Book review: Measuring Good Business - Chap. 3
Marie-Josée (MJ) Privyk
Human. Agent of change. ESG subject-matter expert and advisor. All insights are mine, not Gen AI's. How can I serve?
Book review: Measuring Good Business - Making Sense of Environmental, Social and Governance (ESG) Data - Chapter 3 - Good measurement
In my introductory post, I explained that I have endeavored to summarize key insights and takeaways from this book (which I highly recommend) in five weekly posts, each one corresponding to a different chapter. This week is Chapter 3: Good measurement.
(I offer my gratitude to the author Richard Hardyment for his thorough research and captivating narrative.)
This chapter is about explaining how ESG and sustainability-related performance are measured, knowing the difference between what can and can’t be measured, and recognizing that the ultimate objective of sustainable business practices falls in the latter category.
Why sustainability is not like financial accounting
The author points to four key differences between financial accounting and sustainability measurement:
Newtonian measurement can’t apply to complex phenomena
The author very interestingly raises the point that ‘Newtonian’ or representational measurement applies well to things that are readily observable and can be counted. The numbers mean something real that is consistent across space and time. They are stable, linear, and precise, and therefore standardizable and comparable. They work well for measuring things like carbon emissions, injury rates, or volumes of waste.
But because sustainability matters are complex and multidimensional, we cannot directly observe and measure them. They are “diverse, dispersed, imprecise, non-linear, contextual, dynamic, ambiguous (and sometimes contradictory)”. Most social matters are subjective experiences “held in the minds and hearts of people” – all of which makes them “fiendishly hard to standardize”. Indeed, it’s difficult to quantify social justice, natural capital depletion, or a sustainable supply chain.?
“The big mistake of measurement is to assume that we can lift the methods that work for physical representations (emissions, water, waste) and transfer them to the rest of the canvas of sustainability. The problem arises when the assumptions, simplifications, categorisations and standardisations that work so well for Newtonian topics are transferred wholesale to other fields.”
For the author, the vital step in measurement is to “be crystal clear about what we mean from any term. [...] It is only once we have been precise in our definitional scope that we can take the next step: carefully selecting the right metrics”.? I couldn’t agree more.
The four types of metrics
Since complex phenomena cannot be directly observed or measured, we need proxies, which is where metrics come into play. The author describes four types of metrics, noting that “most people assembling reports and using data fail to realise the profound differences between these four types. But they are crucial to understanding why sustainability measurement so often misses the mark.”
The first three don’t tell us much about ‘what happened’, which is where outputs come in. Most sustainability metrics are output metrics. But when it comes to measuring a sustainable business, what we really want (dream of) measuring is outcomes and impact.
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However, as the author points out, there are no outcome metrics per se. Therefore, there is an inevitable gap between numbers and outcomes – “the trick is to recognise this and try to make it as small as possible”. Numbers and data are proxies for reality, they are not reality itself and cannot substitute themselves for the unmeasurable outcomes and impacts. We must be careful not to put more meaning in the data than there is. Good measurement is about finding useful proxies for the outcomes we want to know about.
The author also reminds us that “all the data in the world means nothing without context.” Context matters because:
To better grasp sustainability considerations and attempt to measure them, the author suggests adopting systems thinking. Describing a company’s footprint as “a web of relationships: complex, ambiguous, dynamic, and evolving through feedback loops and adaptation”, he posits that if we look only at the parts, we cannot see the whole. “To make a complex system measurable, we select parts to examine. We scrub out the context. We break the world down into smaller units. We then make the mistake of assuming that the whole is the sum of the parts [...] Starting with a systems mindset means we can drill down with more confidence, mindful of what we are missing as well as what we are seeking when we select metrics.”
Not everything that counts can be counted
The author speaks of? a “ginormous gap” between what is known and unknown or unknowable, between what we can see and not see, or what we can measure and not measure. When it comes to corporate reporting, this gap is reflected between what is real and what is disclosed. “It’s not possible for any company, or a third party, to collect data on everything. There are physical and resource limits. Corporate reporting goes through a giant filter where legal and reputational risks alongside financial cost, commercial confidentiality and practical considerations whittle down the potential list further.”
The contents of this entire chapter certainly help to gain a fuller understanding of the famous quote that “not everything that can be counted counts, and not everything that counts can be counted” (Cameron). In other words, just because we can’t measure something, doesn’t mean it does not exist or it’s not important, not valuable… or not worth managing.
Next up: Chapter 4 - Making a difference
Bringing people, planet and profit together | Affable Chap.
1 个月Another great post MJ! When considering this, its correct, as you are applying Newtonian thinking (relatively linear) to an ecosystem of issues. This is very prevelent when looking at PE or Banks attempting to value or measure ESG as part of due diligence: its still stuff in a linear/process based mindset. This has then made how you actually measure the impact of a companys ESG performance poor as the measurement is only as good as the data or the quantum, and the quant used is limited...and a bit lazy to be honest. As ESG evolves into focussing on modern slavery, human rights in value chains etc it becomes harder, as you can't offset slavery. However, with some dyslexic thinking (shout out to my fellow dyslexics!) we apply abductive reasoning versus newtonian based logic to help measure impacts because abduction can start to see the world as an ecosystem of seemingly non connected issues that are interconnected. Anyhoo. Its a complex issues, I still think the best model so far is the Yanagi model - pretty amazing from Japan https://www.ft.com/content/481d4e1a-49f0-41bc-84f8-5300409e2ffd
Human. Agent of change. ESG subject-matter expert and advisor. All insights are mine, not Gen AI's. How can I serve?
1 个月?? About the book: https://www.richardhardyment.com/measuring-good-business ?? Frankly Speaking Podcast: https://podcasts.apple.com/de/podcast/51-richard-hardyment-how-to-measure-good-business-and/id1644106274?i=1000659472892&l=en-GB
Retired Sustainability & Post-Growth Optimist at Lean.Earth
1 个月As you had promised in the previous post, the book is getting more interesting and closer to a systems view of organizations and the insights of W. Edwards Deming who noted some 50 years ago: "the most important things we need to manage can't be measured." I will have to add this one to my reading list... Measurements for the benefit of remote non-participants often mischaracterize the 'in-process' situations and can drive incalculable dysfunction and misdirected effort within an enterprise. Without careful consideration, imposing new quantitative targets puts indefinable stress on the patterns, relationships and processes that need to be adapted to align with sustainability. This is especially true for the many context-free sustainability metrics currently in vogue. In some ways, sustainability in practice means the slow death (or at least de-emphasis) of ‘what cannot be measured cannot be managed’. Organizations are organisms, not machines and sustainability requires recognizing the importance of this distinction in practice.