Starting with IT Carbon Data

Do You Need Perfect Data to Start Measuring IT Carbon?

No. 

One of the biggest barriers to measuring the carbon impact of IT is the belief that every asset, supplier and service needs complete, precise emissions data before meaningful work can begin. 

In reality, few organisations start with perfect information. 

Asset records may be incomplete. Supplier data may vary in quality. Information may sit across different systems. Product-level emissions data may be unavailable for some technology. 

Waiting until every gap has been filled can mean waiting indefinitely. 

A better approach is to start with the best available data, understand its limitations and improve the quality of the carbon picture over time. 

Why Is IT Carbon Data So Difficult to Collect? 

Technology estates are complex. 

Even relatively small organisations may use hundreds or thousands of devices, applications, cloud services and technology suppliers. 

Information about them can be spread across: 

• IT asset management systems 

• Configuration management databases 

• Procurement platforms 

• Finance systems 

• Cloud platforms 

• Data centre management tools 

• Supplier records 

• Energy information 

• Spreadsheets 

• Individual teams 

Those systems were not necessarily created with carbon measurement in mind. 

One system might tell you which laptops employees use. Another records when they were purchased. A supplier may provide environmental information separately, while electricity consumption sits somewhere else entirely. 

The first challenge is often not calculating carbon. 

It is bringing together enough information to understand what the organisation actually has and uses. 

What Data Do You Need to Get Started? 

The answer depends on what you are trying to measure. 

For an IT estate, useful starting information might include: 

• Asset type 

• Manufacturer and model 

• Number of devices 

• Purchase or deployment date 

• Location 

• Ownership or user 

• Asset status 

• Energy consumption where available 

• Cloud or infrastructure usage 

• Supplier information 

• Product carbon footprint or environmental data where available 

• Replacement and disposal information 

Not every field needs to be complete before analysis can begin. 

The priority is identifying which information is available, where the most important gaps exist and which improvements would materially change the quality of the carbon calculation. 

What Can You Do When Product-Level Carbon Data Is Missing? 

Detailed manufacturer or supplier data is useful, but it is not always available. 

Where primary data cannot be obtained, organisations may need to use appropriate secondary data, estimates or recognised emissions factors to build an initial picture. 

The important thing is transparency. 

You should understand: 

• Which calculations use primary data 

• Where estimates have been used 

• Which assumptions have been made 

• Where data quality is strongest 

• Where uncertainty is greatest 

• Which gaps should be prioritised for improvement 

An estimate that is clearly understood can still support better decisions than having no visibility at all. 

As more accurate supplier or product information becomes available, calculations can be refined. 

What Is the Difference Between Primary and Secondary Carbon Data? 

Primary data comes directly from the activity, asset or supplier being assessed. 

For example, a manufacturer may provide product-specific lifecycle emissions information for a particular device. 

Secondary data uses external datasets, averages, emissions factors or other representative information where direct data is unavailable. 

Primary data can provide greater specificity, but organisations should not assume that carbon measurement is impossible without it. 

A practical carbon measurement approach may use a combination of data types. 

Over time, organisations can improve the proportion and quality of primary information in the areas that matter most. 

Should You Start With Everything? 

Not necessarily. 

Trying to capture every part of a large digital estate at once can make the project unnecessarily difficult. 

A more manageable approach may be to start with an area where: 

• Reasonable data already exists 

• Carbon impact is likely to be significant 

• The organisation has influence over decisions 

• There is a clear opportunity to reduce cost or emissions 

• Better information would support an upcoming procurement or investment decision 

That might be end-user computing, data centre infrastructure, a particular business unit or another defined part of the technology estate. 

Starting with a manageable scope allows the organisation to test its methodology, understand the data challenges and demonstrate value before expanding. 

How Do You Establish a Starting Point? 

The first measurement does not need to represent the final level of data maturity. 

The aim is to use the best information currently available to establish enough visibility to identify significant emissions, understand where data quality needs improving and begin making informed decisions. 

As better information becomes available, the organisation can refine its calculations and improve confidence in the results. 

The formal process of establishing and using an IT carbon baseline is explored in How Do You Measure the Carbon Footprint of IT? 

How Accurate Does Your Carbon Data Need to Be? 

Accurate enough for the decision you are trying to make. 

Different decisions require different levels of precision. 

A high-level assessment designed to identify carbon hotspots may be able to work with broader estimates. 

A formal disclosure, customer requirement or detailed comparison between technology options may require stronger evidence and greater accuracy. 

This is why data quality should be considered in context. 

Rather than asking “Is our carbon data perfect?”, ask: 

“Is the data good enough to support this particular decision, and do we understand its limitations?” 

That creates a much more practical route to improvement. 

How Do You Improve IT Carbon Data Over Time? 

Once an initial picture exists, the organisation can identify where better information would make the greatest difference. 

That might involve: 

• Improving asset records 

• Connecting information from existing systems 

• Requesting better environmental data from suppliers 

• Introducing sustainability requirements into procurement 

• Capturing product-level data when new equipment is purchased 

• Improving energy or utilisation information 

• Recording asset lifecycle events more consistently 

• Establishing clearer ownership for carbon data 

• Replacing broad estimates with more specific information where it adds value 

This creates a maturity journey. 

The organisation moves from limited visibility towards increasingly accurate and useful carbon information without delaying action until every system and dataset is perfect. 

Why Does Data Quality Matter for Procurement? 

Procurement is one of the points where organisations can improve future carbon data. 

If environmental information is requested when technology is being selected, carbon becomes part of the purchasing decision rather than something sustainability teams have to reconstruct later. 

Organisations can begin asking suppliers: 

• Can you provide product-level emissions information? 

• What lifecycle or environmental data is available? 

• How long is the product expected to remain supported? 

• What repair or refurbishment options exist? 

• What happens at end of life? 

• Can environmental data be supplied in a format we can use? 

Over time, better procurement requirements can improve both the quality of carbon information and the sustainability of the technology being purchased. 

Can Better Carbon Data Help Reduce Costs? 

Yes, because improving carbon visibility often improves visibility of the technology estate itself. 

Bringing asset, utilisation, procurement and carbon information together can expose issues such as: 

• Unused or underused equipment 

• Unnecessary replacement 

• Duplicate assets or services 

• Poor utilisation 

• Inefficient technology 

• Avoidable procurement 

• Assets remaining active when they are no longer required 

These are environmental issues, but they can also be financial ones. 

Better data can therefore support decisions that reduce both emissions and unnecessary technology expenditure. 

The relationship between the two is explored in more detail in Can Reducing IT Carbon Also Reduce Technology Costs? 

How Does Better Data Support Asset Lifecycle Decisions? 

Carbon data becomes particularly useful when it is connected to information about the assets themselves. 

Knowing an asset’s age, condition, utilisation and carbon impact can help organisations make more informed decisions about whether to retain, redeploy, refurbish or replace it. 

Without that context, replacement policies can become arbitrary. 

Equipment may be replaced because it has reached a particular age rather than because replacing it represents the best operational, financial and environmental decision. 

We explore this further in How Can IT Asset Lifecycle Management Reduce Carbon and Waste? 

Where Does COzPro Fit? 

COzPro is designed to help organisations work with the data they have rather than wait for a perfect dataset. 

By bringing IT asset, infrastructure and carbon information together, organisations can establish an initial view of their digital carbon footprint and identify where better data would improve accuracy or decision-making. 

As additional information becomes available, that picture can become more detailed. 

This helps turn carbon measurement into an ongoing management capability rather than a one-off exercise dependent on manually assembling information each time reporting is required. 

Start With What You Know 

Perfect data is an unrealistic starting requirement for most organisations. 

The more useful approach is to establish what information exists, understand where the gaps are and begin with a transparent methodology that can improve over time. 

That gives the organisation something it did not have before: visibility. 

From there, better supplier information, stronger asset data and more connected systems can gradually improve the quality of the carbon picture. 

The important thing is to start. 

Talk to KA2 about turning the IT carbon data you already have into useful insight and improving its quality over time.