The digitalization maturity models and roadmapping constitute two major research streams guiding companies’ digital transformation enactment. Research on digitalization maturity models is criticized for overemphasizing expert vision instead of empirical evidence, promoting a “one-size-fits-all” approach, and a simplified approach to the development of the digitalization dimensions, which does not take into account their implementation precedence. Roadmapping literature offers a variety of data-driven, expert-based, and hybrid approaches for technology and strategy roadmapping. Current data-driven approaches draw on text mining algorithms and employ topic modelling, link prediction, and other quantitative techniques for generating roadmaps. Given their advantages, such approaches rarely focus on technology development sequences and their characteristics. This paper aims to propose a new kind of data-driven , process mining-enables roadmapping approach for digitalization strategy planning, including a roadmapping method and application directions. A quantitative process mining-enabled roadmapping (pm-DR) approach allows for identifying the fastest digital innovations adoption sequences using longitudinal data on digital innovations diffusion. A case study of the development of augmentation, integration, analytics and automation digitalization capabilities illustrates how to plan a digitalization strategy based on the proposed approach.
Process Mining-Enabled Roadmaps for Digitalization Strategy Planning.
Stefanini A.
2023-01-01
Abstract
The digitalization maturity models and roadmapping constitute two major research streams guiding companies’ digital transformation enactment. Research on digitalization maturity models is criticized for overemphasizing expert vision instead of empirical evidence, promoting a “one-size-fits-all” approach, and a simplified approach to the development of the digitalization dimensions, which does not take into account their implementation precedence. Roadmapping literature offers a variety of data-driven, expert-based, and hybrid approaches for technology and strategy roadmapping. Current data-driven approaches draw on text mining algorithms and employ topic modelling, link prediction, and other quantitative techniques for generating roadmaps. Given their advantages, such approaches rarely focus on technology development sequences and their characteristics. This paper aims to propose a new kind of data-driven , process mining-enables roadmapping approach for digitalization strategy planning, including a roadmapping method and application directions. A quantitative process mining-enabled roadmapping (pm-DR) approach allows for identifying the fastest digital innovations adoption sequences using longitudinal data on digital innovations diffusion. A case study of the development of augmentation, integration, analytics and automation digitalization capabilities illustrates how to plan a digitalization strategy based on the proposed approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
