Major retail and healthcare outlets are moving towards full supply chain automation at a very fast pace. As a result, the need for suppliers to provide good quality product data has never been greater. One of the largest supermarkets in Australia is now even using Data Quality as a key supplier performance metric!
Data Quality is the accuracy and completeness of information that relates to your products.
This can include information such as product description, product name, country of origin, allergens, nutritional, ingredients, product dimensions, pharmaceutical & medical device data and marketing claims.
In today’s hyperconnected, highly automated world, maintaining good data quality is an enormous challenge. It takes elbow grease and focus. However, taking the time to lay the foundation for data quality is crucial. If information is missing or contains errors, you run the risk of disruptions up and down the entire supply chain impacting your bottom line.
Good product data saves you money, saves you time and saves your company’s reputation.
In a world where customer experience is crucial, good data quality results in a good customer experience. If product data such as an ingredient, dosage or expiry date is missing from a product and causes an adverse reaction, a vocal customer on social media can make the lack of this data not just a simple oversight, but a brand-impacting event.
It’s not only human behaviour that is affected by poor quality data. With the rise of new technologies such as artificial intelligence, machine learning and warehouse automation, data quality is now even more critical for these technologies to function accurately and efficiently.
The sheer volume of data that needs to be collected and analysed is another significant factor to take into consideration. Data is required at an extremely rapid pace and in huge volumes. A small error or delay in your product data can make a significant impact on the supply of your products.
Large retail and health organisations can’t afford risks such as out of stocks and incorrect orders.
To ensure you have the right level of control and can maintain the quality of your data, it’s recommended that a sole owner or team is assigned to manage your data quality processes.
These are the disciplinarians who will ensure all items pass through the data quality lens. You also need to ensure data quality is treated as business critical and gets the appropriate level of senior management support.
Don’t try and re-invent the wheel. Tap into the talent of data quality experts who deal with the management of data on a daily basis at
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