Technology-driven workforce management in multi-utilities

Authors: Luca Giustiniano and Andrea Prencipe (LUISS Guido Carli University – Rome – Italy)

‘The imperatives of technology and organization, not the images of ideology, are what determine the shape of economic society’

John K. Galbraith, The New Industrial State, 1967

Background In some business environments the pressure toward innovation can be very weak (e.g., Hughes, 1983). When competitive pressures are low, so are the ones toward managing workforces, and the organization of work at large. The paper reports an exploratory study conducted in an Italian multi-utility company (ARTIO - fictional name) that, regardless of the absence of traditional competitive pressures, at the end of 2014 decided to undertake ARTIO 3.0 – a courageous project of organizational and technological innovation; in such respect, a vehicle for adopting an aggressive strategy of cost reduction and quality improvement. The financial results achieved – already in 2016 - demonstrated that ARTIO 3.0 not only represented a real strategic breakthrough, enabling a dramatic improvement of the operational and economic performance and value sharing towards several stakeholders (customers, shareholders, employees, suppliers, natural environment), but also a substantial rethinking the company's role and responsibility in its social and economic settings (Henfridsson, Mathiassen and Svahn, 2014; Constantinides and Barrett, 2015).

ARTIO 3.0 is an Information Technology-driven project, designed and implemented in partnership with one of the world’s leaders in ERP solutions (Enterprise Resource Planning), yet based on customized but non-ad-hoc developed solutions. The initiative allowed ARTIO to rethink the whole customer experience via the design of end-to-end processes and the redefinition of the technical and managerial skills needed. This revolution in the operating model required a major organizational redesign based on the complete digitization of both ARTIO’s operational infrastructure and network management processes (redefining its operating model), as well as a radical review its workforce management logic (Work Force Management) and performance measurement system (i.e., Spagnoletti, Resca and Lee, 2015).

Research Methods The study reported in this paper is based on: over 20 in-depth exploratory interviews conducted by the authors across organizational levels (from CEO to field technicians), across company’s functions and business units and with the involvement of external stakeholders too (business partners, investors); a detailed analysis of a massive body on internal documents; the direct participation to internal company’s events. The study presents an extreme case (radical organizational innovation in very static environment, shift from human-based to technology-driven task allocation, from top-down to bottom-up logic in performance evaluation) in which organizational tasks referred to on-the-field workforce management (technicians engaged in utility network maintenance) can be dynamically decomposed, grouped and allocated in a faster and more accurate way thanks to IT solutions (e.g., Burton, Obel and Håkonsson, 2015; Bolton and Foxon, 2015). In particular, ARTIO 3.0 entailed the shift from a human-programmed, static, push-oriented logic of workforce management to a centralized, IT-administered, pull-oriented logic of dynamic task allocation.

Findings and contribution Inspired by the contingency approach, we trust the analysis reported in this research contributes to the ongoing debate about the redesign of workforce management systems several ways. First, the study illustrates that the online task decomposition, recombination and allocation can be executed only under two concomitant

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ex-ante circumstances: (a) the availability of a detailed set of skills that can be associated to any single task (task/skill codification); (b) a repository with all the individual profiles coded according to the same skills (technician’s profile). Second, if the technicians’ daily job is dynamically designed centrally (company’s control room), the role of the first-line foremen (former territorial managers) shifts from technical supervision to competence coaching. That generates, at least in the short run, some liminal effects that the extant literature tends to underestimate (see also Laurey, Berends, & Huysman, 2017). Third, the combination of resource planning and geolocalization allowed the company to capsize the supervision mechanism from reports to territorial managers to automatic production of data by the IT systems, with dramatic implications in terms of workers’ safety (i.e. car’s speed) and performance measurement. Fourth, having their tasks and duties centrally determined (control room), technicians result to be permanently “on call” and with no possibility to define or prioritize their job, or to decide on the interactions with their peers. That unveils a tension between the rational task allocation and the individual engagement with the job and organizational knowledge sharing and learning (Yoo, Henfridsson and Lyytinen, 2010). Fifth, as ARTIO deploys some of its activities in partnership with other organizations providing similar services, the adoption of a novel operational model forced the partner to do the same, spreading the internal organizational design beyond the company’s boundaries. While that could be read as a form of coercive pressure, the partners saw it as a learning opportunity (“ARTIO 3.0 encourage us to get where we already wanted to go”). To this extent, one single organization’s design – and its above- mentioned implications - could contaminate the external environment (Tiwana, Konsynski and Bush, 2010).

Crossing different disciplinary fields, we believe our study emphasizes the “reshaping” quest issued by this call for contributions. In fact, we trust our study to be able to significantly contribute to the extant literature as it shows how technology adoption (ERP solution), organization design (task design/redesign/allocation, mutation of hierarchy, coordination mechanisms) and some practice of human resource management (e.g., skills codification, training, development of coach-related attitude and skills) are inextricably interwoven. Furthermore, the case we discuss presents some significant avenues for future lines of investigation, such as: to what extent artificial intelligence would be able to replace the work analysis and resource allocation that at the moment is administered centrally (control room) but yet based on the human interpretation of the case (task design); how would big data analytics be able to anticipate the local needs of citizen and therefore activate prevention of intervention or a faster response; how wearable devices would be able to increase the accuracy of the data produced during the operations in order to improve control activities (i.e., actual usage of safety tools).

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