et al., 2021; Vallo Hult and Byström, 2022). Billett (2014a, 2014b) reasons specifically about workers who consistently report learning occupational skills in workplaces and/or through the circumstances of work. In particular, the digital transformation presupposes an increased space for different types of learning that are in line with the strategic work of organizing and managing for learning. Substantial and progressive learning is the result of a streamlined and organized approach to build and increase competence at work, step-by-step (Shahlaei and Lundh Snis, 2022).

Besides of the digital transformation, organizations face complex problems that require new information, knowledge and competences to make informed decisions where the outcomes are not known in advance. Dealing with complex issues, learning and collaboration are fundamental in all sectors of society to include various perspectives and competences across organizational borders (Bernhard and Olsson, 2020). Collaboration for organizational learning may be based on inclusion of employees, internal and external stakeholders, a learning climate, trust, transparency, systematic employee development and encouragement for constant experimentation and learning (Battistella, et al., 2021; Bernhard and Wihlborg, 2021; Olsson et al., 2021). Inclusion for organisational learning is here argued to be in line with the intentions for social sustainability (United Nations, 2021).

As working life has become increasingly complex, everchanging and unpredictable, workers face new and growing demands to engage in continuous learning, training activities and formal education. Work-integrated learning (WIL) can be seen as a collective transdisciplinary approach and concept encapsulating a variety of different approaches in understanding learning. Within WIL, in the form of co-production of knowledge inter-professionally means that new learning is achieved in collaboration. This development is reflected in a renewed academic interest and learning at work, where theoretical and practical knowledge as well as experiences are integrated and linked in workplaces (Billett, 2004, 2009, 2014a, 2014b). Mobilizing and coordinating knowledge are a major challenge for innovations as well as to learn in a changing working life (Gherardi, 2009; Nicolini et al., 2016).

Management and organization in digital transformation has proven to be of great importance for whether and in what way WIL activities may sustain and influence work practices. People in organizations are constantly confronted with new and different challenges, requiring learning of new practices, adaption of new strategies and technologies, but also a readiness to leave behind old ways of organizing and working. Hence, studies of how approaches to require learning capabilities about future work practices and how this could be developed and managed need further attention in research.

2. The articles in this special issue

Previous versions of the articles in this first part of the special issue were all presented at the OLKC 2022 Conference of Organisational Learning, Knowledge and Capabilities, 7–9 September, 2022 at School of Business, Economics and IT, University West, Trollhättan, Sweden. The overall theme was “Learning future workforce capabilities for global sustainability”.

The six articles collected in this part of the special issue entitled: “Learning Capabilities for Future Work Practices” bring up many important aspects regarding the role of learning capabilities for future work practices. The two first articles are based on empirical cases from public and private contexts. The next two articles take the point of departure from tripartite collaboration, where learning and co-creation are analysed to derive implications for future work practices and social sustainability. The subsequent article analyses organizational models for smart working (SW) in different environments, whereas the last article develops a method to visually represent data to be applied to empirical cases of workplace learning.

Leading off, the contribution by Alice Mohlin aims both to identify and map contemporary research on advanced technology implementations for problem-solving purposes in the manufacturing industry and to further understand the organizational learning possibilities of advanced technology problem-solving in the manufacturing industry. The author outlines a scoping review, discussed in the light of contradicting learning logics theories, of contemporary research on the subject. Findings show that contemporary research on the subject is characterized by technological determinism and a strong solution-focus. A discussion on the manufacturing industries’ contextual reasons for this in relation to contradicting learning logics shows that a Mode-2 problem-solving approach could facilitate further learning and expand knowledge on advanced technology problem-solving in the manufacturing industry. A research agenda with six propositions is provided. This contribution gives value by providing novel knowledge on the relationship between advanced technology, problem-solving and organizational learning in the manufacturing industry.

The second article written by Ann Svensson, Linn Gustavsson, Irene Svenningsson, Christina Karlsson and Tina Karlsson is a qualitative study with mixed methods. The aim of the study is to explore how professional learning is unfolding in patient-based work in Sweden when a digital artefact transforms their practice. This digital technology is a new tool for identifying a patient's cognitive impairment, transforming and challenging established routines, behaviours and skills in health-care professionals’ work practice. The paper contributes new information connected to professionals’ ability to reflect on changes. Professionals’ knowledge and experience constitute the prefiguration when the introduction of digital tools brings about indeterminacy in the work practice.

As a third contribution, Iréne Bernhard and Anna Karin Olsson explore the benefits and barriers for learning in industrial PhD education through the perspectives of industrial PhD students. The empirical context is a Swedish university profiling WIL offering PhD education in three disciplines. Findings show, e.g. that industrial PhD students are developing practical and transferable skills hence contributing to research of interest for academia and work-life. Their research adds understandings to the emerging field of studies of alternative doctoral education by identifying benefits and barriers for learning and providing recommendations for how university and industry may promote learning in a resilient industrial PhD education collaboration. Furthermore, the study contributes novel and significant insights into an industrial PhD education transforming along with societal needs promoting a future workforce of researchers with skills, new work practices and learning capabilities applicable in the work life of contemporary society.

The fourth article is written by Fredrik Sunnemark, Emil Gahnström, Hedvig Rudström, Erika Karlsson and Per Assmo. The article explores a tripartite collaboration between residents, higher education institutions and local government, as an approach towards social sustainability that involves residents’ interests in local governance. The authors put focus on the co-creation of knowledge and how to examine and develop social sustainability through learning in the work of a joint municipal project. A time-spatial method is applied. By providing a voice to residents through a collaborative working governance arena brings them closer to government. This increases the potential for bottom-up socio-political development through co-creation of knowledge and WIL. The study shows the significance of fostering social sustainability. The authors conclude that the possibility to examine the connections between work and learning within community-based projects is high if co-creation of knowledge is facilitated through a such a tripartite collaboration.

The fifth contribution made by Nunzia Carbonara, Barbara Scozzi and Roberta Pellegrino provides an easy-to-use and powerful tool to assess the organizational readiness to adopt an effective SW, to use a maturity model called SWOR (SW organizational readiness). The model consists of three dimensions, each of them further detailed into two sub-dimensions. In the study, the SWOR maturity model was converted into a Web-based questionnaire, which was applied in a survey conducted on a Local Health Authority in Italy. The paper contributes with several implications; from a managerial perspective, the SWOR maturity model could help companies identify the status quo of the processes, technologies and human resources enablers on an effective SW, and develop a roadmap to achieve a desired “to-be” situation.

The final contribution in this first part of the issue is written by Clay Spinuzzi. It explores a novel method to visually model data generated by qualitative case studies. The author critically examines Max Boisot-s I-Space model that conceptualizes the interplay among knowledge assets used by a population. By using an example from an early-stage start-up company, he comes up with three limitations of the I-Space model:

1. Its theory of information does not account well for how people use representations synchronically for learning.

2. It is a conceptual framework, and the tentative attempts to use it for mapping representations have been used in workshops, not for systematically collected data.

3. It does not adequately bound a case for analysis.

Thus, it can be applied analogically but not directly for mapping representations in qualitative case studies. Based on the review, the author develops criteria for appropriate modeling of meaningful elements in the context of qualitative studies of workplace learning.

With this first part of the special issue, we thank all authors, reviewers and other contributors, and hope that the issue will inspire both researchers as well as practitioners to develop the field of Learning Capabilities for Future Work Practices.