Data governance

Data governance.

At its core, data governance is about how decisions are made about data and who is responsible for it (Australian Research Data Commons [ARDC] - https://ardc.edu.au/resource-hub/data-governance.)

There is no "one-size-fits-all" approach, particularly for a multi-organisational sector like the red meat industry. ARDC advises that good data governance is achieved by combining high-level principles and policies with detailed procedures and processes, as determined by those responsible for managing the data. This supports better compliance with regulatory and ethical requirements, better risk management and greater trust from participants, helping to streamline decision making with clear demarcation of authority and rules that must be followed. Benefits include more efficient and timely decision-making, more rapid and straightforward access to data, and control over costs.

Striking a balance between availability and risk, and between principles and procedures, is fundamental to supporting compliance without exposing participants' sensitive information.

This is where industry data validation services can help to ensure good data governance, while maximising efficiency and trust within the supply chain.

What is an "industry data validation service"?

There is a need for clarity in defining an industry data validation service, as there are myriad commercial entities providing data cleansing and database de-duplication services under the title of "data validation". The "check services" we are concerned with provide simple tools to rapidly validate key data at each step of the supply chain, returning only true or false results along with non-sensitive, related data.

These services rely on Source of Truth (SoT) registries - as described on the previous page.

Data validation is not only the quality control that ensures clean, correct, and consistent data exists in the SoT, but also the process that delivers trusted affirmation of correct values when checking the validity of data attributes. Combining both ensures data reliability for all users within the ecosystem.

Industry data validation services are a cornerstone of good data governance.

The global food-supply chains of today rely on accurate, timely data to facilitate trade and commerce. Where once we sold products with their data attached (e.g. packaging and carton barcodes and consignment notes), we now sell data with products attached. Data errors can result in products being rejected, blocked, diverted, returned or eliminated. For commodities such as meat, there is a very high level of data scrutiny, with large amounts of government and industry-managed data required to facilitate the safe and reliable transit of quality-graded meat products through global supply chains. To ensure accuracy and to operate with the confidence that their supply chain will not break down, commercial trading entities need to be able to validate this product-related data.

Data validation services are a necessary response by industries to this requirement for incorruptible data trails. Ensuring compliance with data governance principles - for management and protection of sensitive information - is a key element.

Examples of industry data validation services.

A good example of this type of service is the Queensland Government "Check registration status" service, at https://www.service.transport.qld.gov.au/checkrego. Enter a registration number and the service will return either "not found" or a set of data that confirms the currency of the registration, the Vehicle Identification Number (VIN), vehicle description (year, make, model), the purpose of use and the registration expiry date. If you visit the Australian Car Network site at http://qld-rego-check.com you will be accessing the very same government data validation service, returning the year, make and model of the vehicle, along with a truncated VIN number. You will also be offered a background history report on that vehicle, for a price. Nowhere in either process was any sensitive information exposed.

Another example is ABN Lookup. Managed by the Australian Business Register - whose vision statements include "be the custodian of trusted business information" and "protect the privacy of business" - the service at https://abr.business.gov.au allows you to look up a business by name, ABN or ACN number. The service will verify or deny the active status of the business number, and provide the type of name (business, entity or trading name), location by postcode and the taxation status of the business as a deductible gift recipient or charity. Although it is referred to as a "search", it is a validation function that retrieves only information deemed to be public.

The principles that underpin industry data validation services with good data governance.

1. The party that is to use a validation service must already hold the data element to be used in the validation request, which means they are already privy to the information that would be considered sensitive.
2. The party that is to use a validation service must be registered - and have a unique security key - to use that service, ensuring only known and active parties can access the service.
3. Should a party abuse the service or attempt to use it outside of the defined terms and conditions, their access can be automatically disabled (a common approach to protection).
4. Each valid and authorised validation request includes a party identifier (matched to the security key) and a unique request identifier - this information is used as part of the login process and identifies request retries for managing and blocking erroneous or malicious activity.
5. All valid and authorised validation requests are recorded, creating an audit trail of request-response information, which provides a robust process for ongoing statistical analysis and compliance-reporting evidence.

The cost of data errors: why we need industry data validation services.

The Export Control Act and its subordinate regulations establish the requirements for export commodities to meet importing country conditions. To demonstrate compliance, livestock must be produced, identified and handled under approved assurance and traceability systems, with records maintained for certification, audit and validation.

To ensure there are no errors in any recorded information, the Act defines the requirements for Australian Export Establishments to have processes in place to check and validate details at every step. Generally, there are no options for correcting errors and civil penalties can apply for making incorrect statements. Analysis of industry program data shows that errors do, in fact, occur and that many go unidentified due to the lack of "Source of Truth" industry data validation tools. Any errors with export shipments can result in the importing country refusing entry, or in market failure. As a simple example, U.S. Food Safety and Inspection Service (FSIS) data shows that up to one fifth of Australian shipments of meat products to the United States are identified as non-compliant shipments and classified as "U.S. Refused Entry" until the issue is resolved, the shipment is re-exported, converted to animal feed or destroyed. There is evidence within industry programs of incorrect recording of NVD serials, supplier LPA accounts, and individual animal identification at the time of slaughter - errors that are undetectable within established processes, due to the lack of industry data validation tools.

The value and benefits to industry of good industry data validation services.

According to CIE modelling, implementation of supply chain information standards within the red meat sector has the potential to achieve a productivity improvement ranging from 1.83% to 3.06% (equivalent to A$1.4 billion to A$2.4 billion). MLA research has demonstrated that "many of the solutions for meat loss reduction call for increased trust and collaboration between industry partners along the supply chain." (Renouf et al 2023: https://eprints.qut.edu.au/243794.)

This is the fundamental point of introducing industry data validation service delivered with good data governance in mind.

While the specific benefits for each leg of the supply chain are harder to quantify, the overall economic advantages for the industry are significant, while the operational benefits would seem to be self-evident - time saving, risk reduction, trust and traceability.