Why Fault Detection and Diagnostics Wasn't Invented by the BMS Industry

Control Versus Intelligence

For decades, Building Management Systems (BMS) have been the backbone of commercial building operations. They control heating, cooling, ventilation, lighting, and countless other systems that keep buildings functioning day-to-day.

Yet despite owning the data and controlling the equipment, traditional BMS platforms were not the organisations that pioneered Fault Detection and Diagnostics (FDD). Instead, the innovation came from independent technology companies focused on analytics, cloud computing, and building performance.

The question is why?

The answer lies in the fundamental difference between controlling a building and understanding how it performs.

Control Versus Intelligence

Traditional BMS platforms were built with a clear objective: reliable real-time control of building systems.

Historically, BMS vendors competed on factors such as:

• Controller reliability

• Front-end graphics and usability

• BACnet and protocol integration

• Alarm management

• Trend logging

• Network architecture

The industry mindset was focused on one question:

"Can we control the building effectively?"

FDD asks a completely different question:

"Can we continuously analyse building behaviour and identify hidden inefficiencies?"

Answering that question requires advanced analytics, contextual logic, rule engines, statistical modelling, machine learning, benchmarking, and workflow management. These capabilities are far closer to a software-as-a-service (SaaS) platform than a traditional controls system.

A Different Business Model

The controls industry has traditionally operated on a project-based model. Revenue was typically generated through:

• BMS installations

• Controller upgrades

• Graphics development

• Commissioning

• Maintenance contracts

  
  

Once a project was completed and operating correctly, the commercial relationship often became reactive.

FDD introduced a fundamentally different approach. Instead of focusing on installation, the value comes from:

• Continuous commissioning

• Ongoing optimisation

• Subscription-based analytics

• Performance accountability

• Measurable operational outcomes

• 
  

This recurring operational model was not naturally aligned with the way the controls market evolved.

Legacy Platforms Were Not Built for Analytics

Most older BMS architectures were never designed to process and analyse data at enterprise scale. Common limitations included:

• Limited trend storage

• Low-resolution data

• Restricted cloud connectivity

• Proprietary architectures

• Limited APIs

• Poor portfolio-wide visibility

By contrast, specialist FDD platforms were built cloud-first. Solutions such as SkySpark, Clockworks, CopperTree and CIM were designed to:

• Ingest vast quantities of data.

• Normalise information from multiple systems

• Understand equipment relationships

• Execute diagnostic rules continuously.

• Benchmark performance across portfolios

  
  

The infrastructure required for analytics is fundamentally different from the infrastructure required for control.

The Limits of Human-Led Diagnostics

Historically, building optimisation relied heavily on engineering expertise.

The process was straightforward:

1. An engineer attended the site.

2. Trend data was reviewed manually.

3. Faults were identified and resolved.

   
   

This model worked when buildings were simpler. Modern commercial buildings are not. Today's assets can generate:

• Tens of thousands of live data points

• Millions of data changes every day

• Hundreds of interconnected control sequences

  
  

No engineering team, regardless of experience, can continuously monitor this level of complexity manually.

Specialist FDD providers recognised early that automation was the only scalable solution.

The Accountability Challenge

One of the less discussed reasons for the growth of independent FDD platforms is accountability. True diagnostics often reveal issues such as:

• Simultaneous heating and cooling

• Failed valves and dampers

• Sensor drift

• Overridden plant

• Poor control sequencing

• Excessive runtimes

• Broken interlocks

• Commissioning defects

In many cases, the organisation maintaining the control system may also have designed, installed, or commissioned it.

Independent analytics platforms created separation between:

• The controls layer

• The performance verification layer

  
  

For landlords, investors, and asset managers, that independence provides confidence that building performance is being measured objectively.

Buildings Were Slow to Embrace Digital Transformation

Compared with industries such as manufacturing, aviation, telecommunications, and finance, commercial real estate has traditionally been slow to adopt digital technologies. Many building systems remained focused on:

• On-premise servers

• Closed protocols

• Proprietary architectures

• Isolated operational technology networks

  
  

Meanwhile, specialist analytics providers approached buildings through the lens of Industrial IoT and cloud computing.

This difference in mindset accelerated innovation and allowed independent FDD companies to move significantly faster than the traditional controls market.

Changing Expectations from Building Owners

Perhaps the biggest driver of FDD adoption has been changing customer expectations.

Historically, success was often defined simply as:

• The heating works.

• The cooling works.

  
  

Today's asset owners expect far more.

They need:

• ESG reporting

• Carbon reduction strategies

• NABERS and operational performance ratings

• Energy cost optimisation

• Tenant comfort insights

• Predictive maintenance

• Portfolio-wide benchmarking

  
  

Meeting these requirements demands continuous performance analysis, not just control.

The Market Is Now Converging

The distinction between BMS and analytics platforms is becoming less clear. Most major BMS vendors are now investing heavily in:

• Cloud platforms

• AI-driven analytics

• Fault Detection and Diagnostics

• Performance dashboards

• Automated optimisation

• 
  

However, specialist FDD providers continue to maintain an advantage in many areas because they have spent more than a decade refining diagnostic rules, engineering knowledge libraries, and performance workflows.

Their entire business model is built around operational outcomes rather than system control.

The Future: Control and Intelligence Working Together

The industry is increasingly recognising that building performance requires both robust control and intelligent analytics.

A useful analogy is this:

The BMS is the building's nervous system.

It senses, communicates, and controls.

The FDD platform is the brain.

It continuously analyses behaviour, identifies inefficiencies, and drives performance improvement.

Neither can deliver optimum building performance alone. Together, they form the foundation of truly intelligent, high-performing buildings.