Can data quality help overcome the penguin effect? the case of item master data pools

The diffusion of standards is characterized by network effects, path dependency, and the penguin effect. Particularly the latter, also referred to as excess inertia, is a frequent inhibitor of the adoption of standards, even if they could provide benefits. This is particularly true for item master data pools that suffer from little adoption in many industries as benefits can only accrue if many firms use them. At the same time, data pools show the potential to improve the quality of item master data by pooling the efforts on data quality assurance. This paper addresses the question whether an improvement of item master data quality can contribute to overcoming the penguin effect by data pools. The theoretical considerations are supplemented by an exploratory qualitative research among the leading retailers in the Austrian food and drug sector. The findings suggest that data quality improvement can be one way to encourage the use of data pools and thus overcome the penguin effect in adoption.