In environmental science and accounting, as in business, uncertainty is a fact of life.
Neither scientists nor business leaders can operate with 100% certainty. Sometimes the information you need to measure and communicate your corporate or product footprint just isn’t as clear, readily available or precise as you’d like it to be. But uncertainty doesn’t mean the science is flawed — it simply signals an absence of certainty, which, in science, is not only normal, but also expected.
That said, uncertainty can create challenges for decision making around impact reductions or tracking the progress of initiatives.
In this chapter, we’ll explore the topic of uncertainty in sustainability accounting and how to manage it.
Uncertainty can mean many things. In science, it refers to a quantitative measurement of variability in data — the idea that all data have a range of expected values as opposed to a precise point value. In other words, there is a range of possible values within which the true value of the measurement lies. In business, it refers to a state of having limited knowledge that makes it difficult to predict future outcomes.
At Quantis, our definition of uncertainty combines elements of both concepts to reflect the reality of sustainability accounting, which involves the practical application of scientific results in a business setting:
“Imperfect knowledge or reduced precision around a data point or calculation, characterized by a range of possible values within which the true value lies, increasing the complexity of decision-making.”
Though uncertainty is completely normal (and often a driver of progress), it’s commonly perceived as problematic.
At the very least, it might make you feel uneasy. At its worst, it has the potential to lead to some big issues:
Misleading conclusions: In the absence of complete information, people will fill in the blanks themselves. High levels of uncertainty can lead to suspicion of wrongdoing. For example, if our example company communicates that it should reduce its corporate footprint by 20% by 2025 but has underestimated or hasn’t acknowledged the uncertainty that lies in those measurements, its reduction claims could be inflated.
Hidden drivers: If uncertainty is related to smaller drivers, not only will they be overlooked in the footprint, but they also won’t be identified as potential levers of improvement in your roadmap. This could give the impression that the original roadmap wasn’t accurate.
Increased liability risk: Companies may soon be held accountable for their environmental impact and will need to demonstrate and defend the analysis of their impact. Doing so will be difficult with highly uncertain numbers, which could have implications for both the credibility of a company’s sustainability efforts and its brand as a whole.
Of course, running a business while navigating high levels of uncertainty surrounding environmental impacts is entirely possible. Businesses make important strategic decisions under uncertainty all the time — and having been doing so since time immemorial — strategic decisions related to climate-related topics shouldn’t be any different.
Ultimately, how you choose to handle uncertainty will depend on both your level of tolerance (how comfortable you are with it) and whether additional information is needed to allow you to act more effectively and efficiently.
When met with uncertainty, there are two options. You can:
Whatever you choose, the real focus should be on making and accurately tracking progress toward your environmental goals, based on roadmaps that allow for more robust decision-making.
So, how do you do that in practice?
The first step is to measure your uncertainty to establish a baseline. Doing this in year one will help you understand not only the level of uncertainty you’re working with, but also where reducing it is necessary to ensure actions taken to reduce impacts are effective and drive transformation.
Let’s look at an example:
A company has measured its uncertainty and included it in its roadmap. It now wants to make a claim about how it has reduced its footprint. In year one (2018), the company found that the range of uncertainty was 4 MtCO2-eq (8-12 MtCO2-eq). Because the uncertainty was both material and present in key areas identified for improvement, the company decided to try and reduce it by collecting more precise data from key suppliers in 2022. It managed to narrow the range of uncertainty to 2 MtCO2-eq in 2022 (1-3 MtCO2–eq). As this change was driven by data improvements, it required the company to rebaseline its corporate footprint from 2018 (see the figure below). Following rebaselining, the 2018 corporate footprint moved from 10 MtCO2-eq (8-12 MtCO2eq) to 9 MtCO2-eq (8-10 MtCO2-eq). This enabled the company to identify a good confidence impact reduction zone, ensuring that it was indeed reducing its footprint because of its climate roadmap, taking into account the potential impact of uncertainty.
So how do you tackle uncertainty? The steps to understand, measure and take appropriate action are encapsulated in our Assess and Act Loop, an iterative process that ensures your company understands and monitors uncertainty. We urge companies to implement this loop to drive progress and increase the chance of meeting targets.
To tackle uncertainty, you first need to assess it. Not only does it enable you to understand where your company stands, it gives you a starting point to reduce or manage your uncertainty.
Identify where the uncertainty lies and why it exists. Companies should prioritize managing uncertainty linked to major environmental impacts and reputation. Here are some questions to consider:
Measure your uncertainty. As the adage goes, you can’t manage what you don’t measure. Measuring your company’s uncertainty will provide you with insight into the potential variability you face in terms of numbers and clarify the impact uncertainty can have. This information is essential for guiding further action.
Determine your company’s uncertainty tolerance level. In the same way investors have risk profiles (risk averse or risk tolerant), your company will have a level of uncertainty it’s comfortable with. Exceed that threshold and, according to your company’s risk-benefit analysis, you should start to reduce your uncertainty to reach acceptable levels again.
Once you’ve assessed your uncertainty, it’s time to act. There are two options: reduce it or manage expectations.
Reducing uncertainty can be costly, but if it means better environmental outcomes, it’s worth doing.
It requires companies to obtain more accurate and precise data for key drivers or sources of impact. This can be done by:
Sectorial and methodological experts can help you reduce the spatial and temporal variability of key flows, parameters, data quality, emissions factors for key commodities and more. When a proxy does not seem relevant to your context, these experts can help you evaluate the need for more precise guidance and information. It’s important to note that reducing uncertainty will likely mean having to rebaseline.
When making assumptions and communicating about your efforts, err on the side of caution. Conservative assumptions and communications can help set realistic expectations.
If, during the assessment stage, you determine that you don’t need to try to reduce uncertainty, the other option is to manage it. Managing your uncertainty means you’ve set expectations around it and can communicate its reasonableness. Ways to do this include:
When considering whether to take action to reduce uncertainty or manage expectations, use the matrix below to help determine which course of action makes the most sense for your organization.
In the end, measuring, managing and acting on uncertainty in your emissions can help keep your company focused on priority areas and protect your credibility.
We have answers. Get in touch with our team today and let us guide you through the solutions that might help you on your journey toward a sustainable supply chain.
This chapter covers what is considered real progress toward sustainability as you calculate and track changes in your supply chain.
This chapter focuses on how to manage the double counting of emissions reductions when considering real progress toward a sustainable supply chain.
This chapter covers why understanding the concept of supply sheds can help make more active progress and ensure companies will be able to claim progress.
Progress toward a sustainable supply chain hinges on the type of data one is using and why. Here we’ll differentiate the types of data and guide you to choose what’s right for your goals.
This chapter dives deep into tools that rely on primary data and their implications for tracking progress in the supply chain.
06 – Currently reading
Progress toward a more sustainable supply chain is possible even with a fair amount of uncertainty. This chapter covers how to measure and manage uncertainty.
Although it may seem complicated to reduce uncertainty, we tend to do it instinctively in our daily lives. Consider the following exercise from Peva Blanchard, co-founder of Kleis Technology, as an example.
Without using a phone or computer, answer this question: How many streets are there in Paris?
You’re not sure how you can possibly know? Do you want a range, even a ridiculous one?
Let’s see if we can figure it out:
You know that there is more than one street and there are certainly fewer streets than humans in the world.
See, you know *something*. Can we do better than a range from 1 to 8 billion? Maybe we can narrow it to 1 to 2 million since there are around 2 million people in that city?
Surely there are fewer streets than Parisians. Yet, clearly Paris is denser than one person per street on average. There must be around 100 Parisians per street, so let’s get that number down to 20,000 (2 million/100).
One street as a minimum is also an underestimation. I’ve seen more with my own eyes: at least 20 in the neighborhood (arrondissement) where I was staying. There are 20 neighborhoods (arrondissements) in Paris so that’s 20×20 = 400 streets.
We narrowed it down to a range between 400 and 20,000 streets. Daring to go for silly numbers can be liberating. It helps you realize you know more than what you thought you did.
However, be aware of overconfidence: are you tempted to pretend you know more than you really do? Here’s how to mitigate that:
Let’s say that as soon as I asked you the question “how many streets are there in Paris?” your answer was: between 3,000 and 4,000. Now, I’ll offer you two options:
Option 1: I will give you $100 if you are correct, and $0 if you’re not.
Option 2: I will use a wheel of fortune, 10% of this wheel is red and 90% is green. I’ll turn the wheel and if the arrow stops on a green section, I’ll give you $100. If the arrow stops on the red part, I won’t give you anything.
Which option do you prefer? If it’s option 1, you’re probably under-confident. If it’s option 2, you’re being over-confident about your range.
These small tricks are inspired from the book “How to measure anything,” Douglas W. Hubbard.
I won’t leave you wondering: there are 6,486 streets in Paris.
Peva Blanchard, co-founder of Kleis Technology.
Kleis Technology is a company specializing in digital transformation with a strong focus on digital product development.
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