PurposePursuing digital transformation is a valuable strategy to attain companies’ operational excellence and sustainable development. However, installing digital technologies and software is insufficient for achieving a successful digital transformation. Equally vital is providing digital solutions with reliable input data, which is a hard task in companies where information is gathered through manual or non-standardized processes. The lack of reliable data prevents technologies and software from operating at their best, hindering their ability to process information and derive correct insights for improvement. To avoid this, companies should embrace structured problem-solving approaches to evaluate current data retrieval processes, identify error sources and formulate countermeasures. This paper aims to provide an empirical study to substantiate A3 as a winning approach for advancing input data acquisition in companies.Design/methodology/approachA case study research is proposed, investigating the application of A3 in an ink manufacturing company, and checking how A3 improves data collection and company performance.FindingsThe case study corroborates A3 as an effective approach, allowing the removal of inefficiencies that previously went unnoticed and reaching a 10% productivity improvement.Practical implicationsPursuing digital transformation is a valuable strategy to attain companies’ operational excellence and sustainable development. However, installing digital technologies and software is insufficient for achieving a successful digital transformation. Equally vital is providing digital solutions with reliable input data, which is a hard task in companies where information is gathered through manual or non-standardized processes.Originality/valueThe originality of this paper lies in the application scope and aim of the A3 approach. A3 is a mature paradigm but often coined for production and still endowed with unexplored potential. This paper proposes the application of A3 for improving companies’ data retrieval processes, focusing for the first time on information reliability and its importance in ensuring the functioning of digital technologies and software.
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