Executive Summary

A UK renewable energy company providing battery storage systems to film and TV productions had a data problem: every deployment generated hundreds of megabytes of telemetry data they couldn't turn into client reports at scale. We delivered two analytics systems — an automated reporting pipeline processing 7.2 million records in under 3 minutes, and a generator right-sizing analysis revealing 60% over-specification across the industry.

The Challenge

Battery energy storage systems generate enormous volumes of data. A single 117-day deployment produced 352MB of CSV data with 7.2 million telemetry readings — one reading every 2-3 seconds tracking power output, generator status, battery state of charge, and dozens of other metrics.

The data told an incredible story — batteries saving hundreds of litres of diesel, cutting CO₂ by nearly two tonnes, reducing generator noise by 85% on set. But that story was locked inside incomprehensible spreadsheets that standard analysis tools couldn't even open.

Meanwhile, the entire film industry was wasting money on oversized generators with no data to prove it.

What We Built

Battery Performance Reporting

A streaming analytics engine that processes telemetry files of any size line-by-line without loading them into memory, calculates 15+ performance metrics, and generates professional branded PDF reports with interactive charts.

The system classifies every data point into operating modes (battery, generator, idle), calculates fuel consumption point-by-point against manufacturer efficiency curves, and produces daily breakdowns of all metrics — from energy delivered to CO₂ avoided.

Generator Right-Sizing Analysis

Using load monitoring data from a catering operation on a film production, we discovered something the industry wasn't talking about: a 100kVA generator running at barely 53% utilisation on its most loaded phase, with severe phase imbalance meaning one phase was doing nearly all the work.

With proper load balancing, a 40kVA generator would suffice — a 60% reduction.

Real-World Results

Short Film Production (5.4 days)

Extended Production (117 days)

Generator Right-Sizing (Catering Operation)

Business Impact

Reports that took hours of manual work now generate in 2-3 minutes with ±1% accuracy validated against manual calculations. The client can now prove quantifiable fuel savings, CO₂ reductions, and cost savings to every customer, transforming raw data into their most powerful sales tool.

The generator right-sizing discovery opened an entirely new revenue stream: monitoring-as-a-service. By proving with data that productions routinely over-specify generators by 40-60%, they can offer right-sizing consultancy that saves clients money whilst reducing environmental impact.

No other battery rental provider in the film and TV sector offers this depth of automated analytics.

The Economics

One 117-day deployment saved £1,078 in fuel alone. Across a typical portfolio of 20+ deployments per year, that is £20,000+ in documented client savings the company can put on the table in every sales conversation. The reports themselves become the most powerful retention and acquisition tool in the business, every customer leaves with hard evidence of the environmental and financial value delivered. The right-sizing service multiplies the value: a 60% reduction in generator specification across even ten productions per year saves clients five-figure rental costs, with the monitoring service paying for itself on the first job. The system is the product, not just the reporting layer behind it.

Why It Worked

The film and TV industry has a 'better safe than sorry' mentality with generators, leading to massive waste. Generic analysis tools crash on 350MB files. Average-based fuel calculations miss the non-linear relationship between load and consumption.

We solved these problems by understanding the specific context — the power requirements of film productions, the efficiency curves of generators, the operational patterns of on-set catering. That context turned noise into intelligence.

Key Takeaway: The most valuable data is often the data you already have but can't extract. When you build the right pipeline with the right context, raw telemetry becomes a competitive advantage.

Executive Summary

A UK renewable energy company providing battery storage systems to film and TV productions had a data problem: every deployment generated hundreds of megabytes of telemetry data they couldn't turn into client reports at scale. We delivered two analytics systems — an automated reporting pipeline processing 7.2 million records in under 3 minutes, and a generator right-sizing analysis revealing 60% over-specification across the industry.

The Challenge

Battery energy storage systems generate enormous volumes of data. A single 117-day deployment produced 352MB of CSV data with 7.2 million telemetry readings — one reading every 2-3 seconds tracking power output, generator status, battery state of charge, and dozens of other metrics.

The data told an incredible story — batteries saving hundreds of litres of diesel, cutting CO₂ by nearly two tonnes, reducing generator noise by 85% on set. But that story was locked inside incomprehensible spreadsheets that standard analysis tools couldn't even open.

Meanwhile, the entire film industry was wasting money on oversized generators with no data to prove it.

What We Built

Battery Performance Reporting

A streaming analytics engine that processes telemetry files of any size line-by-line without loading them into memory, calculates 15+ performance metrics, and generates professional branded PDF reports with interactive charts.

The system classifies every data point into operating modes (battery, generator, idle), calculates fuel consumption point-by-point against manufacturer efficiency curves, and produces daily breakdowns of all metrics — from energy delivered to CO₂ avoided.

Generator Right-Sizing Analysis

Using load monitoring data from a catering operation on a film production, we discovered something the industry wasn't talking about: a 100kVA generator running at barely 53% utilisation on its most loaded phase, with severe phase imbalance meaning one phase was doing nearly all the work.

With proper load balancing, a 40kVA generator would suffice — a 60% reduction.

Real-World Results

Short Film Production (5.4 days)

Extended Production (117 days)

Generator Right-Sizing (Catering Operation)

Business Impact

Reports that took hours of manual work now generate in 2-3 minutes with ±1% accuracy validated against manual calculations. The client can now prove quantifiable fuel savings, CO₂ reductions, and cost savings to every customer, transforming raw data into their most powerful sales tool.

The generator right-sizing discovery opened an entirely new revenue stream: monitoring-as-a-service. By proving with data that productions routinely over-specify generators by 40-60%, they can offer right-sizing consultancy that saves clients money whilst reducing environmental impact.

No other battery rental provider in the film and TV sector offers this depth of automated analytics.

The Economics

One 117-day deployment saved £1,078 in fuel alone. Across a typical portfolio of 20+ deployments per year, that is £20,000+ in documented client savings the company can put on the table in every sales conversation. The reports themselves become the most powerful retention and acquisition tool in the business, every customer leaves with hard evidence of the environmental and financial value delivered. The right-sizing service multiplies the value: a 60% reduction in generator specification across even ten productions per year saves clients five-figure rental costs, with the monitoring service paying for itself on the first job. The system is the product, not just the reporting layer behind it.

Why It Worked

The film and TV industry has a 'better safe than sorry' mentality with generators, leading to massive waste. Generic analysis tools crash on 350MB files. Average-based fuel calculations miss the non-linear relationship between load and consumption.

We solved these problems by understanding the specific context — the power requirements of film productions, the efficiency curves of generators, the operational patterns of on-set catering. That context turned noise into intelligence.

Key Takeaway: The most valuable data is often the data you already have but can't extract. When you build the right pipeline with the right context, raw telemetry becomes a competitive advantage.