Inaccuracy of data can cost a business money and destroy business value.
Any data record that includes an error is considered “dirty,” which means that the data is out-of-date, inaccurate, incomplete, and just plain wrong. Recent research from Gartner shows that poor data quality is responsible for close to $15m in losses annually. This number increases the more complex and global the organization.
Data is the success factor for supply chain visibility and digital data is the underlying foundation for digital transformation. As businesses undergo digital transformation, a reliance on this “dirty” data can undermine the entire transformation strategy and journey. In order to get the most value from data, it must be cleaned and linked. To clean the data, businesses must correct or remove corrupt or inaccurate records and identify incomplete, incorrect, inaccurate or irrelevant parts of the data.
In digital transformation, data first needs to be integrated and collected from disparate systems. It must be made consistent so that every system will “speak” the same language and “talk” to each other. It is recommended that a team of specialists define the scope of items to be cleansed, assign rules for which classification to apply to certain families of parts, agree on abbreviations (e.g., Bearing to BRG) and define the attributes or specification detail to be associated to each part (dimensions, weight, supplier name, color, etc.).
Different data sets must be linked so that product numbers, shipments and order information is standardized. Now a purchase order is a purchase order; master data is consistent; codes and units of measure are standard; and prefixes and suffixes are harmonized. Once this is complete, transactions can be linked across partners and processes.
An integration platform with connectors to various ERP systems, and inter-company master data mapping functionality which brings all that data into a common, canonical “Universal Business Document” (UBD) format, might be the key differentiator for a business. Using the clean data, UBDs will improve message translation, foster reliable inter-enterprise communication and speed up collaboration, making it easier for companies to conduct commerce with each other. UBDs rationalize barriers for trading partners, allowing them to connect to each other easily. UBDs create domain-driven expression to business processes and ensure a common language across all trading partners. None of this can be successful without accurate data input upfront.
UBDs give complete visibility throughout the supply chain for all parties, from the point where a supplier receives a sales order to the point that the invoice is paid and can also include carriers and shippers involved in the movement of goods. A customer service rep could look up the PO or invoice number and see where the order is within the supply chain — whether in shipping transit, in manufacturing or in inventory in a distribution center. With the proper data foundation, companies can track shipments and identify risk, such as the delay in a shipment that can be detrimental to customer satisfaction.
The Outlook
In the future, more and more businesses will gain value from the insights derived from cleaner data. UBDs, populated with accurate data that is linked, will help supply chains react faster. Capturing clean, actionable, real-time information across a critical mass of trading partners in a consistent manner is the cornerstone of deriving value out of the supply chain and the start of a digital transformation.
