Webinar Recap: How to Easily Improve Your Data Quality
- Zixi (ROSA) Yang
- May 5
- 3 min read
Quality data is undoubtedly the foundation of operational success. However, how can you assure data quality when you still rely on spreadsheets, endless email threads/phone calls, and manual validation/support?
Furthermore, when it comes to updates and maintenance, many of us lack the time, effort, or willpower to endure the tedious process.
The Current Situation: We Have A Problem that We Often Ignore
Let's face it: the importance of data governance was (still is) overlooked.
"In every projects we do, data always turns out to be a hot topic. As a CIO, I really can't remember any project that I've been involved with that data didn't come up as a potential detriment to what we want to deliver," said Ed Wong, a retail veteran with 30+ years of experience in retail supply chain operations and IT systems in the recent webinar hosted by Simplain and GS1 US. "We never allocate enough time, resources or money to really address a lot of the root causes."
From his perspective, adapting industry standards (such as GS1 standards) and processing data in a centralized and collaborative environment (such as Simplain Vendor Portal) is the solution for retailers and wholesalers in the food and hardline retail industry.
What to Capture: Single-Origin Data
First, you need to attain data interoperability.
"Instead of trying to decipher each other's systems and data base, data can be integrated seamlessly regardless of the technology used. How does this happen -- if it's based on a common language that can easily be interpreted and ingested by any system or technology. And that's exactly what we do at GS1 -- focusing on getting supply chain partners to talk, understand, collaborate and establish this this common language."
She then used the example of voltage adapter to further illustrate her point. "What happens to our day-to-day common business is we don't have that common to be able to adapt your system to my system."
Beginning with unique identification, GS1 standards allow companies to catalogue products, standardize item information and transport such information from one location to the other. "That's just the way that the data is structured and is sent to different systems from a centralized source of truth."
Where to Operate: An Open Platform that Assigns Accountability
To process/maintain your data and institute your data governance workflow, you need a bi-directional platform specialized in vendor collaborations.
"Once the vendor submits something, it goes to the portal for triaging. The retailer can visually or manually look at this data and review it. The main purpose of this review will be for negotiation of terms, costs, etc. During the same process, the data is also being reviewed by the Master Data team and/or category managers for data completeness, correctness, etc," said Sanjaye Elayattu, founder and president of Simplain Software Solutions. "The idea is here you solve the issue at the source, and you don't have the error going from your vendor to your supply chain systems or ERP. "
He then elaborated on how Simplain can now leverage GS1's data hub due to the recent official partnership with GS1 US.
"Our platform aims to make each party (retailers/wholesalers and vendors) accountable for their own data and make sure they have a common way to collaborate, thus increasing the transparency in the supply chain altogether."
What can You do to Improve your situation?
Sanjaye and Lucelena then discussed real-life use cases where GS1 standards and Simplain Vendor Portal improved the financial standings for major retailers by increasing supply chain traceability and improving efficiency.
All three speakers answered:
What are retailers/wholesalers are looking for from suppliers like GS1 and Simplain?
What have you seen as the most common mistakes made by retailers and wholesalers in master data management?
What advice would you give to people looking to improve this area?
What would be cost to fix the "bad" data?
How can the foundational structure provided by GS1 Standards be leveraged to ensure the quality and interoperability of the data used for AI-powered advanced analytics that ultimately leading to more accurate forecasting, personalized customer experience and optimized supply chain management?
Comments