Don’t let the mediocre be the enemy of the good
“Don’t let the perfect be the enemy of the good”
Oft-cited to help motivate us to get on with making something.
But what happens when we’re not even at ‘good’ yet?
Sorting out today’s challenges needs consideration of what gets ‘embedded in the system’ so that, instead of the 100x impact we need, we stumble into creating 100x friction in a few years.
There is a bar for good enough.
Watching the unfolding developments in data sharing, with environmental reporting as an exemplar of the size of the challenge, we are still very far away from good.
For example, when I look at the landscape of carbon reporting, I see necessary progress from global standards bodies and regulators to mandate that companies must report. This will impact every business (not just the big ones) because those standards mandate that lenders (e.g. banks) must report on the businesses they are lending to (i.e. pretty much every business).
Note the emphasis on mandate and must. This isn’t going to be optional.
The challenges
The natural response to Big Problems is to say things like:
- We need to start somewhere, so let’s create some approximations that look like things we already do
- Let’s start by gathering all the data in one place
- We know this is a global issue, but we need to create something centralised to start with so we can control it
(1) We need to start somewhere so let’s create some approximations that look like things we already do
Our approximations of investment risk for climate are not yet deeply rooted in reality — we don’t know what the real impact of most of our low-carbon investments will be. If I was to ask you to make a financial investment where I could say your bank balance was ‘about $100 plus or minus $50’ you wouldn’t give me your money. Right now, ‘carbon reporting’ has error bars. Large ones.
People are reporting (because they must) and investing (because they also, must) but there is very scant data that shows that $X invested will link to exactly Y tonnes of climate impact. I don’t (just) mean offsetting, I mean exactly how much will I reduce my footprint by if I invest in changing a process. This is ‘okay’ (for some definitions of okay) for the business-as-usual economy, where market corrections emerge over time.
I’m confident we’re investing in a lower-carbon future, but I’m not confident that we’re investing in a net zero future. With climate, physics doesn’t care about our economy. It matters today, not tomorrow, that we have the right numbers.
(2) Let’s start by gathering all the data in one place
This is still the go-to.
It ‘feels’ safer and easier to control. Everyone can kind of get their heads around ‘building a database’. I’ve, covered, this, many, times.
Except, everyone makes their own. They’re mostly tech-first, not market-first. They don’t scale. They are, despite the marketing hype, not interoperable. It’s [still] a mess. It’s going to get a lot worse.
The challenge is that everyone is happy to collect data as long as they don’t need to share theirs.
And, there are $100M’s (hundreds of millions) being invested in private sector companies to create the next generation of eco-unicorns (whether software solutions, insurance companies or rating agencies). The castle & moat business models that these rely on are already at play, and that’s baked into their design.
(3) We know this is a global issue but we need to create something centralised to start with so we can control it
There are over 300 million companies in the world. Most large companies report over 70% of their carbon footprint is in their supply chains (e.g. SMEs). For lenders, the majority of their carbon footprint is in their customer chain (e.g. SMEs).
How are we going to collect, check, calculate, verify, audit and share this data between organisations, across borders, in a comparable manner — and doesn’t undermine business confidentiality or national security?
Part of the solution is to think differently about the market architecture for a data-enabled future
So, what can we do differently? What things can change, and what things won’t?
I doubt we can change the castle & moat business model, so let’s not try.
What we can do now is change how we design data markets from the outset to connect, not [just] collect.
Doing so would be good news for businesses. If they do this, they’ll save money and get more and better data faster, and at scale.
The good news for everyone else is it can help create a race-to-the-top on insights instead of just relentless monetisation of the raw data, while also putting in place the right protections and security that everyone needs (including the businesses themselves), so everyone can engage.
The key is, in business language, to shift where the line is on ‘pre-competitive’ access to data. To achieve this, we must ensure that the right foundations (robust data governance, technical and legal interoperability, common processes) are in place. The outcome will be that we can commoditise access to data, while enabling the value of data to be paid for or exchanged.
The bar for good should be increased competition on analytics and measurable impact, not on the ‘biggest database’ (big data is so 1990s).
In 2024 good should assume (secure, permission-based, valued) access and unleash the power of our systems (human, financial, technical — including AI) to deliver the changes we need, quickly. Really quickly.
The foundations of this have very little to do with ‘web tech’ (it’s already built), and a lot to do with culture, process, law and policy. If you’d like to learn about how we’re doing in one area, to help automate carbon reporting for every UK SME, see https://ib1.org/perseus
What else?
I may write equivalent pieces on data sharing in other areas we are working on, such as finance, energy, water, transport, buildings, and agriculture.
But the tl;dr is the patterns are all identical.
The challenges as large and (really) nothing to do with web technology, despite all the hype. The likelihood of making outcomes good, or mediocre, are the same in every sector I’ve engaged with.
Of course, with climate, mediocre means ‘absolutely catastrophically terrible’.
(see the solid black line)
