SB'24 San Diego is open for registration. Register early and save!

Supply Chain
3 Steps for Ensuring Complete, Accurate Primary Supply Chain Data

Primary data is the foundation of a strong sustainability program. This framework will help you effectively and efficiently collect the data you need to map, measure and reduce your supply-chain impacts, and meet reporting requirements.

At its core, most corporate sustainability work relies on a three-legged stool of impact measurement, reduction and reporting — the foundation of which should be accurate and timely supply-chain primary data. Unfortunately, many businesses are on shaky ground — according to McKinsey, nearly half of global supply-chain leaders have a limited view of their supply chain or none at all.

To help get your sustainability strategy on stable ground, we’ve developed the following three-part framework for developing an effective and efficient program to collect raw supply-chain (aka primary) data. (Full disclosure: Worldly recently launched a solution for high-frequency primary-data collection that we’re pretty excited about.)

1. Define your needs

Without a clear sense of your corporate objectives, you run the risk of collecting more primary data than you need. Not only is this time-consuming and costly, it creates confusion and fatigue — with resistance leading to lower data quality, lower supply-chain coverage and delayed data receipt.

Instead, develop a clear throughline from corporate objectives to your primary data needs. In our view, carbon/energy, waste and water are among the most important types of environmental data. To determine which types of data to collect, answer the following questions:

  1. What are your reporting requirements? This includes both voluntary (e.g., science-based targets) and regulatory requirements (e.g., EU CSRD). The good news is that most carbon and waste requirements are built on and/or compatible with the Greenhouse Gas Protocol Scope 3 Technical Guidance. Water reporting is more nascent. When developing a data plan for water, we suggest referencing the Water Footprint Network.

  2. How will you select and assess manufacturers? Your supply-chain data-collection assessments should include questions that allow you to classify and sort manufacturers by size, supply-chain tier, country and production capabilities. If you don’t know what happens within the four walls of a factory, you risk trying to compare apples to bananas when analyzing the data.

  3. How will you measure manufacturers’ progress over time? Collect data at a standardized cadence (monthly, quarterly, annually, etc), so that you can easily track manufacturer performance over time.

  4. How will you measure the impact of your work with supply-chain partners? Make sure that you are capturing data at the level of granularity and at the cadence you need to assess the impact of those interventions. If you only collect data on an annual basis, you may have to wait for over a year to understand the impact of a project. This delay can erode trust with your executives and undercut the effectiveness of your program.

2. Data collection must-haves

When it comes to primary-data collection, details matter — a lot. Make sure that your assessment questions and responses map to 1) data outputs your internal systems can handle; and 2) the outputs that you will need for reporting.

Part of this work involves diving into data definitions to avoid confusion. Terms that seem obvious, such as “natural gas,” can be interpreted in a number of ways. Here’s an excerpt from our internal definitions database for “natural gas” (make sure to develop or ask your solution provider for a data dictionary with a similar level of specificity):

Another example that often leads to confusion is water consumption and accounting. In order to accurately assess water consumption, the water balance must be consistently calculated across each node of your supply chain. Carefully defining and gathering data for specific water types is a key success factor for a robust and accurate water accounting system.

You’ll want to store the data in both its raw format and in an aggregated, clean format that is ready for inclusion in external reports. The former will help with internal management and progress tracking, while the latter is what your stakeholder will want to see and use for benchmarking. If you need help going from raw data and reporting-ready outputs, refer to the calculation guidance from GHG Protocol and/or reach out to your solution provider.

3. Analyze, improve and scale

Data collection is crucial; but it’s only the first step. Because most primary supply-chain data is collected from supplier assessments, errors can occur. Make sure to audit and clean up the data before diving into your analysis.

Here are three strategies for cleaning data, all of which can be used together:

  • Supplier engagement — If you see a data point that doesn’t make sense, reach out to your supplier to review it. This can be tedious; but it’s critical. If the same question(s) keep giving suppliers trouble, consider updating the questions you’re asking.

  • Automated outlier detection — many assessment providers (ourselves, included) are working on features that help facilities and brands identify and correct unintentional data errors.

  • On-the-ground verification — companies such as SGS (a Worldly partner) go to facilities to verify primary data — an approach that can be great for new, large and complex partners.

Once the data is cleaned, it’s time to dig in and analyze it. As part of the analysis process, be sure to consider additional types of data or supply-chain partners that should be included in subsequent data-collection efforts.

Primary data is the foundation of a strong sustainability program. We hope that following this framework will help you collect the data needed to map, measure and reduce your supply-chain impacts, and to meet reporting requirements.