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The purpose of this paper is to identify, characterize, classify and conceptualize different perspectives on strategic alignment still in use, propose a taxonomy and definitions that allow understanding the various coexisting concepts, as well as investigate the implications of strategic alignment for data-driven sustainable performance of firms and supply chains.

Bibliographic review was used.

The taxonomy proposes two classes of strategic alignment: (1) Align – more rigorous types of alignment: structure alignment, strategic congruence and strategy alignment; (2) Fit – less rigorous types of alignment: contingency strategic adjustment, strategic coalignment and strategic consistency. Companies are accumulating large amounts of data, which relevance varies widely. The strategic alignment can define criteria to select only the data that have strategic value, which restricts the amount of data to be analyzed. Each of the six types of strategic alignment is appropriate for a given situation in companies and/or supply chains.

The limitations stem from the exclusive use of the taxonomy of strategic alignment, without considering the most diverse perspectives of strategy.

Decision makers will be able to identify more objectively which classes of data should be explored in each situation.

Theoretical implications – The taxonomy proposal and the definition of each of the strategic alignment perspectives solve generalized misunderstandings resulting from the lack of a clear delimitation between the perspectives and the conceptual divergence between authors, who use them as equivalent or synonymous.

From 1961 to 2019, no paper was found proposing taxonomy, typology, systematization, ranking, distribution or classification of strategic alignment. The strategic alignment can define criteria to select, within the large amount of data accumulated by the company, only those that have strategic value, what restricts the quantity of data to be analyzed and facilitates the decision of the leaders.

This study aims to broaden the understanding of the additive manufacturing (AM) body of knowledge, presenting a model better suited to the current level of technological development that supports the decision to implement AM in industries, based on the experience of companies in the industry of orthopedic medical implants.

Based on the design-science research, the model for the decision to adopt the AM was designed and submitted to experts from the industry of orthopedic implants in Brazil for refinement. For the empirical test of the final model, interviews were used in a company that was considering implementing AM and in another that was not, to evaluate the model.

The model considers seven dimensions for decision analysis of AM implementation: legal constraints, financial, technological, operational, organizational, supply chain and external factors, being subdivided into 42 criteria that play a relevant role in the implementation decision. The analysis factor of each dimension and criteria are also presented.

The model seeks to be as complete as possible and can be used by various industrial productive sectors, incorporating the analysis of the requirements of health regulatory agencies, suitable for the analysis of the decision to implement AM for the manufacturing of medical implants, not found in other models.