When I speak to peers and clients about sustainability, I begin with a simple image: a town where everything is designed to be used, repaired and reused rather than thrown away.
That idea of keeping value in products and materials for as long as possible defines the circular economy – a shift from ‘take, make, dispose’ to smarter resource use.
A question moving from lecture halls to boardrooms is whether emerging digital tools can help scale this model. One concept, still largely theoretical, is ‘predictive blockchain’.
Blockchain records information so many people can trust it has not been secretly altered – a public ledger logging who owned a product, when it was repaired, or where its materials came from. Predictive analytics uses past data to estimate what may happen next, such as when a battery will fail or how many used phones will be returned for recycling.
Combine the two and you get predictive blockchain: trustworthy product records paired with forecasts about their future, where those forecasts could trigger actions such as arranging repairs or unlocking performance-linked finance.
Circular systems struggle with unreliable data and uncertainty about future material flows.
If manufacturers know what materials will return and when, they can design for repair and remanufacture. If lenders can rely on verified recycling forecasts, they may finance circular models more confidently.
Yet this pairing remains largely conceptual. We have ledger-based tracking and advanced forecasting tools, but integrating them into systems that automatically act on predictions demands caution. Rushing such tools into production without safeguards would be irresponsible.
For Kenya and the wider African context, the stakes are high. Effective circular systems could create jobs in repair and refurbishment, reduce dependence on imported raw materials, and ease waste pressure on communities and ecosystems.
But technology does not automatically deliver these gains. If affordable only to large firms, or if it locks small enterprises into costly platforms, it may widen inequality. Informal waste pickers must see genuine inclusion and fair pay, not digital systems that sideline them.
This is where the triple bottom line matters. Any blockchain-based solution should be judged on People, Planet and Profit. Does it improve incomes and rights for informal workers and small businesses? Does it reduce extraction and pollution across product lifecycles? Does it create long-term value rather than short-term returns?
Risks are real. Immutable ledgers can enable surveillance if sensitive data are mishandled. Predictive models may encode bias, disadvantaging smaller suppliers. Even energy-efficient blockchain systems rely on hardware with environmental footprints.
As citizens, policymakers and business leaders, we should demand rights-respecting design, inclusive financing, independent audits of data and models, and open standards that prevent market capture.
Used wisely, digital tools can support a fairer circular future. Used carelessly, they risk becoming impressive dashboards with little impact on the ground.