Climate change has created a new level of commitment from the automotive industry to reach net zero emissions. This drive for sustainability has evolved from tailpipe emissions to manufacturing emissions to encompass the entire life cycle of the product. The GHG Protocol establishes comprehensive global standardized frameworks to measure and manage greenhouse gas (GHG) emissions, which fall into three categories: scope 1, 2 and 3.
For automakers, scopes 1 and 2 are related to manufacturing a car (fuel consumption in production and assembly, electricity, heating, cooling, and steaming for operations). Scope 3 involves upstream inputs such as purchased goods and services and logistics as well as the end-of-life treatment of the vehicle.
To make more sustainable products the starting point is no longer confined to just monitoring the production process. Companies must also enlarge their toolkits to allow them to modify product strategy and select environmentally aware supply chain partners.
For example, Ford has requested that all its Tier 1 suppliers disclose their carbon emissions. Ford used these numbers to calculate how much of the scope 3 emissions it was responsible for. The number was about 70 percent.
Moving beyond aggregated information
All this tells us that the path to Net Zero is a transformative process that must be guided with sufficient data insights to make the right strategic decisions.
Currently Ford, and other automakers, know their direct emissions, and some of them have a reasonably good estimate of the emissions that come from their value chains and how much comes from their facilities. However, it does not have the data to compare emissions from the F-150 pickup against the Explorer SUV because they sourced different parts, assembled them in different facilities, and they have different fuel efficiency. This is the vision of product-based emission accounting, which will be crucial to have to make effective business decisions.
With a product-based carbon footprint an automaker would know the carbon cost for every hour of welding, or for every painting of a surface space. This would allow them to understand the carbon footprint of every step in the production process. However, the current data tools companies use to collect and report emissions data are far not capable of providing this granular level of insight.
The data triangle
There are three parts of an effective sustainability data strategy -- first data sourcing and quality, secondly data management and consistency, and finally the analytics that is derived from the data.
The conundrum of data sourcing and quality is the first challenge that automakers are grappling with. Companies need data points that allow them to understand how much fuel they are spending on each part of the logistics chain.
There are numerous data sources, and they are fragmented across an organization. That’s why data ingestion tools that interface with emission activity data in different formats, structures, and even methods of ingestion are critical. They also reconcile different input data frequencies and reveal gaps and unusual values to maintain data quality.
Next up is the data management piece. Companies serious about measuring and tracking progress must develop a flexible, future-proof core database.
Without a centralized data model with a constant core set of data architecture and concepts it will be difficult to manage the ever more complex emission and climate related data. More importantly, the organizing structures of the data should remain flexible while the values and computations should remain consistent.
The third, and most important aspect is the ability to access that data and perform advanced analytics on it to deliver business insights that lead to achieving sustainability targets.
For example, having the ability to attribute different carbon footprint to different product lines and being able to to make decisions on how to prioritize or innovate the product portfolio.
This will enable an organization to be more selective about the environmental implications of its supply chain decisions. It can also shed light on the opportunities or limitations in adopting zero-carbon or low carbon energy sources for production and logistics.
Published on: https://europe.autonews.com/guest-columnist/data-analytics-key-reaching-net-zero (opens in a new tab)