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:
-
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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.
-
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.
-
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.
-
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.
Published Jun 29, 2023 11am EDT / 8am PDT / 4pm BST / 5pm CEST
Sr. Director of Analytics
Worldly
Cashion "Cash" East is a sustainability leader and strategist with over 15 years of experience in the environmental industry. He serves as the Director of Analytics for Worldly, where he designs and builds the technical underpinnings for sustainability software solutions for manufacturers, brands, and retailers. Cash leads the data science team responsible for implementing the data and methodology to ensure that companies have robust, accurate, and actionable results. JR Siegel, Worldly, Sr Director of Product Innovation
Sr. Director of Product Innovation
JR is the Senior Director of Product Innovation at Worldly; the author of Bright Spots, a weekly newsletter focused on positive news from the climate space and how you can be part of the change we need; and a technical advisor to the Tom Ford Plastic Innovation Prize. He lives in Seattle with his wife, three kids, and a very silly dog.
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