Smart Data One: helping to improve data quality

Im Rahmen des Internationalen Süßwaren-Kongresses von Sweets Global Network informierte Fabian Dimski, COO von Smart Data One, über die Initiative von GS1 Germany, mit deren Hilfe die Firmen ihre Stammdaten überprüfen können.

Just a few years ago, electronic data played a minor role in the distribution segment as more often than not, selling results would hinge on the right product for the right price in the right place. Back in the day, data management was something of a nerdy thing, explained ­Fabian Dimski, COO for GS1 Germany subsidiary Smart Data One GmbH, at Sweets Global Network‘s workshop in Berlin. But those times are long over, and the digital transformation has put the data at the heart of the whole value ­creation chain.
Having said this, providing high-quality product data is a complex and ever-growing challenge for any company, especially medium-sized and small ones, because the demand for detailed, high-quality product data is skyrocketing. Both the big trade chains and e-commerce businesses are insisting on up-to-date data administration and error-free master data. Consumers, on the other hand, now routinely expect comprehensive information on all channels, while the legislator urges for more transparency, as highlighted by the Food Information Regulation.
It‘s for this reason that GS1 Germany formed Smart Data One ­GmbH in 2013 as a wholly-owned subsidiary and a sister company of data pool operator 1WorldSync. Delivering services in the field of product data management, Smart Data One is currently helping more than 600 industrial and retail customers to provide the required quality-­assured product data quickly and completely. The data quality initiative Data Quality Gate was launched in a concerted effort to optimise the ­data. According to Dimski, it is a software solution designed to check the product data automatically and forward reports to the data providers.
The reports, which are sent by the system free of charge, give an overview of the specific errors that were identified. During the pilot stage with 200 suppliers and 18,000 items, 91 companies used the system to bring the error ratio in the attributes down to zero. ­Beginning in May 2017, the Data Quality Gate has been expanded to cover some 2,000 industrial enterprises. According to Dimski, the automated checking typically saves manufacturers several weeks. ”Send us your data,” was the expert‘s call to the workshop participants to leverage that service. The result is a continuous ­improvement of the data quality, thus curtailing time losses in distribution and product listing.•