Master Data teams at FMCG retailers/wholesalers have the responsibility of keeping the data in the enterprise clean and consistent. This is important because the total cost of data errors in the enterprise are too high. However, they often do not have the right tools for them to efficiently do their jobs. They deal with outdated systems and processes even as they work on supporting the organization pursue their strategic goals.
Key Challenges for Master Data Teams:
Following are some of the key challenges faced by the data stewards:
Data they receive from Suppliers/Vendors is often inaccurate, incomplete and inconsistent.
Competing priorities by different internal teams they serve. For example, category managers may need their item to be completed at the earliest so that they can make use of an opportunity buy. However, the supplier might not have provided them with the key information such as dimensions, product certifications, nutrition, allergens, digital assets; much to the dislike of compliance and e-commerce marketing teams within the organization.
Master data teams may be overwhelmed by the the sheer volume of data during peak seasons (or the time leading up to the peak seasons) and during business events that require mass-maintenance of product information (such as switching vendors, opening new facilities and M & A activities)
More importantly, the master data teams will have anywhere from dozens to couple of hundreds of product attribute (based on the type of the product and nature of business) that they need to enrich based on the information provided by the vendor and other internal team members.
How an AI Driven UI Workflow in Simplain Vendor Portal can help the Master Data team?
Traditional user interfaces catering to vendors and master data teams often are cumbersome to use and require users to click through multiple buttons/check boxes and scroll through multiple pages. These rule based engine require configuration of multiple workflows and the user has to be careful so that the product goes through the correct work flow.
Recent advancements in generative AI technologies allows for a much smoother user experience in Simplain Vendor Portal. The user experience in Simplain Vendor Portal, do not just depend on rule based logic, but they also make use of Gen AI technologies to interpret the intent of the user.
For example, a user searching for protein rich items will also see items that are protein rich but do not contain the word protein in the description. Similarly the system will automatically determine that a product is a beverage item requiring bottle deposit related attribution based on semantic meaning of other product attributes, such as description. In Simplain Vendor Portal , for example, the user does not have to key attributes that are part of the product label; The vendor or master data user can just upload a clean image of the product. The system also suggest tags, merchandise hierarchy etc. based on semantic similarity of the current item compared with the cluster of other products that are in the catalog.
While the rule based data validations in the system (there are hundreds of validation rules in the system based on FMCG best practices and GS1 standards) improve the overall data quality and establishes accountability for the respective data owners, the Gen AI assistive features significantly boosts efficiencies for all users in the system including vendors and master data teams. The examples provided here are just the tip of the iceberg when it comes to the possibilities that lie ahead in providing a user experience that understands the "intent" of the user. Simplain is already on this exciting journey along with our customers and their vendor partners.
Comments