Take a look at the work I done with Aeoni | Part of The Bereau Group.

Data Analytics

Building a Data-Driven Pricing & Sustainability Engine for AEONI

At AEONI, a startup focused on tracking the lifecycle and carbon footprint of office furniture, my role centred around turning complex data into something commercially valuable. The challenge wasn’t just to collect information — it was to structure and apply it in a way that could directly influence pricing, decision-making, and sustainability outcomes.

One of the core pieces of work was developing a dynamic pricing algorithm. Rather than relying on static or subjective valuations, I built a system that could automatically assess the value of furniture based on key variables such as condition, age, and visible flaws. Items were categorised across a clear scale — from new and excellent through to fair and poor — with pricing adjusted accordingly.

From Static Pricing to Intelligent Valuation

The goal was to move away from manual pricing and towards a more intelligent, scalable model. By introducing a consistent framework, the algorithm ensured that pricing remained both competitive and reflective of real-world value.

This allowed AEONI to:

  • Standardise valuations across a wide range of furniture types

  • Reduce reliance on manual decision-making

  • Increase confidence in pricing for both buyers and sellers

It also created a foundation for scaling the platform, where large volumes of inventory could be processed efficiently without compromising accuracy.

Embedding Sustainability Into the Core Model

Beyond pricing, a key part of the project involved integrating environmental impact into the valuation process. This meant going beyond surface-level metrics and working directly with Environmental Product Declarations (EPDs) to understand the true carbon footprint of each item.

By collecting and analysing EPD data, I was able to:

  • Map the carbon impact of materials and manufacturing processes

  • Factor in transportation from origin to end user

  • Build a clearer picture of each product’s lifecycle emissions

This data wasn’t just informational — it became part of the decision-making process, aligning commercial value with environmental impact.

Linking Data to Real-World Outcomes

What made this work particularly impactful was how it connected multiple data points into a single, usable system. Pricing wasn’t based solely on condition or demand — it was influenced by a combination of physical quality, lifecycle stage, and environmental cost.

This created a more transparent and forward-thinking model, where:

  • Buyers could better understand the value and sustainability of their purchases

  • Sellers could price inventory more accurately and competitively

  • The platform itself could position sustainability as a measurable, not abstract, benefit

Creating a Scalable Foundation for Growth

As a startup, AEONI needed systems that could scale quickly without adding complexity. The pricing and carbon modelling approach I developed provided exactly that — a structured, repeatable framework that could handle growth in both inventory and data.

By combining automation with detailed analysis, the platform was able to move faster, operate more efficiently, and offer a more sophisticated product to its users.

A Data-Led Approach to Sustainable Growth

This project demonstrated how data can be used not just to inform decisions, but to shape entire business models. By embedding both commercial logic and environmental insight into the same system, AEONI was able to differentiate itself in a competitive market.

The result was more than just a pricing tool — it was a step towards a more transparent, data-driven approach to sustainability within the circular economy.

Condition vs Value Depreciation Curve Algorithm

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