An evidence-based approach to energy management
In Great Expectations, Charles Dickens warns his readers that there is no better rule than to “take nothing on its looks; take everything on evidence.” This advice also applies to energy management, particularly in the current economic context.
The combined realities of the energy crisis and the push to net zero mean that many businesses might have already implemented a plan to measure and reduce their energy consumption. Organisations are also in the process of monitoring and limiting their carbon emissions to comply with ever-stricter environmental regulations.
However, all strategies are of limited use unless they are based on data we can trust. Decision-making based on inaccurate, incomplete or obsolete data, or even worse on intuition and gut feeling, can be counterproductive and damage a business’ bottom line.
No margin for error
Research by the Federation of Small Businesses shows that the energy bills of the average small business have reached over £28,000, over four times the average in February 2021. To keep afloat and maintain a competitive edge, it is imperative that businesses take action. However, it is impossible to plan without a crystal-clear picture of the present. And in the current climate, spend confidence is a business imperative.
This is where automated data management can help. Manual data collection and analysis carries an intrinsic margin of error – gathering data from multiple sources, in multiple formats, and making it available to multiple departments can inevitably lead to inconsistencies. For businesses with operations in several locations and sites, the risk is multiplied.
Accurate, automated data management removes this error margin and helps business managers understand how much energy is used for operations, how this energy is distributed, the peak usage times, tariffs in place at the time of use, and more.
Another problem arises from obsolete data. The highly dynamic nature of energy data and the many variables to consider in energy management mean that it is not possible to base decisions on outdated information. Automated data collection, measurement and management gives access to near real-time information, which is crucial to put together a credible plan for energy management.
A helping hand for carbon reporting
Accurate data is not only essential to support energy saving plans – it is also necessary for carbon reporting purposes. Historically, a lack of standardised data requirements has allowed some businesses to inflate their sustainability claims, despite weak evidence.
Today, regulatory bodies are pushing for stricter requirements, but research from the Boston Consulting Group found that only 9% of companies are confident when measuring their data emissions. Failure to provide accurate data is not only unethical, but it can also lead to serious financial consequences.
Fines for incorrect emissions reporting, even if unintentional, are a possibility. Moreover, investors are less inclined to work with companies that don’t demonstrate a clear commitment to Environmental and Social Governance (ESG).
In fact, research from PricewaterhouseCoopers found that 50% of investors would be willing to divest from companies that are not taking sufficient action on ESG. Finally, inaccurate emissions reporting, if discovered, could lead to a PR crisis that could seriously compromise the credibility of a business.
In the context of an energy crisis and tense economic climate, organisations have renewed impetus to validate energy spend and avoid unnecessary costs. Accurate, automated data management can drastically simplify emissions reporting and allow companies to achieve transparency in this crucial area.
From complexity to clarity in four steps
The benefits of taking an evidence-based approach to energy are clear, but how can organisations get started? There are four essential steps to data integrity.
The first is to eliminate manual data collection and rely on intelligent software to simplify this operation. By creating a single collection point, this type of software can pool data together and collate it into easy-to-grasp reports that can be used for decision-making.
It’s also essential to scan data for errors and inconsistencies. At this stage, many organisations rely on spot checks, however energy management software has advanced and can validate 100% of a business’ energy data in near-real time, as well as alerting managers to issues, such as missing charges or duplicate bills.
Once these processes are in place, it’s possible to measure and analyse data to optimise consumption. With all data in one source, validated and clearly presented, businesses have all they need to pinpoint the source and root-cause of energy waste, and to improve operations accordingly.
Finally, organisations can consider scaling up this approach across their entire energy portfolio, using all-inclusive software that automates energy data management at all levels, from procurement to payment.
Current energy market conditions call for organisations to carefully rethink their approach to energy management, and to implement solutions that leverage the power of data to stay ahead of the competition. Remember Dickens’ advice and “take everything on evidence” – your bottom line will thank you.
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