From chaos to clarity
Navigating the challenges of data quality
Ever wonder about the cost of bad data? Well, looking at organizations in general, Gartner puts it at a hefty $12.9 million every year, on average.
Wrong products being packed and shipped, or inaccuracies in stock levels, are often caused by poor data quality. Duplications, inconsistencies, and errors in master data quietly wreak havoc on operations.
But the right tool can make the job easier by solving inconsistencies between datasets, pinpointing simple typos in records, or disclosing hidden logical errors.
Read now the second chapter of our MDM guide and quickly learn how to navigate the challenges of data quality in supply chains.

"*" indicates required fields