SUSTAINABILITY FOCUS 7

Companies are continuing to set bold decarbonisation goals and, as a result, the global corporate landscape is undergoing a major organisational shift. Carbon is no longer simply a reporting concern, it has now become a core strategic component within an organisation that must be urgently addressed. As more and more net zero pledges are made by companies and demand in how companies approach the goals they set, the challenge lies within data and being able to pull the right insights that show the impact. However, this is seeing a much slower development rate. Several leaders don’t believe that they have the data they need to act now. But why wait for the ‘perfect’ data when there is existing data right in front of you?

Decarbonisation data is being seen in a whole new light thanks to technologies such as Artificial Intelligence (AI) and Machine Learning (ML). Being able to capture real-time data for all suppliers and at every site can often seem like an unachievable task, but leveraging technologies such as AI and ML can mobilise companies to move at the pace needed to achieve net-zero - without needing to draw on comprehensive and granular data at scale.

It's as easy as one, two, three…

1. Use available emissions data to build a high-quality dataset

Most large companies have inefficient and time-intensive processes that enable them to annually disclose their emissions data, sometimes taking up to seven months to calculate for the previous year. In order to pursue decarbonisation goals, many large businesses face a rather overwhelming challenge to acquire the necessary data. Often, these large companies are depending on a patchwork of systems. Where they may have real-time asset data in some locations, in others they may be limited to monthly consumption data from electricity bills. Not only is this process arduous, but the data being analysed is very quickly out of date.

AI and ML are providing organisations with the solution to fill these gaps. Leveraging ML-based algorithms enable companies to analyse more facilities as well as model missing data, allowing them to further develop their decarbonisation strategies. By modelling representative sites that share characteristics such as climate zone and production environment, these tools are able to build a model of missing data that is highly accurate. Digitalising this process can also reveal calculation errors that weren’t previously visible. The trends generated from these models allow them to anticipate change according to a number of variables, for example, a change in equipment efficiency. Organisations will then be able to use this foresight to create forward-looking models that can then inform their strategic decisions.

Whilst many organisations are early in their adoption of these tools, the more they leverage them to model missing data, the better their carbon strategy will become as they continue to overcome the data acquisition barrier.

2. Use the right data to facilitate decarbonisation actions

Better data is needed if organisations want to be successful in meeting their bold decarbonisation goals. However, the same level of data granularity isn’t always necessary. Tailoring the data you need and adopting advanced data techniques can aid in accelerating decision making and reducing costs.

When it comes to data granularity, differing levels are needed according to how advanced the decarbonisation actions are. Where 24/7 carbon-free energy contracts need sophisticated contracting and real-time data, many clean energy supply contracts can often be executed with yearly energy procurement data. Existing operational data can also be used to make sound asset-level decisions, such as heating and lighting. For companies to meet annual emissions reductions milestones, collating monthly plant-level data often suffices to support decision making.

3. Create a single source of truth for the organisation surrounding sustainability

Whilst companies can take measures to tailor their data needs to match decarbonisation goals and integrate the correct analytical techniques, encouraging the organisation to join in deploying their decarbonisation strategy at scale can still prove difficult. Business functions all play a critical role, but finance may be using entirely different data than operations and procurement. Digital tools provide a single source of truth and ultimately result in more inclusive partnerships organisation wide.

The time to act is now

We are at a time where corporate ambition, technology and market pressures have converged. Organisations simply don’t need ‘perfect’, real-time data to be able to make and implement strategic decarbonisation decisions. Leveraging existing data sources through AI and ML, strategising and collaborating are key enablers towards net zero. Ultimately, companies that leverage a data-first strategy towards decarbonisation goals in 2022 will be the ones who truly make an impact.