Many companies still rely on manually entered utility data for strategic energy decision making. Such systems are prone to human error and often incomplete and inaccurate.
Energy costs and the related management expenses are a major financial concern for most companies. A significant amount of time and money goes into tracking data, monitoring market changes, validating rates, detecting and resolving billing errors, and developing and analyzing cost and usage exception reports. Utility bill management is tough for organizations juggling multiple invoices from repeatable bills such as gas, electric, water, sewer, waste, communications and logistics, especially in a distributed environment.
Managing utility bill data is a major concern for facility and energy managers. Such data has a major role in setting and tracking budgets, in supporting the reports to stakeholders, and in auditing and verification, and reviewing. Processing hundreds or thousands of paper utility bills and extracting useful data for analysis is a cumbersome process.
Challenges in Utility Data Processing
* Lack of utility data standards has made the automated collection of data from hundreds of utilities (with different formats, tariffs, and taxes) very difficult for multi-facility organizations
* Converting disparate data from different utility providers into a consistent, standardized and useful format is a major challenge
* It is difficult and expensive to deliver data in formats required by energy management, accounting, facilities and procurement systems
* Ensuring data quality requires hundreds of automated audits across the collection, normalization and delivery
All these factors prevent multi-facility organizations from automating the collection of utility data, making them rely on manual data entry. However, this poses many challenges:
* Manual entry of data is prone to human errors and results in the entry of inaccurate data into the database
* Manual data entry is time consuming, causing delays in the availability of data and making old data prevail in the system
* When data is entered manually, usually only important data gets entered, leaving out a significant amount of information
* Data entry clerks lacking domain expertise cannot understand and process hundreds of different utility tariffs, semantics, and tariffs, resulting in unnoticeable errors
A possible solution to address these challenges is to scan and convert utility bills to electronic format or to rely on professional data entry services for accurate and fast entry of data. Data in electronic format allows easy accessibility, improved data accuracy, and ready availability of information. A professional service provider would have the capability to consolidate thousands of bills into one invoice that can be processes and provide automated data feeds to the clients accounting software.