What to Buy and What to Build in Renewable Energy Data Infrastructure

A Digital Control Platform (DCP) is the data infrastructure that connects, collects, normalises, and manages operational data from renewable energy assets. Most operators agree they need one. The harder question is which parts to buy and which to build.

In The Build Trap, we looked at why IT teams are drawn to building everything themselves, and what that choice really costs. This post looks at the other side: what a commercial platform should handle for you, and where your own engineers can add the most value.

What to Leave to a Platform

A globally adopted commercial solution is the more cost-effective means for addressing the core data requirements all renewable energy companies have in common. The leading solution in the space has proven scalability across massive portfolios while minimizing maintenance and operating costs. Critically, a commercial Digital Control Platform can be deployed in days and connect dozens of plants and tens of thousands of pieces of equipment in a matter of weeks–dramatically speeding the path to digital transformation compared to months or years of custom development.

Every renewable energy operator shares the same foundational data requirements. These are best handled by a proven commercial platform, not custom development:

Plug-and-play data collection infrastructure is the foundation—the ability to easily integrate any renewable energy data source and reliably consolidate data in the cloud. The experience should be as simple as a mobile phone app store: pre-built plugins downloadable from a central hub in seconds that start collecting and normalising data immediately. One compelling reason to rely on a commercial solution is access to a vast library of such plugins, kept up to date as firmware evolves and new equipment models emerge.

Security and regulatory compliance are mission critical, not merely table stakes. Requirements are ever evolving, and most IT teams don’t have the requisite domain expertise to keep up. Cybersecurity controls and immutable audit trails to support compliance with critical infrastructure regulations should be built into the architecture.

Equally critical is centralised management of remote data collection technology—centralised monitoring, patching and updates, backup and recovery, and remote deployment of new plugins when firmware is updated or equipment refreshed. Without these capabilities, managing security across hundreds of distributed sites becomes an operational nightmare.

Cloud operations infrastructure handles the undifferentiated heavy lifting—storage systems for time-series data, backup processes, disaster recovery capabilities, and scaling infrastructure that grows with your portfolio. Critically, it should enable secure data sharing with partners, vendors, and third-party applications without compromising control or creating cyber risks.

Before developing a digital control platform in-house, executive decision makers should ask themselves: what are the true costs—including salaries and benefits—of reinventing the wheel? Consider not just the initial development investment, but the ongoing cost of maintaining a home-grown solution as technologies and regulations evolve. Finally, they should factor in the flight risk of internal experts: when they leave, they take irreplaceable institutional knowledge with them. Who maintains the home-grown system then?

The question isn’t whether you can build it. The question is whether you should, and what you’re giving up by making that choice.

Where to Invest in Building

Differentiated Applications are where your team should invest their time and expertise. Your proprietary forecasting models, unique optimisation algorithms, custom analytics that answer your investor’s specific questions, and specialised integrations with your internal systems represent genuine competitive advantages. These are worth building because they make your organisation distinctly better at what you do.

Consider what truly differentiates leading renewable energy operators: the ability to predict equipment failures before they impact production, optimise dispatch decisions in real-time based on market conditions and storage capacity, or provide investors with insights that go beyond standard performance metrics. While these capabilities rely upon quality, accessible data, the real return on investment comes from focusing engineering resources on extracting insights—not on building and maintaining the data infrastructure itself.

When your engineering team isn’t consumed by maintaining data pipelines and troubleshooting connectivity issues, they can focus on building machine learning models that identify degradation patterns across your fleet, developing algorithms that optimise maintenance scheduling based on weather forecasts and crew availability, or creating dashboards that help asset managers make faster, better-informed decisions.

The goal is to spend your engineering resources here, where the return on investment is highest. Every hour your best engineers spend on undifferentiated infrastructure is an hour they’re not spending on capabilities that create measurable competitive advantage.

To see how buying and building work together in practice, read The Hybrid Approach: Building on a Shared Data Foundation.