Abstract

Industrial maintenance services are seen to be revolutionised in the
near future by the emergence of the fourth industrial revolution and big data.
However so far the adoption of the big data –based innovations in maintenance
has not met the high expectations. Many late adopters that cannot afford to
experiment with big data could benefit from exploiting a resource efficient
technology strategy and adopting lean data –based innovations instead. This
paper studies the challenges of adopting data-based innovations in the context
of industrial maintenance services. A literature-based conceptual framework is
constructed to analyse the main factors influencing big data and lean data –
based innovation adoption under corrective, predetermined, and conditionbased maintenance. Two empirical case examples are used to demonstrate how
the framework can be used to analyse maintenance organisations’ motivation to
adopt data-based innovations.