Welcome back to The Ledger - a weekly briefing at the intersection of business, sustainability, technology and systems thinking. Let’s get straight into Issue #7.
The Big Idea: Data Entropy
Every organisation depends on numbers. But numbers don’t stay still.
Metrics lose clarity the moment they’re frozen in reports, detached from the conditions that shaped them. A baseline that looked solid last year becomes misleading under today’s volatility. A compliance audit compiled over six months is already out of date by the time it hits the board.
This is data entropy: the slow drift from signal to noise. Decisions orbit outdated figures, “optimisations” chase shadows and conviction erodes.
The paradox: companies are flooded with more data than ever, but much of it decays faster than decisions are made. The result is stalled investment, stranded projects and leaders who no longer trust their dashboards.
The challenge isn’t measuring. It’s keeping metrics alive.
Signals from the Noise
What matters, what works, and what’s worth watching.
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⚡ Rice University: Turning waste into energy
Researchers demonstrated how lost energy flows can be recaptured and cycled back into productive use - a reminder that hidden margins often lie in places long written off as “noise.”
🔗 Rice News
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🔍 Design acceleration through iteration speed
Topology optimisation cut design cycles from weeks to days, improving efficiency by 30%. The faster the iteration, the less time entropy has to creep in.
🔗 IPI Singapore
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🌡️ Attribution science is sharpening accountability
A new study tied the frequency of extreme events directly to emissions from major producers. External scrutiny is getting more precise while many internal metrics still blur.
🔗 AP / Nature
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🔄 Storage systems depend on live variability
Research shows long-duration storage underperforms when planned on static averages, but excels when fed live, adaptive data. Stale numbers undermine resilience.
🔗 ScienceDirect
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💸 Europe’s industrial investment freeze
Heavy industry is delaying upgrades - not for lack of capital, but because boards lack conviction in the numbers underpinning ROI. Data confidence, not money, is the bottleneck.
🔗 Financial Times
From the Ground
An operator told me this week:
“We don’t lack projects. We lack confidence. Everyone’s seen the PowerPoint curves, but no one trusts the numbers enough to bet careers on them.”
The Ledger Line
Data entropy doesn’t break machines. It breaks conviction.
End Note
Leaders often assume that more measurement equals more certainty. But in practice, metrics decay faster than they’re acted on.
The next decade won’t be decided by who has the most dashboards. It’ll be decided by who keeps their numbers alive long enough to matter.
If this issue made you think then please do consider sharing The Ledger with someone who this might strike a chord with.
And if you’re fighting data entropy then reply and let me know what’s working or where you’re facing a bottleneck - I read every reply.
Here’s to what’s possible.
Dom