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Adding value with energy financial management.

Energy use has grown dramatically over the past 20 years. Commodity prices for electricity and natural gas have risen as suppliers increase their reliance on generation from natural gas and meeting demand becomes more difficult with existing reserves. Markets, suppliers, and rates are becoming more complex for large users--paper mills among them.

Often considered an organization's least controllable expense, energy is responsible for a large and volatile portion of production cost. Energy managers and energy management organizations are focusing on linking three key energy management areas: financial management, operations, and procurement. To improve in these areas, mills should review and analyze energy consumption data, rate details, and billing information. Ideally, this information should be combined and analyzed in a single system. For this article, we will focus on the area of financial management.

Industrial energy managers face slim operating margins, high demand charges, peak vs. non-peak rates, variability in production-related energy costs, and distributed energy assets. Traditional energy management tools and operational control systems cannot meet today's energy challenges and cannot help manage the marginal cost of energy.


Best energy management practices require the ability to link the purchase, usage, and settlement of energy--sometimes across hundreds of facilities--from dozens of suppliers in highly variable and volatile conditions. Often, industrial energy users already have lots of data in their existing systems, but are missing the tools to access, review, and analyze that data quickly and easily to make informed operating decisions.

Many industrial operations greatly underestimate the value of a comprehensive financial management strategy in their energy management plans and practices. Too often, those practices involve process or facility improvements to drive energy efficiency and getting energy bills for commodities such as electric, natural gas, water, and steam processed and paid in a timely manner. With time and mill resources short, additional financial management and analysis activities may be viewed as "nice-to-haves," thereby missing many cost-saving opportunities. Using a comprehensive strategy, industrial energy users can identify and prioritize a much broader range of optimization opportunities. Some examples are described below.

Energy managers must ask specific questions to understand how their mill's energy use is audited against their energy costs:

* how are those costs allocated to various facilities?

* what type of information is required for analyzing energy expense and consumption?

* how are key performance indicators compared within or across facilities?

* what data is evaluated in the budgeting and forecasting process?

* what energy information is needed to accurately forecast use and increase the predictability of future energy expense?

By implementing smart financial management solutions that accurately capture budgeting, accounting, and true cost allocation, energy managers can become highly strategic, purchasing energy at the best possible rate, decreasing costs, and working to improve overall operating margins.


Strategic assessment. Savings opportunities result from an initial assessment of historic utility costs and usage, performed by a professional analyst at the beginning of a project, and updated semi-annually or annually.

Ongoing bill data collection. Captured through an electronic feed from utility suppliers or data entry process by users or an outsource firm, bill data is input into a single, consolidated data repository with usage data.

Bill validation. Utility bills should be checked for potential metering and billing errors. If meter data is available, true shadow billing will recalculate bills and identify variances.

Facility analytics. Various alerts, reports and graphs monitor utility performance and identify savings opportunities. Analyses are updated daily and accessed via the Internet or email.

Accounting and payment. Information from utility bills feeds other financial systems, including accounts payable, accruals, and general ledger. A bill payment service can help reduce late fees and optimize cash management.

Activity-based costing. In-house bill generation, cost allocation, and usage data are assigned to specific departments or cost centers within a mill or organization. Allocations are based on types of activities, such as floor area occupancy, submetered production lines, and hours of operation.

Budget tracking. Intelligent utility budgets are desired from historic data and price forecasts. Near-term budget variances are projected daily, based on defined drivers and early warnings are issued automatically for large variances.


A strategic assessment is a report based on historic utility bill data. It typically includes a standard set of reports, tables, and graphics tailored to customer-specific requirements. This assessment should also have several objectives, such as identifying the following:

* utility price savings opportunities (e.g., right rate analysis)

* competitive procurement opportunities

* fundamental utility spending and usage breakouts (e.g., costs by commodity, service provider, and facility)

* facilities or areas where usage or demand patterns indicated cost savings opportunities

* problem accounts which have incurred high late fees, penalties, billing errors, or other avoidable or recoverable costs.

The following are examples of strategic assessment reports:

* right rate analysis

* procurement eligibility survey

* supplier analysis

* YTD enterprise performance

* demand risk sssessment

* facility benchmarks--price, use, production, weather

* late fee account identification

* historic bill validation


A key requirement for most utility bill-based applications is the timely and accurate collection of data. Bill validation, payment approval and processing, budget tracking, and exception reporting all depend upon two capabilities collecting accurate data as soon as it is available from creditors and capturing sufficient information from utility bills to support energy management requirements.

There are various models for processing utility bills, including in-house data collection and entry, import from a third-party service provider, and transmission of all bills to an outsource data processor.

Tools and services for ongoing data collection are listed below:

A utility accountant bill entry module. This is a customer application for manual bill data entry. It supports simple or complex data capture (few or many line items) and remote or centralized data entry. It also includes checks for common data entry errors such as duplicate or skipped bills, incorrect dates, quantities, subtotals, and fiscal period assignment.

Bill importer. This application maps and imports electronic bill data. It includes checks for duplicate bills, unidentified accounts, and line items.

Late bills alert. This reports accounts when bills have not been received by an expected date and reduces late fees.

Electronic data interface service. This is a content service that maintains bill importer maps for selected electronic interfaces, such as utility EDI-810 formats.


Bill image presentment. This is a customer application that links bill image files to an energy management database, enabling the user to view scanned utility bills on the internet.


Bill validation and reconciliation is the process of identifying potential data entry errors, utility metering errors, bill calculation errors, and suspicious use patterns. Questionable bills are flagged and a report is issued to the user (usually the energy manager) for follow-up investigation. It is always better to know if a utility bill exceeds a threshold demand before it is actually issued.

Bill validation tests can be categorized as checks for potential metering errors and checks for potential cost calculation errors. They can be very simple tests such as checking if electricity usage for an account exceeds some expected maximum, to shadow billing. Because the user defines the test thresholds, exception reports are generated when they are most meaningful to the user.

Shadow billing consists of recalculating a bill using interval data. When a new bill is entered into an efficiently designed enterprise energy management program, a nightly automated process recalculates the bill for the same billing period and compares the results with the actual bill. If the actual and calculated bills vary by more than a specific threshold, then an alert is issued.

In brief, a successful bill validation component (see Figure 1) accomplishes the following:

* Checks for cost, usage, demand and load factor anomalies

* Tailors thresholds for problem for high-spend accounts

* Schedules validation as an automated or on-demand service

* Validates standard or negotiated tariffs with shadow billing


A variety of reports and graphs monitor utility performance and identify savings opportunities. Excel or Crystal Reports can personalize the data even further. Analyses are updated daily and can be accessed via the Internet or email. These analytics fall into three broad categories:

Bill history. This reveals actual usage and cost trends over time, by individual mill or aggregated for the entire enterprise.

Variance. This compares current and previous year usage and cost, or actual vs. base-line cost. It can drill down to variance drivers such as average price, production, etc.

Benchmark. These facility comparisons use indices such as average price, cost per square foot use per square foot, and use per widget or ton.

Always look for an application capable of performing baseline variance analyses that can be used to verify savings with energy management programs. For example, is the facility achieving the expected cost savings from a new cooling system retrofit immediately after adjusting for weather conditions? Choose a company that can create and maintain these baselines as an ongoing service by updating baselines on a quarterly, semiannual, or annual basis.

Facility analytics crosses over readily into the area of operations in the enterprise energy management spectrum. One example is using financial analyses to identify inefficient facilities and analyze interval data--in the form of usage profiles, load duration curves, and statistical metrics--to determine the root causes of that inefficiency. Another example is using utility rate models to determine the costs associated with specific usage patterns. By comparing multiple alternative usage scenarios, a user can determine an optimum operational strategy based on the true marginal cost of energy.


Information from utility bills feed other financial systems. For some applications, this is a simple extraction and translation task. Others benefit more from sophisticated capabilities such as projected bill calculations. Tools and services in support of accounting and payment include the following:

Bill payment approval.

A/P and G/L customized interfaces. These customized applications extract bill data from an energy management program and format it for the paper mill's financial software.


Bill payment service. Look for just-in-time bill payment services for U.S. payees.

Cost accrual. Inaccurate accrual estimations of utility expenses can be a problem. Restating underestimated expenses is particularly painful, both in administrative and financial terms. An effective energy management solution can provide more accurate accrual estimation.


Most industrial organizations have accounting departments that perform cost allocation functions. This usually produces a long delay between receiving bills and apportioning costs. For example, a paper mill may submeter different production lines and use the submeter data to allocate a bill or main meter data. The allocated costs or usage are then reported by activity.

A better solution is to implement an enterprise energy management system that can quickly and accurately allocate costs and usage to specific cost centers. The allocation rules must be flexible so the end-user administrator can maintain them. Above all, a system should provide an allocation immediately upon bill entry or interval data collection. Immediate feedback on energy performance drives end user accountability and reduces usage by influencing production decisions (see Figure 2.)


Paper mills need intelligent energy budget information. Too often software provides a mass of unusable data Intelligent energy budget information, on the other hand, translates to historic data, price forecasts, near-term daily budget variances based upon weather or other production drivers, plus automatic early warnings for larger variances. A solid budget tracking system comprises the following components (see Figure 3):

* A budget development capability based on historic usage patterns and year-ahead rate forecasts

* Periodic (e.g., quarterly) budget adjustment

* Continuous budget performance tracking

* Budget variance analysis.


Paper mill energy consumers must produce valid, accurate information for analyzing, billing, and reporting purposes. They must understand load profiles and energy costs at the plant and enterprise levels, while reducing overall energy costs and improving energy efficiency. After all, operating margins remain tight. To successfully accomplish this objective, industrial energy consumers should implement an enterprise energy management program that fully addresses and provides a comprehensive solution to financial management of energy. The best results in energy management are realized when decisions affecting energy consumption and price are made with solid information and thorough, but efficient business processes.
Bill validation checks Company:
 User:: All Users

Account Number Approve Invoice Date Fiscal Period

1845 Bill 1: [??] 5/26/2003 12:00:00 PM 5-2003

 Test (21) Large change in total cost as compared to
 preceding bill
 Test (30) Meter demand exceeds the maximum for this
 billing account

Account Number Approve Invoice Date Fiscal Period

2116 Bill 1: [??] 5/29/2003 12:00:00 PM 5-2003

 Test (18) Total cost unchanged in successive bills,
 possible inactive account
 Test (20) Usage equals preceding bill, possible estimate

Account Number Approve Invoice Date Fiscal Period

2136 Bill 1: [??] 5/24/2003 12:00:00 PM 5-2003

 Test (27) Total meter usage exceeds the maximum for this
 bill account
 Test (30) Meter demand exceeds the maximum for this
 billing account

Bill validation checks Report date: 6/3/2003 6:47:27 PM
 Start Date:: 5/23/2003
 End Date:: 5/31/2003

Account Number Start Date End Date

1845 4/17/2003 5/19/2003

Account Number Start Date End Date

2116 4/22/2003 5/22/2003

Account Number Start Date End Date

2136 4/17/2003 5/17/2003

Figure 1: Bill validation and reconciliation example.


* Best practices in energy management.

* Why facility managers underestimate the value of energy management.

* The key features of an effective energy management strategy.


* "6-point checklist of best practices in energy management," available as a download via the Itron website. Go to

EDITOR'S NOTE: A related document, "6-point checklist of best practices in energy management," is available as a download via the Itron website. Go to


Tim Berson is a solution consultant for Itron Energy Management Solutions, Alameda, California, USA. Itron Inc. is a global solutions provider and source of knowledge for collecting, analyzing and applying electric, gas and water usage data and has more than 2,000 clients world-wide. Berson has been an industrial technology professional for 16 years. Most recently he has performed solution consulting in enterprise software and energy management, focusing on process optimization. Contact Berson by email at: or by phone at +1 510 263-2612.


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Title Annotation:Energy
Author:Berson, Tim
Publication:Solutions - for People, Processes and Paper
Date:Feb 1, 2004
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