Digital Business & Information Systems
A prescriptive-AI carbon platform that turns sustainability from compliance reporting into emissions reduction.
The need
Most companies treat carbon tracking as a compliance chore. The opportunity was to make it operational: not just measure emissions, but actually reduce them, and turn that into a competitive advantage in the run-up to the EU's 2030 targets.
The challenge
Plenty of tools already track and report emissions. The real gap, and the hard part, was the prescriptive layer: recommending concrete actions a business can take, and getting an organisation to actually trust and act on AI recommendations embedded in its ERP.
What I made
I designed a prescriptive-AI platform that ingests internal ERP, supply-chain and external climate and regulatory data and surfaces prioritised actions (reroute shipments, switch suppliers, adjust schedules). I structured the Why / What / How case, a tiered multi-tenant SaaS model, competitive benchmarking against tools like Ecochain, and an adoption analysis through Socio-Technical Systems theory.
The outcome
We presented the concept across a full day at Deloitte's headquarters, in their main hall, where Deloitte assessed the work.
Key points
- Designed a prescriptive-AI concept that recommends actions, not just dashboards
- Architected three data streams: ERP and IoT, supply-chain, and external climate feeds
- Structured the full Why / What / How case with benchmarking and a tiered SaaS model
- Analysed adoption through Socio-Technical Systems theory; presented at Deloitte HQ