What is a life cycle analysis?


· 8 min read
Life cycle assessment (LCA) is a method of evaluating the environmental impacts of a product or service over its entire life cycle, from raw material extraction to disposal.
The goal of LCA is to identify and quantify the environmental impacts of a product for reporting purposes and to support sustainability initiatives.
What is the environmental impact of the cheap t-shirt you bought in this fast-fashion retail store?
It requires data from multiple sources to follow the impact of your products along the value chain until the end of life.
In this article, we will try to understand how advanced data analytics tools can support Life Cycle Assessment (LCA) by extracting and processing data from multiple systems to perform diagnostics and simulate scenarios.
To initiate our Life Cycle Assessment (LCA) we need to define the goals and scope of this assessment.
This includes identifying the product being studied, the environmental impacts of interest, and the functional unit (the unit of measurement used to compare different products or services).
What is the environmental impact of producing and selling a t-shirt in a fast-fashion retail company?
Make sure that the scope is agreed upon by all stakeholders involved in the assessment to ensure that the Life Cycle Assessment results are meaningful, representative and will not be challenged.
📊 From the Data Analytics Angle
The product will be linked to one (or several) SKU code(s) in your different systems (ERP, WMS, TMS)
For each life cycle stage, you may have different data sources/systems
Geographic boundaries can be defined by the source system and transaction information
Identifying the time frame can be challenging and will impact your assessment results
Note that the scope could be more or less detailed according to your needs and the expected initiatives that will benefit from the results.
The second step is to gather data on the materials, energy, and other resources used and the waste generated throughout the life cycle of the product or service.
Raw materials
Your t-shirt is made of 100% cotton grown and processed in India
You can now quantify the CO2 emitted, the energy and the water used per functional unit.
💡 Impact of Raw Material Cultivation
Production
The t-shirt is produced in your factories located in India
Transportation
Your t-shirt is produced in India and shipped to Europe by sea freight
💡 Impact of your Logistic Network
Usage and disposal
Your product is used (usage and disposal) in the market’s country.
The t-shirt is used for 2 years before being disposed of.
The t-shirt is disposed of in a landfill in the country where it is sold.
📊 Data Analytics Solutions for Inventory Analysis
Instead of using estimation or average, you can build a data architecture to retrieve updated data and metrics in a data lake
This architecture will reduce the amount of manual work and improve the accuracy of your reporting by using up-to-date parameters and input data.
Now that we have gathered data for each step, we can start evaluating the environmental impacts of the functional unit (1 t-shirt here) on
The majority of the impacts are generated during production and transportation.
This is the process of assessing the overall environmental performance of the product and identifying areas for improvement and potential mitigation strategies.
Comparison to industry standards
The results of the impact assessment can be compared to industry standards or benchmarks to see how the t-shirt compares to other similar products in terms of environmental performance.
Identification of hotspots
The results of the impact assessment can be used to identify the “hotspots” where the t-shirt has the greatest environmental impact.
In our example, these hotspots are greenhouse gas emissions and energy consumption during production and transportation.
💡 Diagnostic Analytics for automated identification
If you have implemented a data pipeline to gather, process and store data for your inventory you can implement diagnostic analytics tools and methodologies to automatically
Potential mitigation strategies
Based on the hotspots identified, potential mitigation strategies can be developed to reduce the environmental impact of the t-shirt.
💡 Example of initiatives
Continuous improvement
The results of the interpretation and evaluation should be used to continuously improve the environmental performance of the product or process over time.
Of course, you need to consider the trade-offs between the environmental impacts and other aspects such as cost and performance to reduce the business impacts.
This article was mainly focusing on how data analytics can support data gathering, processing and visualization with diagnostic tools.
A digital twin is a digital replica of a physical object or system.
A Supply Chain digital twin is a computer model that represents various components and processes involved in the supply chain such as warehouses, transportation networks, and production facilities.
In this digital representation, you can model each element of your end-to-end supply chain with costs, energy, emissions and lead time parameters.
When you are brainstorming potential mitigation strategies you can simulate their impacts on the whole supply chain.
For example,
This article is also published on the author's blog. illuminem Voices is a democratic space presenting the thoughts and opinions of leading Sustainability & Energy writers, their opinions do not necessarily represent those of illuminem.
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