ATLAS COPCO

Multiple EU countries

Engineering Services for Airpower Technologies
Large industrial service provider


Organisational analytics, HR decision-support tools
Field service engineers, HR professionals
Retention, human-centric HR governance, technology acceptance

Keep new engineers longer by fixing what drives early exits

ATLAS COPCO delivers advanced engineering services for airpower technologies across multiple international customer centres, supporting highly specialised, safety-critical systems. As the company grows, a clear challenge has become more visible: early turnover among newly recruited Field Service Engineers (FSEs). These hires require major investment in recruitment, training and onboarding, yet some leave within a relatively short time.

Within SEISMEC, ATLAS COPCO is addressing this as an organisational and human challenge, not only an HR process issue. The pilot aims to make the real drivers of turnover visible and actionable, empowering both engineers and HR teams with better insight and decision support.

The Challenge

Early turnover cannot be explained by one factor. It is shaped by how work conditions, technology use, organisational practices and expectations interact over time. Traditional measures often focus on recruitment and selection, but that does not fully capture what new engineers experience once the role begins, including technology demands, travel intensity and long-term career expectations. ATLAS COPCO needed a more evidence-based way to understand why turnover intentions develop and how to respond in ways that reflect local context.

The Challenge

Early turnover cannot be explained by one factor. It is shaped by how work conditions, technology use, organisational practices and expectations interact over time. Traditional measures often focus on recruitment and selection, but that does not fully capture what new engineers experience once the role begins, including technology demands, travel intensity and long-term career expectations. ATLAS COPCO needed a more evidence-based way to understand why turnover intentions develop and how to respond in ways that reflect local context.

Workers were part of the design

Co-design is central. A core group of HR professionals from fifteen customer centres worldwide takes part in developing measurement tools, interpreting findings and identifying potential organisational responses. This distributed HR community helps ensure local realities and cultural differences are included, avoiding one-size-fits-all conclusions.

FSE experiences are also brought into the process to make day-to-day realities visible in organisational decision-making, especially where technology use and working conditions affect autonomy, competence and belonging.

How it works on site

The pilot is finalising in the data-collection phase. Early insights already show that turnover intentions are more complex and context-dependent than much of the existing literature suggests.

Why it matters

For workers

For Field Service Engineers, the pilot aims to support better alignment between what is promised during recruitment, what the job actually requires, and what support is available when technology demands and working conditions become challenging. Making experiences visible is a first step towards improving adaptation, reducing frustration and strengthening long-term engagement.

For Michelin

For HR teams, the pilot shifts the focus from “select the right candidate” towards understanding turnover as an outcome of interacting organisational, technological and human factors. This supports more targeted retention actions, grounded in evidence and adapted to local contexts.

This pilot applies Industry 5.0 in practical terms, using human-centric organisational innovation to strengthen retention, technology acceptance and resilient growth in engineering services.

The SEISMEC solution at Kvalitetas

The pilot redesigns work processes using AI, IoT and related tools to increase autonomy, reduce mental load and support better decisions. Technically, Kvalitetas is exploring AI (publicly available in the market) and IoT solutions alongside Manufacturing and Warehouse (integrated into RIVILE GAMA software), Odoo CRM (with AI functionality) Systems to support both management and manufacturing activities.

The tools aim to improve monitoring of production parameters, support inventory and material balance management, improve routine administrative and planning tasks, and strengthen food safety implementation. AI-based tools are also being explored for marketing and communication, including the creation of promotional and educational content that translates scientific and biological product information into accessible messages for consumers interested in functional nutrition and personalised diets.

SEISMEC CAPS factors guide choices and assessment, keeping creativity, automation, productivity, safety and job satisfaction in view.

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