A Call for Embedded Carbon Intelligence

With the onset of ESG disclosure regulation and net-zero pledges, companies are scrambling to account for their carbon footprints. This is a manual exercise, handled by consultants and questionnaires. For example, Ernst & Young is hiring 1,300 consultants for its “Carbon” sustainability practice in the U.K. alone. Many businesses don’t know how to improve their net-zero plans and ensure proper reporting, so they ask consultants for help.  

The questions being asked to consultants include:

• How comprehensive should carbon emissions reporting be? Scope 1 and 2 or Scope 3, too?
• What is the correct scientific methodology for calculating emissions?
• Where can companies find the required data?
• What’s the right industry standard?

As of today, consultants are guiding companies to create their annual carbon disclosure reports and sustainability strategy. Recently, a number of carbon accounting startups have also entered this space, but they, too, are relying on consulting work and manual data entry.

Reporting and strategies don’t equal net zero

While this might be an effective starting point for some companies, there are fundamental issues with this approach:

• Lack of integration: Carbon disclosure reports and decarbonisation strategy are adjacent to core company metrics, objectives, and strategy. Companies that are serious about their net-zero commitments won’t get there by producing a report once a year.
• After the fact: By its very nature, any form of reporting happens after an event or activity takes place. Insights into the event’s carbon intensity have no impact on decarbonization. Sure, it may have an influence on future actions, but how can organisations ensure that good decisions are being made at the time?
• Manual: Operational data must be collected, cleaned, converted (units, currencies), and manually entered into Excel or a carbon accounting software. This is time-consuming, not to mention an error-prone process with little quality assurance happening when data is transcribed.

For the world to cut its emissions by 45% by 2030 and reach net-zero by 2050, annual reports won’t cut it. Achieving sustainability goals will require nothing short of a complete transformation of the global economic system. We need to rethink how emissions data is tracked, analysed, integrated, and used for smarter decision-making.

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The concept of Embedded Carbon Intelligence

Rather than manually tracking and processing carbon data, carbon intelligence needs to be embedded into a given organisation and its processes, including everything from ERP to production management, procurement to transportation, buildings and energy management to employee travel, and more. Embedded Carbon Intelligence alone allows organisations to consider climate metrics at the time of decision-making (and not afterwards) and enable the necessary decisions.

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For integrated carbon intelligence to achieve its potential, existing B2B software solutions need a ‘climate upgrade’. This transformation is already happening with early adopters, and we expect to see most B2B software being climate-aware by default in the near future.

• Your fleet management software no longer just tracks the whereabouts of company vehicles. Now, it reports carbon emissions in real-time too.
• Your procurement software automatically reports on carbon emissions attributed to your purchases, alongside recommending spend-optimisation measures
• Now, your building management software automatically tracks and reports emissions caused by wastewater and energy usage.

Organizations using these solutions can then aggregate this information and, if necessary, use it for reporting. These new metrics can also enable scenario planning and be incorporated into daily decision-making, improving operational management and accelerating the net-zero journey in the process. Audit trails and logs allow you to keep track of how your decisions impact your company’s net-zero path. In turn, you can identify root causes at a granular level.

Leading software providers are bolstering their solutions with valuable additions (and thus increasing the value of the offer, retention, loyalty, etc.). These providers can offer previously impossible services to their clients, namely benchmarking climate performance against their peers, or, even better, improving software so it helps customers reach net-zero. For example, processes can be run when the electricity grid’s carbon intensity is low, low-carbon can be outsourced to vendors, and travel choices can be optimised.

We explored five use cases for Embedded Carbon Intelligence to better illustrate the impacts of this approach:

1. Logistics: Automatic CO2e footprint estimates for all shipments and journeys, no matter the mode of transport or length of travel.
2. Procurement: Automatic mapping of spend-based emission factors to all line items in a PO, even pre-purchase ones, alongside the embedding of carbon metrics in spend-analytics software.
3. Buildings: Monitoring the CO2e footprint of buildings, from construction to usage, including energy, water, waste, and tenant emissions.
4. Predictive processes: Real-time carbon intensity metrics enable the scheduling of process-heavy machine learning algorithms when there is a high representation of renewables in the grid mix, allowing for “green” scheduling of energy-intensive processes.  
5. Internal carbon pricing: Embedded Carbon Intelligence can include internal carbon pricing and offer organisations a dual way to manage the impacts of day-to-day decisions.

Accelerating the green transition with integrated metrics

Embedded Carbon Intelligence isn’t just about reducing manual input and human error for carbon footprinting and reporting.

It is about elevating key climate metrics for better decision-making, allowing the journey towards net-zero to be more accessible.

It is about upgrading existing software solutions and making them climate-aware to meet customer demand for a new set of carbon emission KPIs and reduction strategies.

It’s about accelerating the green transition through data and insights.

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