Master packaging data to drive supply chain synergies

  • January 09, 2024

There's a valuable currency within the supply chain we must discuss more often: data. More specifically, we need to discuss accurate item master data, which includes the weights and dimensions of the products organizations design, manufacture and move through their supply chain.

The fourth industrial revolution, or Industry 4.0, has propelled automation and data connectivity. The revolution has compelled product manufacturers, brand owners and retailers to drive growth and balance SKU complexity with digitization while maintaining a robust bottom line.

After major supply chain disruptions during the pandemic, we saw many organizations expedite their digital transformation strategies to drive efficiencies across production, storage and handling and distribution of goods.

Establishing processes and upgrading existing equipment and infrastructure to allow connectivity is a good early step. But what if your packaging data isn't accurate?

Prioritize packaging data accuracy

Various data sets affect an organization's daily operations. As an example, sales and operations data — commonly captured in enterprise resource planning (ERP), transportation management system (TMS) and warehouse management system (WMS) systems — help drive transactional operations within the business.

Packaging data specification is critical to creating and developing packaging design and structure. Stock-keeping unit (SKU)-level data on weights and dimensions are foundational building blocks of other essential business operations. This data will be used to determine how to store products in warehouses or distribution centers and how to load out trucks and trailers more effectively, thus reducing transportation inefficiencies and related use capacity. For example, weight and dimension information at the sell unit, case pack and pallet load level all feed downstream processes and studies such as warehouse space capacity analysis, optimal transportation planning other scenario modeling analyses.

Some organizations may own or input this data themselves. Others may rely on trade partners, co-manufacturers or vendor partners to provide this level of information to their Master Data teams. Either way, packaging engineering teams and vendor partners should take ownership of data accuracy for back-end business operations.

Define business rules and best practices in packaging

The adage “garbage in, garbage out” starts at the data entry level, which is why foundational processes for data inputs are essential. Specific details in a system's data configuration and architecture can highly impact the accuracy of input by novice users on the front end.

Many organizations have extensive training programs for employees to operate machinery and equipment, yet they often need more rigorous processes and training for data entry and edits.

While it may seem simple, specific packaging data and details and requirements still need to be captured and defined upfront, including:

  • Defining a unit of measurement — imperial or metric units.
  • Defining length, width and height of finished goods. Are you capturing this based on shelf presence, portrait, or landscape orientation? Or how it’s shipped?
  • Defining terminology. For example — sell unit vs. finished good (FG) vs. “shipper” vs. “case pack.” Many organizations use these terms interchangeably. Teams must define these various levels of the product up front, along with their dimensional impacts.
  • Understanding retailer rules.
  • Review GS1 standards for guidance on acceptable product dimensional variance limits.

Establish one source of data truth

Data is only as accurate as its sources, and when you have many, the picture gets messy. Fragmented systems can lead to lost productivity, lack of visibility and increased organizational risk.

A recent Gartner study states, “Specification management applications enable data governance, reporting, and compliance across packaging, ingredients, components, and finished goods. Supply chain technology leaders should use this research to improve data management practices and support growing governance and compliance needs.”*

Establishing one source of truth, often from a cloud-connected data platform or specification management system, for all components of product master data — including weights, dimensions and detailed packaging material specifications — will increase data accuracy and provide crucial information on environmental impacts and greenhouse gas emissions.

Sustainability legislation will continue to advance, requiring manufacturers and vendor partners to report and track the impacts of their organization’s packaging. Accessing, summarizing and reporting on this data requires a robust system and process. SharePoint sites and spreadsheets are great starting points, but a more sophisticated system will be essential as the frequency and level of detail increase.

Identify gaps and unlock opportunities with data

Before we circle back to the upstream data processes, look downstream and think about end goals. Master data within an (ERP) system feeds into many functions of an organization, including production scheduling, inventory planning, demand forecasting, transportation planning, warehouse slotting and capacity planning.

For larger organizations, having systems that talk to each other is key. Centralized ERP data needs to be connected to satellite warehouse and distribution center sites and their technology stacks. Read-write rules for satellite hubs should be established, with a centralized system housing all data as its “one source of truth."

Inaccuracies or missing data fields may lead to big gaps in your value chain, add hardline costs and have intrinsic impacts. For example, incorrect or missing size data at a case level can create a ripple effect of added costs as the product moves from manufacturing, to transportation to warehousing and storage to outbound delivery to the end customer. Peeling back the layers of the onion may uncover additional costs, such as:

  • Under-used trailers in outbound shipments.
  • Low-capacity usage of sea container shipments and FEUs.
  • Dimensional weight penalties in small parcel shipments.
  • Excessive warehouse space requirements based on inaccurate case sizing or pallet TI/HI counts and dimensions.

In each scenario, cost additions are compounded throughout the supply chain. Imagine what savings opportunities can be identified when processes and systems are implemented to protect data accuracy.

Close the data gap

Accurate packaging data makes for optimized, efficient warehouses and transportation networks. As your organization advances its digital transformation strategy, make product master data accuracy a priority in your supply chain.

Avoid unnecessary costs and slow processes by moving your data to a centralized platform for better visibility, collaboration and reporting. If you begin now, you'll be prepared for the next wave of reporting requirements and unforeseen events that may impact your supply chain. It’s time to close the data gap.

Contact us and see how NTT DATA can empower you to conquer inefficiencies and rein in costs. Our top supply chain talent, enabled by proven, leading-edge digital assets — tools, methods and content — deliver actionable insights and measurable outcomes to some of today’s largest and most complex supply chains.


Subscribe to our blog

Rob Kaszubowski

Rob Kaszubowski is the Managing Director and Practice Leader of Packaging Optimization for NTT DATA's Supply Chain Consulting group. He leads a team of talented packaging engineers and consultants who've been solving complex packaging challenges for over 20 years. With over 300 consulting engagements across multiple industries and platforms, they deliver solutions to packaging challenges across client supply chains, both domestically and around the world.


Related Blog Posts