Cambridge University Press & Assessment – AI Energy Management in Action: How Intelligent Monitoring Uncovered Hidden Waste and Cut Costs

Re-watch the webinar with CUPA

About CUP&A and the initial challenge

Cambridge University Press & Assessement (CUP&A) is a world-leading academic publisher and education provider with a broad UK footprint. Sites vary in age, purpose and infrastructure maturity, which historically made it challenging to create a single, trusted view of performance. CUP&A has clear carbon ambitions, including a 72% reduction by 2030 and net zero by 2048. Progress to date is substantial, with a 35% reduction across the wider sustainability programme and a 45% cut in energy-related emissions since 2018. However, much of this progress relied on manual analysis.

“I was spending hours trawling through spreadsheets and BMS reports, trying to spot inefficiencies. We knew there were savings to be made, but it was incredibly time-consuming.”  Peter Lumb, CUP&A.

To scale improvements, the organisation needed faster insights, a shared portal, and a replicable method for university energy savings.

Bringing the data together for consistent visibility

Working with Optimal Monitoring, CUP&A integrated billing, BMS, solar generation and tenant sub-meter data into a single platform. Once the data pipelines were established and quality-checked, EMMA AI analysed historical and live patterns together. This surfaced issues that traditional monthly reporting can miss, such as late lighting, overnight cooling and air handling units running out of hours. The phased UK rollout began at the Triangle, UPH, and Cass sites, supported by targeted submeters and corrections to legacy data quirks. The approach created a robust baseline that underpins repeatable university energy saving across the estate.

“We’d already proved there were inefficiencies in our estate. Emma AI gave us a faster, more effective way to spot them — often in days instead of months.” – Peter Lumb, CUP&A.

From insight to action in weeks

Emma AI translates anomalies into plain language alerts that quantify both cost and carbon. One retrofit office zone revealed an inefficient on-and-off cycle on an air handling unit, estimated to cost roughly £5,000 per year. That evidence supported a plan to upgrade controls. At an office site, EMMA AI identified chillers running outside scheduled hours. Correcting schedules is expected to save about £8,000 per year. In an events space, simple time clock resets, stopped out-of-hours air conditioning and removed unnecessary consumption.

“Within weeks we had a long list of actions, from small fixes to larger projects. Some were as simple as incorrect time clocks — but together they were costing thousands each year.” Peter Lumb – CUP&A.

By attaching pounds and kilograms of carbon to each issue, EMMA AI makes ownership clear and accelerates university energy saving without debate over data.

Why CUP&A chose EMMA AI

CUP&A selected EMMA AI because it delivers measurable results quickly without capital expenditure. Deployment is software-led, which means value arrives before any hardware changes are required. Automated data collection supports ESOS evidence and governance needs by providing a clear audit trail. Crucially, the platform goes beyond raw numbers. It turns detection into cost-effective recommendations that facilities teams can implement straight away. The shared portal also strengthens collaboration between sustainability, property and finance. Everyone works from the same information, which keeps discussions focused on root causes and fixes. This shared rhythm of review and improvement supports long-term university energy saving while building confidence in the underlying data.

“Emma AI doesn’t just give us data — it puts a cost on inefficiency. That makes the case for investment far stronger.” – Peter Lumb, CUPA&A.

Embedding a proactive operating model

With EMMA AI in place, CUP&A has shifted from reactive investigation to proactive management. Typical issues uncovered were each worth between £5,000 and £8,000 per year when corrected. Those savings compound across a multi-site estate and translate directly into reduced emissions. The proven UK results supported expansion to the organisation’s two major production facilities. The first international deployment is underway in Singapore, and the team is exploring integrating footfall data to align plant schedules with actual occupancy better. This blend of analytics, targeted metering and operational discipline is creating a scalable foundation for university energy saving at home and abroad.

“Emma AI has become my go-to portal for energy data. Everything is in one place, and it gives us real insights we can act on.” – Peter Lumb, CUP&A.

Impact to date and what comes next

CUP&A’s wider sustainability programme has already delivered a 35% reduction in carbon emissions, including a 45% cut in energy-related emissions since 2018. EMMA AI has reduced manual analysis time, exposed avoidable spend worth tens of thousands of pounds and helped site teams act sooner with greater confidence. The following steps focus on deepening sub-metering where it adds value, broadening international coverage and linking insights to planned lifecycle upgrades. By quantifying waste in both financial and environmental terms, Emma AI keeps momentum high and ensures university energy saving remains a daily practice rather than an occasional project.

“We always knew there were opportunities, but Emma AI has helped us quantify them. It’s made energy savings quicker, clearer, and easier to deliver.” – Peter Lumb, CUP&A. 

Summary

For CUP&A, EMMA AI has turned disparate data into targeted action. The platform streamlines analysis, empowers local teams and delivers clear cost and carbon outcomes. With proven UK performance and international trials underway, CUP&A is accelerating toward its 72% by 2030 and net-zero by 2048 goals while embedding practical, repeatable university energy-saving measures across its global estate.