Skip the horse and buggy modes of manual reporting, and let us share a few things with you about automated energy reporting. We know, it’s difficult, especially for enterprises still creating pulling data manually. How did we arrive at this juncture? Smart Data Meters, The Decarbonisation Movement, and RPA baby!
Costs involved with a delay in reporting
As energy reporting shifts from voluntary to mandatory, there are hefty penalties for delayed reporting. Official SECR fines have yet to be codified. You can still look to the ESOS, and CRC fines to estimate that late reporting fees will be around £40,000+.
Given the timeframes and fees, there are three modes to consider for submitting your energy reports:
- Manual entry for each building
- Spreadsheet management/uploading
- Optimized RPA software – automatic energy reporting and benchmarking
Manual entry and spreadsheet uploading pose a threat to meeting costly deadlines, mostly because of its time to ensure accurate data and conduct deduplication. The average energy bill has a minimum of one error. Manual investigation of errors on thousands of accounts can tank justifications for scaling staff efforts. Manual entry and poor data created by this process can cost 15% to 25% of company revenue.
Optimized RPA Bill Management and reporting can take just 1 minute to process, analyze, and correct 600 bills, getting those energy reports out on time, every time, avoiding costly penalties.
Cost of lousy energy data
IBM has estimated that decisions based on bad data cost $3.1 trillion per year for the US economy alone. Big data increases the amount of bad data going into a system for analysis, driving us into a new era of “big junk data in, big junk data out.” Feeding a model with bad data will set back benchmarking efforts and cost companies an average of 12% of revenue in off-the-mark decision making.
Scaling energy efficiency measures and staff size becomes futile with the backdrop of large, flawed datasets. Elevating from spreadsheets and batch processing to real-time data validation and deduplication of redundant data removes the risks associated with bad energy data. Using automation for benchmarking and data audits improve lifecycle energy management and reports to a level unmatched by manual data handling.
How energy reporting can be used
Laws mandating energy use and carbon disclosure are coming into full swing, like the SECR in the UK, AU’s NGER, Canada’s GHGRP, and the various city and state reporting mandates across the US. While these laws are meant to drive energy savings, they actually have benefits for companies willing to use that modernization sitting on virtual shelves to improve operational costs, employee satisfaction, and even community standing.
When automating energy data collection with cloud-based platforms, you can use real-time information to increase operational efficiency and a host of other deliverables:
- Increase operational efficiency
- Improve environmental decisions and sustainability initiatives
- Reclaim economic benefits of decision-making based on accurate data
- Utility system benefits
- Improved risk management
- Effective benchmarking
- Scale business objectives through energy efficiency upgrades and rebates
- Get recognition for accomplishments in building efficiency and sustainability
The mid-tier building sector in Australia, which accounts for 80% of office buildings and 50% of floor space, stands to reduce the equivalent of 135,000 cars worth of carbon emissions every year (540,000 tonnes), according to Sustainability Victoria’s Energy Efficient Office Buildings (EEOB). Automated energy reporting can be used to rapidly realize the economic and environmental benefits of this large swath of the sector.
With businesses under pressure to reduce energy use, the efficiencies of an RPA platform can improve issues like tightening the billing lifecycle without human intervention or using data from sensors on wind turbines to develop predictive analytics with AI. This particular strategy allowed for electric and gas utility, Xcel Energy, to deliver savings to their end customers from a reported $60 million in efficiency gains.
At last! Here’s what good data actually looks and feels like
Whether benchmarking your buildings or adhering to energy reporting mandates, reliable data can speed up your processing time and deliver peace of mind when it comes to accuracy. Quality data will provide a fast track for better risk assessment and keep you ahead of your reporting requirements, sustainability efforts, and bottom lines.
Good data supports:
- Singular platform processes for effective procurement, budgets, payment, and energy reporting
- Risk reduction from manual data management
- Better utility bill process
- Real-time access to accurate data for decision-making
- Remote access to accurate energy data for benchmarking and budget revisals
Reporting agencies recommend a digitized Utility Bill Management process, especially for organizations with:
- Manual or semi-manual utility information and bill handling services
- An extensive portfolio of sites to manage and report on
- A need to reduce manual entry and eliminate data errors