First things first. What exactly is a Data Flow Model?
A data flow model is a diagrammatic representation of the flow and exchange of data within a system. Data flow models are used to graphically represent the flow of data in an information system by describing the processes involved in transferring data from input processes to file storage, to data processing & validation reports generation and ultimately data extraction to external systems.
How does it relate to the Global UDI Syndication Hub?
Global device manufacturers must often submit UDI data to a myriad of country-specific regulatory authorities, each requiring their unique data exchange standards and data validation requirements. And submitting that data is part of the UDI Data Flow lifecycle.
Are there different kinds of data flow models to the Global UDI Submission problem?
Yes, broadly speaking there are two types of submission approaches:
- UDI Passthrough Submission solutions (without data conversion, just data validation and messaging formatting & handling)
- UDI Data Enrichment & Submission (with data conversions, data maintenance, data validation and submission message formatting & handling).
Tell me more about the UDI Passthrough Solution model.
The Passthrough data flow model is really a “centralised” master data maintenance paradigm. The UDI master data is created or maintained in upstream source systems only (e.g. PLM, ERP, RIM). That means you use a UDI submission system to map source UDI data to the required regulatory attributes, validate the mapped source data, and generate the messages in the Regulator’s required messaging standard, and then delivery/submit the messages to the Regulator’s UDI system.
What are the benefits of the Passthrough Solution model?
Since the data is centrally maintained in upstream source systems (usually ERP or PLM), it’s easier to manage, correct and modify. Data conversion and some data validation happen in those source systems before it is packaged into a message for external submission. Any required data changes occur within those source systems. Users don’t require a multitude of applications to maintain the various subsets of master data depending on each use case, and each country. This is especially helpful because your users only need to be trained on using those source systems for master data management. This model is also very cost-effective purely from a UDI submission perspective since you’re using the UDI system for data exchange only (and not to create or maintain UDI master data).
Are there any downsides to the Passthrough Submission model?
The biggest downside to using a passthrough model is that extensive software development is required in upstream source systems to add new attributes, valid code lists, and data validation rules as different countries develop their own flavour of UDI regulation. This could overload those source systems with much more complex than they were originally designed to do. As a result, the cost of owning, enhancing, and then validating those source systems (for GAMP 5) may increase significantly over time as they are customised to support more & more data attributes and validation rules that are added around the world. Just be aware that as you extend the source systems to support the UDI data compliance requirements for new countries, you’ll also be adding more attributes & code lists. There’s the potential for a proliferation of attributes that could be challenging to govern if you’re syndicating UDI data to many different countries.
So, tell me about the UDI Data Enrichment & Submission model.
In this model, master data management is not centralized. A subset of the UDI data may be imported from different source systems, while other data is maintained in the UDI “PIM” system. Imported master data may also go through a process of transformation, enrichment, localisation (to each country’s requirements), validation, approval and then regulatory submission.
What are the benefits of the Data Enrichment & Submission model?
The key benefit of using a Data Enrichment & Submission approach stems from IT landscapes where the source systems cannot be modified easily, or cannot be extended cost-effectively, to capture new, emerging UDI data attributes, or where the sources don’t exist at all. Even if those source systems do exist, they cannot be easily modified to support emerging UDI data types & data elements. In these scenarios, having a UDI compliance system that allows for UDI data capture, maintenance, validation and approval workflow can dramatically reduce the total cost of ownership for those source systems. Maintaining master data in a system that is built for UDI compliance means that data capture, creation and management processes will be simplified for the Regulatory Affairs, Quality Assurance and Master Data Management teams.
Are there any downsides to the Data Enrichment & Submission model?
Of course, the concern with this approach is that additional data governance would be required. Remember, the data for newly-added UDI attributes need to be created or originated from somewhere. So, it’s important to decide how they will be sourced, stored, enriched, managed and governed as you move from country to country.
How do I know which data model is right for my company?
Think about how your IT landscape operates and where you want to source your master data. If you’re not sure which approach best suits your company, the Innovit team is here to help. At Innovit, we’re agnostic to either approach for UDI data submission, and our solutions support both data flow models. We can walk you through each process and help you figure out the best path forward!