The Art of Data Collection: Strategies for Gathering Utility Data Efficiently

It’s often said that knowledge is power, so it is easy to understand why data is the real powerhouse in energy management. The quest for energy efficiency is data-driven – after all, “you can’t manage what you can’t measure.”

Even if the two companies seem similar, they may operate from quite different locations, with varied heating, lighting, and energy efficiency systems. In turn, this can significantly impact their overall energy needs. While the typical business consumes between 15,000 and 25,000 kWh annually, this number and the associated cost may vary greatly depending on the specifics of the company’s energy profile (Bionic, 2023). Changing factors like business hours and staff energy use patterns might also have an impact.

How should companies of all sizes improve data collection of utilities and energy consumption? Let’s find out:

Gauging the Reliability & Completeness of Utility Data

Utility bill data covers monthly consumption, cost, demand, and tariff details. It reveals energy usage patterns, peak demands, and the timing of usage, alongside a breakdown of costs, including usage charges, taxes, ratchet fees, and other utility fees, all detailed on invoices.

The effective management of a utility dataset necessitates a keen awareness of its contents and potential omissions. This assessment encompasses two critical aspects: reliability and completeness.

Factors influencing reliability include measurement tool tolerance, error margins in extrapolating geometries; and, the quality of source material. Variations in as-built data or the credibility of the data provider, who might be accountable for the dataset’s accuracy, can impact reliability as well.

Completeness, however, is shaped by the dataset’s origins, including the who, when, and how of its creation. Often, records may be restricted to certain utilities and overlook surrounding infrastructure. While government records might cover public utilities, private properties can be left uncharted.

Datasets might not reflect utilities installed after they are originally documented, abandoned ones, or those undetected at the recording time. A dataset might accurately pinpoint geospatial locations but lack information about the utilities’ nature or operators.

Steps to Efficient Data Collection of Utilities

1. Define Data Parameters Start by pinpointing your energy data parameters. What data types – electricity, gas, water, or ambient conditions like temperature and humidity – are you targeting? Where is this data emanating from: meters, sensors, or smart devices? Determine your data’s frequency, units, and formats, be it hourly readings in kWh or monthly reports in CSV.

2. Select an Optimal Data Collection Strategy Your collection method should align with your data parameters. While manual readings are straightforward, they are time-intensive and susceptible to errors. Wired or wireless setups offer speed but need regular upkeep. For scalability and convenience, consider cloud solutions, but be prepared to address internet dependency and security concerns.

3. Streamline and Refine Data Ensure the collected data is coherent, comprehensive, and precise. Adhere to a standardized naming convention and eliminate anomalies like duplicates or data gaps. Tools ranging from simple spreadsheets to specialized data refinement software can be pivotal in this phase.

4. Safeguard and Structure Data Safe and easy access to your data is paramount. Decide between local storage, remote servers, or cloud platforms. Ensure data integrity with encryption and backup solutions. For swift data retrieval, employ indexing or visualization tools.

5. Refresh & Backup Periodically Routine monitoring of your data processes is crucial. Adjust and refine as needed. Transfer older data to archives to conserve space without losing historical context.

6. Analyze for Actionable Insights The ultimate goal is to derive actionable insights from your data. Harness various analytical techniques, from predictive analytics to AI-driven insights, to support energy objectives like consumption reduction, efficiency augmentation, or sustainability enhancement.

Some Other Considerations…

1. Prioritize Accuracy:

• • Implement Automated Data Collection: Shift from manual entry to automated systems to minimize human error. Leveraging technology like Verdafero Utility Insights can provide precise and consistent data.
  • Quality Assurance Protocols: Incorporate regular audits and validations to maintain the integrity of your data. Advanced software solutions can continuously monitor data quality, flagging anomalies for review.

2. Ensure Completeness:

• • Comprehensive Data Aggregation: Ensure your system is equipped to capture and store all relevant data points. Implementing an integrated platform that can handle the vast array of data from a typical utility bill is essential.
  • Regular Data Audits: Conduct periodic audits to ensure no data points or entire bills are missing. Utilize software that can cross-verify and fill in gaps by comparing against historical consumption patterns.

3. Maintain Timeliness:

• • Embrace Real-Time Data: Invest in systems that provide real-time or near real-time data. This enables immediate response to consumption patterns, leading to more dynamic and effective energy management.
  • Automated Bill Retrieval: Transition to automated platforms that can retrieve utility bills as soon as they’re generated, eliminating delays inherent in traditional mail systems.

Selecting the Right Partners for Energy Data Management…

Managing utility data in-house might be feasible for organizations with limited geographic spread and few accounts. However, as the scale and complexity of operations grow, partnering with specialized software and service providers becomes beneficial and essential.

• Expertise & Specialization: Look for partners with proven expertise in your industry and the specific challenges you face.
• Advanced Technology Solutions: Choose providers that offer advanced, scalable solutions for data collection, validation, and analysis.
• Customized Service Offerings: Your partner should be able to tailor their services to your specific needs, ensuring you’re not spending time on tasks that could be efficiently outsourced.

For smaller organizations with limited geographic spread, in-house utility data management might be feasible but not the best option. As operations scale and complexity increase, the need for specialized software and service providers becomes more apparent.

Choose partners like Verdafero, with a proven track record in your industry who can provide customized service offerings. Ensuring they can tailor their services to your specific needs means you won’t waste valuable time on tasks that could be efficiently outsourced.

As a holistic solution, Verdafero Utility Insights is deployed in the detection of utility leaks and theft, the identification of opportunities for efficiency improvements, the forecasting of trends, the enhancement of operational profitability, and the preparation of regional and federal emissions reports.