Many organizations are facing unprecedented pressure in today’s Amazon-dominated world. The reality is that there is a “garbage in, garbage out” cycle of inaccuracies plaguing supply chain data, which can both create inefficiency and negatively impact the consumer experience. For example, one small measurement error can mean a shipment will not fit into the warehouse space assigned, causing a company to incur thousands of dollars in unnecessary costs. Additionally, a product ingredient missing from a product listing can cause an adverse reaction in a particularly vocal consumer using social media, leading to long-term damage to the brand’s reputation.
The good news is that companies which want to become more proactive about data quality do not have to reinvent the wheel in 2018 to improve the condition of product data. They can look inward at current business processes and use the framework established by the GS1 US National Data Quality Program as a blueprint for success.
The program was created by a diverse range of professionals with responsibility for master data management, quality assurance, and other data-related roles who recognized the need for one common approach to improving data quality. GS1 US worked with these passionate data professionals to establish three pillars that each promote product information accuracy.
In 2018, businesses across many industries can expect continued relentless disruption. This will only expose bad product data and the inefficiencies it can create. Data quality is no longer a distant “someday” goal or a quaint idealistic dream. Now is the time for companies with a competitive eye to harness the power of data to use 2018 as a springboard for new growth.
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