For over 15 years, the concept of Industry 4.0, now transitioning into Industry 5.0, has been a focal point for the manufacturing sector. Yet, the success of companies in embracing digital transformation varies. There are numerous models and assessment tools for assessing digital readiness and maturity. Several models have been developed over the years, but firms also realize no "one-size-fits-all" exists when testing them. Previous studies show that firms must take charge of their own digital transformation (DT) journey to find a path that suits their specific needs.This qualitative paper is driven by a case study supported by a within-case analysis conducted with a heavy-machine industry with fourteen production plants worldwide – data collected from 2020 to 2023. Volvo Construction Equipment (Volvo CE), created Factory 4 Tomorrow (F4T) to address Industry 4.0. The central challenge for the F4T initiative was how to facilitate an inside-outside approach to identify an inclusive maturity model that emphasizes learning and collaboration. A diagnostic of opportunities model was created to aid the organisation’s transformation journey. It aimed to support all plants by evaluating their maturity in digital transformation, identifying gaps, and support in prioritising. Unlike traditional models that assess and compare plant levels, this model aimed to foster awareness and alignment, establishing a shared language. Thus, a unique model was explicitly crafted for the firm. The process of developing the model itself enhanced awareness and alignment. Therefore, this paper explores the development process - failures and successes - to compile a digital transformation maturity model tailor-made to a firm's needs and goals. The objective is to offer comprehensive advice for firms to implement DT initiatives effectively in a way that suits them.
CITATION STYLE
Ericson Öberg, A., Goncalves Machado, C., & Stålberg, L. (2024). Diagnostics of Opportunities – A Dialogue Tool for Addressing Digital Factory Maturity. In Advances in Transdisciplinary Engineering (Vol. 52, pp. 395–406). IOS Press BV. https://doi.org/10.3233/ATDE240183
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