Sometimes we need to pay attention to the man behind the curtain.
U.S. utilities have a significantly higher portion of personnel involved in advanced analytics jobs than U.S. companies generally, and the top decile for these jobs’ salaries are higher for people in these jobs at utilities, vs. the same jobs at other U.S. industries. These and related results are based on an analysis performed during March 2018 for Utility Analytics Institute, based on the latest-available data from the Bureau of Labor Statistics, and were corroborated by additional analysis of job trend data from two additional independent sources.
Advanced analytics-related job trends in the utility industry are important to a lot of us personally. But they are also worthy of general periodic review as we reflect on how our industry is evolving in its advanced analytics journey.
In Praise of the Proverbial Man Behind the Curtain
The curtain is not necessarily a bad thing. Putting aside the fact that researchers would have a lot less work to do if clean comprehensive and detailed data were fully available about all companies, there is also a point after which transparency is not good. Even though publicly traded companies have to disclose details about their financial and operational performance on a quarterly basis, much of their competitive advantage depends on other information which, properly, remains behind the curtain. And with acquisitions and copy-catting being what they are, it would be difficult for the typical smaller company to grow if it had to step up to the level of disclosure of revenue and operational data required of publicly traded companies, let alone if it had total transparency foisted upon it.
Job Analysis Data Sources
There is a tremendous amount of employment and job trend data worthy of rigorous analysis, available from public sources. Data sources include:
- Job listings and profiles on LinkedIn
- Employment, salary, and productivity statistics from the U.S. Bureau of Labor Statistics (BLS)
- Job title trends from Data.Com Connect by Salesforce.com, Inc.
Savvy researchers have long known that there is something special about job-related information. But when it comes to farming publicly-available employment data sources to gain insights about region- or industry- or technology- specific trends, there are caveats.
On the positive side, since job listings, employee resumes, and LinkedIn profiles must, of necessity, be public facing, they are sometimes good leverage points, data-wise, for special insights to be gained and/or hype to be debunked.
On the negative side, there is a lot of information being re-reported, chasing its own tail. So researchers must inspect the source, age, and accuracy of the data.
The U.S. government’s reporting of employment and productivity data involves drawing an elegant line between full transparency and full disclosure. As a result, even though the IRS and Census Bureau have wide-ranging and highly detailed revenue and employment data on all tax-paying companies, along with earnings and demographic data on all tax-paying individuals in the country, before the U.S. Bureau of Labor Statistics (BLS) reports the annual GDP, their input data is cleansed of data about specific companies and about specific individual taxpayers.
This cleansed Occupational Employment Statistics data from the U.S. Bureau of Labor Statistics (BLS) bundles employment and productivity data by industry and by region. The BLS provides details on 140,400,120 jobs across 289 industries and 250 job titles, including jobs for 547,190 employees at utilities, across the following segments:
- Electric Power Generation, Transmission and Distribution
- Hydroelectric Power Generation
- Fossil Fuel Electric Power Generation
- Nuclear Electric Power Generation
- Solar Electric Power Generation
- Wind Electric Power Generation
- Geothermal Electric Power Generation
- Biomass Electric Power Generation
- Other Electric Power Generation
- Natural Gas Distribution
- Water, Sewage and Other Systems
The comprehensive roster of 250 job titles which the BLS applies across all industries includes the following ten titles which relate most directly to Advanced Analytics. (Detailed definitions of each of the ten job titles are provided in the Appendix.)
- Management Analysts
- Computer Systems Analysts
- Market Research Analysts and Marketing Specialists
- Logisticians
- Information Security Analysts
- Computer Network Architects
- Operations Research Analysts
- Database Administrators
- Software Developers, Systems Software
- Statisticians
Based on taking ratios for employment levels across the above ten jobs versus all jobs, the BLS data shows that utilities employ 80% more people in these job roles than other industries, and generally pay higher salaries to these employees as well, with a strong skewing of higher utility employee salaries at the higher-ranking deciles for these jobs:
| Analysis of Ten Advanced Analytics Job Titles for U.S. Utilities and for All U.S. Industries | |
| Total Utility Employees for these ten job titles | 20,190 |
| Total U.S. employees for these ten job titles | 2,831,420 |
| Utilities Employment for this title as % of total utility employees | 0.36% |
| All industries employment for this title as % of total employees in all industries | 0.20% |
| Employment level ratio of utilities to all industries | 1.8 |
| Utilities Annual mean wage as % of Annual mean wage for this title | 103% |
| Utilities Annual 10th percentile wage as % of average for this title | 121% |
| Utilities Annual 25th percentile wage as % of average for this title | 114% |
| Utilities Annual median wage as % of average for this title | 107% |
| Utilities Annual 75th percentile wage as % of average for this title | 100% |
| Utilities Annual 90th percentile wage as % of average for this title | 95% |
A high level of confirmatory consistency is evident when we disaggregate the above results and look at the details for each of the ten jobs.
Specifically, utility employment is proportionally higher for the first seven of the ten job titles, and, unsurprisingly, the biggest outlier involves a three-fold greater prevalence outside utilities for the job title of Software Developers, System Software.
| BLS–Job titles analyzed | Total Utility Employees for this job title | Total U.S. employees for this job title | Utilities Employment for this title as % of total utility employees. | All industries employment for this title as % of total employees in all industries | Ratio of utilities to all industries |
| Management Analysts | 6,890 | 637,690 | 1.2% | 0.5% | 272% |
| Computer Systems Analysts | 4,660 | 568,960 | 0.8% | 0.4% | 206% |
| Market Research Analysts and Marketing Specialists | 2,300 | 558,630 | 0.4% | 0.4% | 103% |
| Logisticians | 1,840 | 146,060 | 0.3% | 0.1% | 317% |
| Information Security Analysts | 1,130 | 96,870 | 0.2% | 0.1% | 293% |
| Computer Network Architects | 990 | 157,070 | 0.2% | 0.1% | 158% |
| Operations Research Analysts | 890 | 109,150 | 0.2% | 0.1% | 205% |
| Database Administrators | 750 | 113,730 | 0.1% | 0.1% | 166% |
| Software Developers, Systems Software | 700 | 409,820 | 0.1% | 0.3% | 43% |
| Statisticians | 40 | 33,440 | 0.01% | 0.02% | 30% |
| Sum or average | 20,190 | 2,831,420 | 0.4% | 0.2% | 179.3% |
The Appendix shows two tables with actual salary figures for these ten roles, which the percent difference results in the table below summarizes:
| BLS–Job titles analyzed
|
Utilities Annual mean wage(2) as % of Annual mean wage for this title. | Utilities Annual 10th percentile wage(2) as % of average for this title. | Utilities Annual 25th percentile wage(2) as % of average for this title. | Utilities Annual median wage(2) as % of average for this title. | Utilities Annual 75th percentile wage(2) as % of average for this title. | Utilities Annual 90th percentile wage(2) as % of average for this title. |
| Management Analysts | 98% | 121% | 115% | 107% | 96% | 85% |
| Computer Systems Analysts | 106% | 119% | 117% | 111% | 106% | 95% |
| Market Research Analysts and Marketing Specialists | 114% | 126% | 128% | 124% | 114% | 103% |
| Logisticians | 110% | 125% | 119% | 110% | 108% | 105% |
| Information Security Analysts | 92% | 107% | 98% | 91% | 89% | 86% |
| Computer Network Architects | 101% | 120% | 113% | 104% | 99% | 95% |
| Operations Research Analysts | 99% | 123% | 111% | 100% | 93% | 93% |
| Database Administrators | 108% | 122% | 116% | 112% | 106% | 100% |
| Software Developers, Systems Software | 93% | 104% | 102% | 95% | 91% | 87% |
| Statisticians | 109% | 144% | 126% | 113% | 100% | 98% |
| Average | 102.9% | 121.0% | 114.5% | 106.7% | 100.3% | 94.8% |
Corroboration of BLS results from LinkedIn job listings and from Salesforce.com data
Consider that the BLS data shows 2.8 million people overall in those ten job titles, out of 140 million employees (or 2%), while for utilities, it shows 20 thousand people in those roles, out of 547 thousand employees (or 3.6%).
Seven advanced analytics related job titles were used to perform a similar comparison of new job listings as shown below, based on results from LinkedIn. The portion of new listings for utilities were generally proportional (+ / – 20% on average) with the 3.6% figure cited above:
| LinkedIn Keyword for Job Search | LinkedIn Job Search Results as of March 5, 2018 | |||
| All U.S. Industries | Utilities only | Utility as % of Total | ||
| Data Scientist | 13,726 | 35 | 0.25% | |
| Data Analyst | 26,501 | 132 | 0.50% | |
| Data Analysis | 131,926 | 985 | 0.75% | |
| Data Analytics | 63,267 | 215 | 0.34% | |
| Business Analytics | 47,300 | 181 | 0.38% | |
| Big Data | 30,966 | 76 | 0.25% | |
| Statistical | 59,124 | 349 | 0.59% | |
| 372,810 | 1,973 | 0.53% | ||
A corroborative study of Salesforce.com Inc. results from the company’s Data.Connect.Com portal was also conducted, which we will report on in more detail in a later article in this series. The initial results, along lines simliiar to the 80% figure derived previously from BLS data, indicate there are 85% more jobs at utilities involving big data and data science, than in U.S. industries on average:
| Total | Analytics related | Analytics related % | |
| US–All companies | 16,316,507 | 22,101 | 0.14% |
| US–Utilities | 120,256 | 301 | 0.25% |
In addition, per the table below, the Salesforce Data.Com.Connect data indicates that the age of these jobs at utilities is running in parallel, or a bit ahead, of overall hiring practices in industries in the U.S. overall:
| Year Job was Filled | Number of these jobs at utilities | Percent of all such jobs at utilities | Number of these jobs at all industries | Percent of all such jobs at all U.S. industries |
| 2010 | 4 | 1% | 121 | 1% |
| 2011 | 2 | 1% | 246 | 1% |
| 2012 | 9 | 3% | 539 | 2% |
| 2013 | 33 | 11% | 2,637 | 12% |
| 2014 | 43 | 14% | 2,876 | 13% |
| 2015 | 56 | 19% | 2,160 | 10% |
| 2016 | 63 | 21% | 5,244 | 24% |
| 2017 | 65 | 22% | 6,710 | 30% |
| 2018 | 25 | 8% | 1,568 | 7% |
| Total | 300 | 100% | 22,101 | 100% |
Taking the cumulative percentage figures from the Salesforce data shows that utilities arrived at their current (higher) percentage of advanced analytics jobs with proportionally more such jobs being added in the 2014 to 2016 time frame, versus all industries generally.
Corroboration of BLS Results from BEA
“Very well and good then,” you may say, “but how do you factor into these results potential differences which may be elevating utility salaries, or variations due to other lower-paying utility jobs making these advanced analytics jobs seem unnaturally more lucrative than they’d otherwise seem?”
The U.S. Bureau of Economic Analysis (BEA) provides some answers, regarding salaries.
BEA salary data helps us answer an important question about our tentative BLS findings: Is the higher pay and higher employment level for these advanced analytics jobs at utilities vs. other industries reflective of a general salary difference at utilities? The answer from the BEA data below is a resounding “No,” as it shows utilities have stayed 0.83% of total U.S. employee compensation for 18 years running, within a standard deviation of just 3%.
Conclusion and Look-Ahead
The ability of utilities to leverage the latest advanced analytics tools has been increasing significantly. The most valuable benchmarks are often internal benchmarks within a single utility, or within a small peer group of utilities in similar situations.
Such utility-specific views are of value in addressing specific areas, rather than the broad benchmarks outlined here, because so much depends upon the specific value propositions, datasets, and/or analytics domains and related technologies involved. But while we do not seek to gloss over significant variations when it comes to each utility’s situation, it is of value to see our industry is not “behind” U.S. industries in general.
On the other hand, we look ahead to the next article in this series showing industry-by-industry variations when it comes to these advanced analytics jobs, as well as some more specific advanced analytics job trends across U.S. utilities as a whole.
