One of the biggest challenges companies face with their product footprinting projects is ad hoc impact data collection requests and the resulting sense of overwhelm. Often because they are not yet set up for a structured data collection journey. But this is exactly where the opportunity lies.
By building the right data foundation early, you can shift from reactive data collection to a clear, scalable and reusable approach – reducing delays, improving data quality, and setting yourself up for long-term success.
In this video episode, we walk you through a practical 5-step framework to prepare your data foundation, helping you set up your product footprinting efforts for success from the start.
The 5 steps covered in this video:
- Step 1: Clarify the business goal for product impact calculation
- Step 2: Map out the product system across your organization
- Step 3: Identify the data gaps
- Step 4: Set up internal data quality rules
- Step 5: Turn your data setup into a repeatable system – and match it to the right LCA software
Video Transcript:
Pratik: Do not wait for the perfect data. Continuous improvement is way better than delayed progress.
Emma: It’s important to keep things feasible and in line with your business goals.
Pratik: This five step framework will help you think ahead and plan better so that from the same foundation you can generate multiple outputs managing the product. Sustainability isn’t easy. Regulations keep shifting. Expectations are changing, and the playbook isn’t always clear behind the product. Impact is our series for exactly that reality. Your front row seats to the questions best practices and operational decisions Sustainability teams face every day to understand, communicate, and improve their product’s impacts.
Pratik: Hello guys. Welcome back to another exciting episode of our series Behind the Product Impact. Are you excited, Emma?
Emma: Yes, definitely. Because I really like the topic we’re talking about today, which is building a foundation for your data collection process. And for my projects at Ecochain, I’ve seen a lot of times that data collection and starting to do your product footprinting project can be very overwhelming. And it usually happens as an ad hoc process because people don’t have the overview and they don’t really yet know exactly what is needed. Which then leads to maybe quality issues, delays, and stuff like that. So in this video we will talk you through a five step process, to build this foundation for your data collection process and be more successful in your product footprint, endeavors, and also, prevent quality issues later on.
Pratik: Yeah, exactly. This five step framework will help you think ahead and plan better so that from the same foundation you can generate multiple outputs as required by your business objectives.
Emma: So with that being said, Pratik, what would be the first step you would take to build this data foundation?
Pratik: If I was a sustainability manager, I would start by identifying my business objective. Why do I want to perform this product impact calculation? For example, if my objective is to communicate the carbon number, I would go with PCF analysis. If my business objective is to improve the product. I would do ecodesign, or if I need some tendering process, I would need the analysis in detail, which is verified by the third party.
So depending on the business objectives, the foundation of the data may change. That being said, what I also want to emphasize is that: Do not wait for the perfect data. Continuous improvement is way better than delayed progress. That’s my motto.
Emma: I also think that in general, perfection is very hard to achieve in LCA in general. So I completely agree with that. And maybe what Pratik just said sounds quite overwhelming because of course, Pratik, you know what to do for which, business requirement. But maybe people that haven’t done these projects yet, actually don’t know. They just know their business requirements, but not exactly how to get there. And there’s actually no shame in that. Because everybody needs to learn this whole field is coming up. So that’s where you can also, of course, get some experts’ advice on how do I actually reach my business objectives with this product footprint thing that I want to do?
Pratik: So Emma, once I fix my business objective, how do you proceed? Because you have helped a number of customers at Ecochain. What would you do next?
Emma: So the next step would be to familiarize yourself with the product system of your organization and to just really get to know the system. And this can be of one product, of course, if you’re going for a model of one product, but this can also be many products at the same time, so that doesn’t really matter. But how you do that is first, you can start by finding a flowchart somewhere in your organization. There’s probably already one laying around there. And you can just start from this one, and really look at it and see like, are there things missing here? Do I maybe need a different zoom? What kind of data would I need based on this flowchart?
And then you can start expanding on that. And then the second step would be to start identifying key data points. So within this whole step. You wanna ideally do this based on impact. So the impact that these points have on your final results. So we always use the 95/5% rule.
That means that 95% of the data should be pretty good quality and then the final 5%, you can also use assumptions maybe to fill that up or secondary data, which we’ll get to later on in the video. However, it is hard to do when you don’t actually have your model yet, so you don’t actually know what makes up the main impact. So generally you can say that, materials and production processes, those things are really relevant and that transport is something that probably doesn’t have the biggest impact on your results. So there you can make more assumptions.
Pratik: So if I summarize it correctly, you’re saying spend your impacts, where the maximum impact lies.
Emma: Cause you already said it. Perfect data is not what we’re looking for. And it also doesn’t exist in LCA. It’s important to keep things feasible and in line with your business goals. goals And related to the whole data points, because of course you might have identified these data points. But we would also say, go one step further based on this map that you have, and also already map the stakeholders you need to collect this data. Because these people are so important for you to actually get the data to understand it. And these stakeholders can be internal, but also external stakeholders.
Pratik: Exactly. Very well pointed out. Emma. Supply chain can be one of the major external stakeholders. How to get data from your supply chain? How to build a foundation to get that data in your LCA calculations? We will be doing a separate video on that. Please stay tuned.
Emma: So Pratik, now that we’ve mapped this entire product system, what would be the next step for you?
Pratik: The next step, what I would follow is identifying the data gaps. And in the data gaps, what I mean is, identify what is the availability of my primary data and the secondary data. What I mean by primary data is, for example, if I am a company who makes steel products.
And I buy that steel from the supplier. If my supplier provides me the impact number for that complete steel manufacturing, I can consider that as primary data for my product, which is produced from that steel. However, the majority of the time we have seen that either the supply chain for the steel originates in India or China, and the companies do not understand how that impacts their final product.
Precisely for such a scenario. There exists something called LCA databases. Which helps us to map the supply chain originating from China or India for the steel manufacturing till the steel is getting produced. And if we use that data, we call it secondary data.
Emma: And these data spaces are quite big and they’re also actually quite commonly used, and I think from our experience as well at Ecochain of course primary data is always preferred, but in reality, often it’s just not there. And that might change in the future, but for now we definitely say that you can also have perfectly fine and good quality results with secondary data.
Pratik: And what I need to stress here is every LCA software provider relies heavily on the secondary databases, like Ecoinvent. And during verification as well, it is agreed upon to use secondary databases. So you do not have get stuck on always collecting accurate and perfect data.
Emma: So Pratik, we’ve talked about data gaps, but what would you do next after identifying these data gaps?
Pratik: The next step after identifying data gaps, is setting up internal data quality rules. And what do I mean by internal data quality rules? We need to check the data against consistency, representativeness, temporal and geographical coverage and uncertainties in this data. Why is it important? Because it is often used for verification as this criteria for your data quality checks. And moreover, this will set a robust foundation which you can scale up.
Emma: Okay good points. One thing that I would like to add to that is that we’ve talked before about the stakeholders, mainly the internal ones. And I also think for this data quality, apart from setting these rules, it’s really important to check with these stakeholders. Ask them: What could be issues with this data? What do you already know from your experience with this data? And also, what are small details that we might need to pay attention to in order to ensure that we’re using the right data?
So for example, in ERP systems, this might be the versioning. So there might be multiple versions of the same Bill of materials. So we need to use the right version. Otherwise you might have an incorrect or outdated model.
Pratik: Yeah, exactly. So now we have covered four steps. What would you suggest as a final step?
Emma: The final step would be to, first off, summarize everything that you have done in the previous step into a plan and make sure you have this plan that you can reuse for every time you wanna collect your data. And secondly, also part of this final step is to add for each data point or data system, how can you get the data out of this system? Is there a possibility for an API, is there maybe an export functionality? What comes out of the export? Are these PDFs, are these Excel files? And this will really help you in the future to get your data.
Pratik: What you are touching upon is a very important point, because that will determine your choice of your product impact calculation software. Because the software has to complement your internal systems, which are already in place. And I think this point will help them choose the correct software.
Emma: Yeah, I couldn’t agree more. That marks the end of this video. So I’ll just quickly sum up the steps to build your data foundation. So first off, identify your business goals and see what you need to do to get there.
Then, familiarize yourself with the product system that is part of this project. Identify data gaps that you might have and make a plan for secondary data, make data quality check rules. And finally, ensure you know how to get the data out of your systems and into another system for your products impact calculation.
If you wanna know more about these topics, please check out our website. We will have some blogs coming out soon as well. And we also have a YouTube channel where we will post more of these type of videos to give you more information.
Pratik: Yeah, and if you have some pressing questions, put them down in the comments and we are happy to answer them. As always. Thank you so much, Emma, for having me in this video.
Emma: Yes, thank you Pratik.
