In a previous post we discussed the challenges of scaling data on-boarding from business partners and customers. We examined how Lore IO virtualizes data standardization to make such on-boarding quicker and more cost effective.
In this post, we review two examples of data aggregators (and their partners) and how Lore IO helps them speed up the on-boarding process. We’ll look at data on-boarding in Retail and in Travel and Hospitality.
One of the challenges of data on-boarding in Retail lies in the heavily used EDI file format. Electronic Data Interchange (EDI) files are a well-accepted mechanism to exchange data between suppliers and their retailer partners. Product Activity Data (EDI 852), Purchase Orders (EDI 850), advanced ship notices (EDI 856), and other types of EDI files help suppliers exchange data electronically and consistently. This helps all parties save time and operational costs, reduce inventory levels, and respond faster to supply and demand changes.
EDI files, however, introduce their own challenges that suppliers must regularly overcome. In general, EDI files are not easily read by humans, and their format changes across industry verticals. In retail, while EDI files have a lot in common, retailers occasionally choose to modify EDI segments based on their unique business rules and guidelines.
Examples of changing business rules that suppliers must accommodate include different lengths of period for functional acknowledgements, whether to consolidate invoices for complex orders, and how to adopt global traded item numbers (GTINs). Suppliers must accept and adapt to these variations to partner effectively with retailers or risk facing EDI non-compliance charges.
Beyond the operational complexity that EDI format variances introduce, they also complicate reporting. Suppliers struggle to ingest and map EDI columns from different retailer files into a centralized data format. And they must invest significant resources to standardize the data.
Given the data transformation complications, it becomes cumbersome for suppliers to aggregate retailer data and analyze product, category, and channel performance holistically. Forecasting and planning cycles take longer and are more prone to errors.
Lore IO’s data transformation for Retail
To help suppliers standardize their retail partner data, Lore IO has developed a custom solution on top of its Data Management Platform. The solution converts EDI files into workable and queryable files. Since retailers often introduce variations in the EDI files, the solution automatically detects schema changes and applies the appropriate transformations.
Once new data is scanned, the Lore IO solution leverages prebuilt taxonomy rules that map and group new EDI datasets into one common output.
The solution includes data validation and alerting mechanisms. For instance, suppliers can quickly identify problems where new retailer files are not received or when entries in new product EDI files lack important information, such as current inventory levels, quantities sold, universal product codes, or global location numbers.
Lore IO enables brands that sell through retailers to on-board new partners faster and at much lower cost. No longer do data engineers need to write and maintain code to handle the variations in new EDI files. Brands can run comprehensive analytics on all retailer data and rapidly identify changes in product demand and performance.
Travel Partner On-Boarding Challenges
Travel aggregators collect data from numerous parties, including airlines, car rental companies, hotel chains, and more. The data they ingest varies markedly from one source to another. Each hotel chain, for example, describes its properties and rooms in each property using different columns and values. To ensure that consumers can easily search and browse through available inventory, travel aggregators must standardize the data they ingest.
Given the large variance in data structure and format, travel aggregators take months to onboard a new travel partner. We’ve seen examples where an integrated team of 25 implementation engineers and 5 DBAs from both the aggregator and their partner would spend 4-6 months to onboard the partner.
Delays in partner on-boarding can have significant impact on the business: contracts get delayed and new revenue is missed when the aggregator misses on-boarding deadlines, hurting the confidence of the partner in the aggregator’s ability to execute.
Lore IO’s Data Mapping for Travel and Hospitality
To help travel aggregators standardize their partners’ data, Lore IO has developed a custom solution on top of its Data Management Platform. The solution virtually maps travel partners’ data into a standardized presentation form, runs validation rules and error reports automatically, and exports standardized data views to target systems.
Lore IO offers a highly visual interaction for travel aggregators to first capture their master set of requirements and rules for validating various fields. This master framework template is then leveraged while connecting with each partner's data.
Lore IO solution offers a library of pre-built rule templates that make it easy to stitch the partner data with relevant translations to map it into the aggregator's standardized data. Leveraging the rules and validations captured in the master template upfront, this simplifies the job of automatically summarizing any errors or escapes and generating validation reports and standardized export templates for every on-boarded partner.
By using Lore IO, travel aggregators can typically cut down new partner on-boarding from several months to 2 weeks. Lore IO enables aggregators to avail new partner data through its existing applications faster, as well as surface data elements that did not pass validation. Travel partners can now describe their data to the aggregator without relying on DBAs.
Lore IO’s data standardization solution is available as self-serve or as a managed service. Lore IO can assist customers in implementing the solution and have the customers run it on their own. Alternatively, Lore IO can implement and operate the solution – on premise or in a managed cloud -- on a short-term or long-term basis, depending on customers’ needs.