We develop and deploy disruptive technologies that
enable businesses like yours to act on data, delivering greater value to your customers and the world.

We provide you with accurate, up-to-date, and easy-to-understand information on the environmental impact of your products through the power of data. How do we do it? By applying a three-pronged approach – breadth, depth, and precision. This helps us provide you and your business with the best data available, by ensuring that we are always ahead of the demand and keeping you and your business ahead of the curve.

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Breadth describes the number of products we can cover with our technology. For the different industries or verticals, we cover, we map out different points in the supply chain to get a holistic view of the number of products, their life cycle stages from cradle-to-grave and all the industries that they exist in.

Where do we get our data from?

Company-level data enables Arbor to showcase aggregated impact on a company’s practices and operations across key sustainability components. This data is further validated by looking at potential violations and historical track records across various operations.

Peer-Reviewed LCA studies

Our use of peer-reviewed and verified data enables us to fill in missing data points to provide comprehensive insights into companies. These insights include the present-day environmental activities, the cleanliness of their supply chains, and the current percentage of goods and services they provide that can be accurately labeled as sustainable.

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Types of materials we have

We compare millions of products and deliver data to your fingertips, enabling you to see detailed impact measurements of products throughout your supply chain. You will be able to see the impact measurements of a detailed scope of products from multiple verticals throughout your supply chain. By covering organic and synthetic materials (polyester, cotton, etc.), along with their life cycle inventories, you will get a clear picture of the impact across your supply chain.


Depth is where we take supply chain transparency to the next level. This step describes our data coverage across the supply chain for any industry or product type, and the complete processing of raw materials from cradle-to-gate. Traditionally, products in the same vertical have the same processing steps. Identifying where products can differ allows us to fill in any data gaps that may exist in the product life cycle..


of carbon emissions are typically embedded in scope 3 of a businesses supply chain - traditionally swept under the rug

How we use hot spot analysis to measure cradle-to-grave

From cradle-to-grave, we use "hot spots" to analyze the percentage of the impact that is created at each stage of the product's journey. This allows us to identify where the most impact is.

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We consider all steps of your product's journey from cradle-to-grave:

  • The cradle to gate impact that has been created
  • The impact during a specific use phase and the processes in it
  • The waste being redirected because of a secondary consumer use stage

Using the hot spots, we analyze where the highest sources of impact and ensure that these areas are constantly reviewed. A hotspot is an area that has a higher concentration of events –the density of "spots"– in a defined area compared to the expected number of events happening completely at random.

Actions speak louder than words

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We use precision to describe the level of detail we can analyze when looking at a product. Coverage of environmental factors including CO2 emissions, water, land, energy use, o-zone depletion, abiotic material use, ocean acidification, ecotoxicity, and human toxicity. The precise level of detail we analyze allows us to increase the impact differentiation between products.

While we always use worst-case assumptions to predict a product's impact, using more precise information increases the impact differentiation between products. For example, in the apparel industry, rather than just looking at the impact of a specific material, we look at what material certifications a product has, where the product was manufactured, and what specific processes the material went through (knitting vs. weaving) to increase the accuracy of the information.

Data Selection

Before we even consider data, we verify its validity. It is heavily scrutinized by experts, peer-reviewed and pulled from industry-recognized data sources.

Extraction, Transformation, Loading (ETL) of data

  • Once we have selected a data source, we pull the data into Arbor’s standardized, proprietary data structure. We aggregate multiple data sources and choose the impact values that most accurately represent a product’s lifecycle.

Cross verification of data points allows Arbor to validate supply chain events accurately. Typically, there are multiple data points for the same material process. We use the information provided about the material, such as geographical origin, in order to determine which data point best represents that material. All of the materials that make up a product are then aggregated and combined with other factors, such as transportation, in order to produce the complete impact of that product.

  1. There is no one data source for all materials/We never use a single data source for materials. We analyze the materials for each category and determine if there are missing processes or data points. Once we determine a missing data point, we conduct research to determine if there has already been a study for this data point. If there is not, we use industry-standard assumptions in their place

  2. No greenwashing here! We use the worst-case assumption model for products that we have access to all of their data points. 100% polyester is an excellent example of this. If there is no geographical data linked to the product, Arbor assumes it’s likely from a region with high inherent impact, such as India or China. Based on other products in our database, we take the worst of the two to determine a baseline assumption.


How we verify that the data is accurate

Our methodology for calculations is transparent and always improving. We use industry-standard and scientifically backed data, and check it against other data sources, studies, and reviews to ensure that our data is always up-to-date. Cross-verifying every data point allows us to accurately validate supply chain events.

You'll spend less time implementing our data than you did reading about it.

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