ELECTRIC RETAIL PRICES. The Energy Information Administration has released a new report finding that the average retail price of electricity has declined for the third...
between the holding company's subsidiaries. In effect, once the G&A snapshot is taken for the holding company instead of the subsidiaries, this potential source of skew is eliminated.
We performed benchmarking analyses specifically for gas and electric transmission and distribution business units, as well as separate studies for power generation. One of our most recent benchmarking analyses focused on electric distribution operations and maintenance expenditures. It compares the performance of all major U.S. electric utilities based on FERC Form 1 data. For this analysis, we selected 265 data points per utility per year, from the following major FERC schedules:
1. Cash Flow, Balance Sheet & Income Statement
2. Electric Operations & Maintenance Expenses (broken out by business unit)
3. Electric Operating Revenue (including customer base data)
4. Material Supply
5. Number of Electric Department Employees
6. Plant in Service
7. Salary & Wages Distribution
8. Electric Meters and Line Transformers
The methodology has evolved extensively over several years, based on feedback from utility executives. We have found that two basic methods need to be employed, both with the type of multi-year data smoothing (averaging) discussed above:
Method 1: "Ratio" Benchmarking:
For each O&M item (and inventory item) of interest, benchmark to the business unit's related asset-, specific distribution O&M costs are divided by the corresponding distribution asset values to create ratios for comparison purposes.
Method 2: Growth Rate "Self" Benchmarking:
Take the delta between percent annual growth of expenditure versus percent annual growth in related asset; and Compare this delta to the same figure for the other utilities.
Although these two methods generally yield similar relative rankings, Method 2 avoids the introduction of skew in the results when comparing very different utilities-such as a utility in the Northeast with an older infrastructure and higher labor costs versus a younger utility in a region with lower labor rates-because Method 2 compares utilities based upon "self benchmarks": Is your expenditure growing faster than your related asset base, and how does your self-benchmark compare to all of the other utilities?
It is of interest to look at how different utilities' benchmark standings improved after implementation of major software systems. Aside from direct O&M costs, benefits also are evident with regard to inventory levels, salary and wages, and other items.
As one example, our recent study involved distribution-related O&M costs related to transmission and distribution (T&D) for 176 major electric utilities that submitted Form 1 data during the past 10 years. This particular study focused on seven separate benchmarks for these utilities:
1. Distribution-O&M supervision and engineering
2. Distribution-O&M on overhead lines
3. Distribution-O&M on underground lines
4. Distribution-Total salary and wages
5. Total distribution operations expense
6. Total distribution maintenance expense
7. Distribution materials & supplies
Each of the seven O&M expenditure areas was normalized to its related asset. In determining how best to make these calculations, we undertook extensive statistical analysis to ensure that the correlations between the O&M data item and its corresponding benchmark asset were high. In addition, extensive checking of the input data was necessary to avoid introduction of errors (,