Those who are responsible for packaging artwork know how complex data governance is. Take this example: a product comes in four sizes and each size is available in 10 markets with different language requirements in each. Suddenly you’re up to 40 labels, and if you have multiple manufacturing sites, this number goes up again. And there can be no “rogue” labels. Despite language and size variations, each label still has to sync with the master label content map, which includes:
- Marketing content (i.e., brand name)
- Legal content (i.e., “Manufactured and Distributed by…”)
- Regulatory content (i.e., “Store at room temperature…”)
- Operations content (i.e., “50mg…”)
- Printing content (i.e., “Batch number…”)
At its core, data governance is about institutionalizing methods and establishing an organization with clear responsibilities and processes to standardize, integrate, protect, and store data assets such as those in the example above. In BLUE’s work with many global CPG clients, we observe a broad spectrum of maturity with regard to data governance. Sometimes, we find there are packaging stakeholders who recognize the importance of establishing or maintaining data governance, but they struggle to convince others to prioritize the effort. As a result, their data governance practices are sub-standard. Some indicators of poor data governance include:
- There are no defined data governance roles and responsibilities.
- Different functions and systems re-enter the same data.
- Inconsistencies exist between data in different systems, or between information on a product and information in a system.
- There are limited data reporting capabilities.
- There is no vision for how to use data as a strategic asset.
One reason it’s difficult to reach consensus on data governance is that it touches many different groups within a CPG organization (regulatory, IT, marketing, manufacturing, supply chain, etc.), with each group seeking a potentially different benefit from data governance and each group needing to apply different levels of effort to achieve the benefit.
To gain consensus and implement and manage a data governance strategy, you must first understand what a few of these groups actually wants. While this may vary from company to company, there are some consistent patterns:
Information Technology
Information technology teams desire a consistently articulated and well understood need from the business. They want selected technologies to be supportable and easy to technically implement. They want the “stack” to be built with flexible, modern technologies that are sustainable and use integration tools that are also flexible and cost effective. They want to have advance notice of resource allocation so they can plan the implementation alongside their many other activities. They want to understand the relative importance of this effort compared to others.
Marketing
Marketing is in the interesting and challenging intersection of “brand governance” and “data governance” – the confluence of regulatory-rational and consumer-emotional. If we talk about the primary product package, there are regulated elements such as ingredients, nutrition, and claims that must blend and co-exist with visually compelling presentations of the brand; regional and seasonal promotions; line extensions based on size, flavor, or regional demographic; and for an international firm, the translation and communication of all of the above into two or more languages. All of this must be managed at an ever-increasing pace, such that brand sales goals are met and packaging art gets to manufacturing and distribution within ever narrowing windows of time.
Legal/Regulatory
These groups stand on the front line of product quality and risk management. The legal team wants a clear, approachable way to review packaging content as it evolves, but not too early – and not too late – in the process. Too early, and there is so much change they end up looking at the same basic information with each iteration and don’t see high value in their interaction. Too late, and they are often told they have delayed the process, spoken too late, or are making unreasonable demands given the available timeframe. It is also very helpful for this group to have an easy to use tool that shows them packaging information in the context of the final artwork – “Copy in Context” or CIC.
In addition, legal and regulatory teams want a reference tool that can tell them which text is located on specific SKUs. For example, if they approve a claim, is this claim destined to be used on one package, or on 500 packages? On a USA-only package, or on an international package? In the past, this has been “managed” by having the team either approve copy without this knowledge (higher risk) or review the same data on all SKUs (unsustainable effort).
Finally, legal and regulatory teams want to be able to quickly reference relevant documents during the approval process such as applicable laws and regulations, studies that validate claims, and previous versions of the package to understand the history of various packaging elements within the brand. They also want to be able to see comments from other teams while they interact with the packaging artwork.
BLUE Understands the “Needs Matrix”
BLUE has a deep understanding of this complex “needs matrix” and can help you gain consensus on data governance in your organization. To learn more about BLUE’s approach to data governance, download our e-book: Mastering the Complexities of Artwork Versioning Control.
