Since the passage of the Telecommunications Act (Act) of 1996, the telecommunications environment has been in a state of constant change. The Act deregulated the telecommunications industry and subjected monopolistic Incumbent Local Exchange Carriers (ILECs) to the rigors of a competitive market. This new regulatory environment of mergers, competition, and emerging technologies presents a challenge to regulators.

One of the largest telecommunications mergers to date was between Texas-based SBC Communications and Pacific Bell (Pacific). Pacific Bell is the largest ILEC in California. In an April 1, 1996 letter to Philip Quigley, Chairman and CEO of Pacific Telesis, the chairman and CEO of SBC, Edward Whitaker, promises a bright future for service quality for Pacific Bell customers:

The new regulatory environment opens a need for new methodologies to monitor the activities of existing and emerging telecommunications services providers. This paper introduces the concept of using Geographic Information Systems (GIS) in a new application to assist utility regulatory agencies to strategically monitor the activities of telecommunications services providers during the transition from regulated monopolies to fully competitive status. GIS is an excellent tool for telecommunications analysts as it opens new dimensions in investigative analysis. GIS can potentially be utilized in a number of ways including monitoring telephone service quality, opening competition in local telephone markets, marketing abuse cases, and universal service.

GIS is a powerful tool that combines desktop mapping technology, database, and quantitative analysis to provide a visual representation of data. Any event on the earth can be mapped using any geographic boundaries. Temporal relations between events can be mapped to show changes in data over time.

Because geography is an essential part of an electric, natural gas, telecommunications, or water utility’s service delivery systems, Geographic Information Systems are used by many utilities in a variety of applications (Wirick et al, 1995). The new regulatory environment increases the demand for information systems such as GIS because of a need to save money, safety and regulatory compliance issues, environmental impacts and siting, and open competitive markets.

In addition to mapping and monitoring infrastructure, probably the most important upcoming use for GIS use by utilities is in the competitive arena. In the new competitive market for telecommunications products and services, "customer satisfaction will eventually displace regulation as the main focus in the electric, gas, and local telecommunications industries (NRRI, 1995)."

The same tools that the utilities use to open explore new markets and monitor their networks can be used in a regulatory environment to assess the impacts of numerous issues in telecommunications. Geodemographic analysis can be used to develop end user profiles that are helpful in understanding the relationships between the network, service quality, geography, and ratepayer demographics within a variety of political boundaries. Table 1 illustrates the types of data sets that can be used in geographical telecommunications analysis.

Geodemographic systems are primarily sophisticated marketing tools used to exploit and open new markets which combine databases on consumer characteristics and behavior, census bureau data, other data sources, and GIS to develop profiles of consumer identity that are tied to specific geographic locations (Goss, 1994). Goss states that geodemographics are based on a set of assumptions: 1) social identity is reducible to an aggregation of measurable demographic and psychographic characteristics; 2) these social identities are predictive of behavior especially consumption; and 3) residential location is a determinant of identity and behavior.

This paper applies Geographic Information Systems (GIS) to monitor telephone service quality in California. The service quality study exposed a number of significant infrastructure related problems in specific geographic areas of Pacific Bell’s network. This study revealed inconsistencies between service quality data reported to the Commission, the FCC and actual conditions. There is compelling evidence to suggest that current regulatory policy may contribute to these problems.

Telephone service quality was in a steady decline since the early 1990s. FCC Infrastructure reports show that overall investment in telecommunications infrastructure has declined over the years. ARAMIS data on infrastructure deployment shows a flat line trend while access lines are on the increase.

Pacific’s deployment of both copper and fiber optic wire has remained relatively flat since the early 1990s. Pacific Bell blames regulation on its lack of motivation to invest in its infrastructure. In California, the New Regulatory Framework (NRF) replaced the traditional rate of return regulation where ILECS could expect to recover the costs of network deployment and maintenance through their rates. The NRF created "incentives" for the ILECs to assume more risk in their business. While the NRF has a triennial review process wherein telephone service quality issues are supposed to be considered, service quality has not been a part of these reviews to date. Regulation in the form of price caps, unbundled services pricing, and sharing facilities to new competitors are the reasons for the lack of motivation. Figure 1 shows the amount of physical plant deployed during the 1990s.

Source ARMIS 43-07 1998 and Kraushaar, 1998

GO-133B contains the rules that establish uniform standards of service to be observed in the operation of telephone utilities. GO-133B was first adopted in 1983 and its most recent update was in 1992.

California does not have an objective that companies must meet for trouble reports, but GO-133B does require that companies report to the Commission when their trouble reports exceed 6 per 100 lines averaged out over the entire network. There are no time frames mandated for repairing service outages or other trouble reports. In the case of installations, California does not have a comparable objective that must be met, but companies must report to the Commission when they do not meet at least 95% of their commitments to install by a promised date. ILECS are required to report all held orders to the Commission and the FCC. Held orders are defined in California as primary telephone lines that are not installed within 30 days of the target installation date or date of the order due to a lack of physical plant. Of the 9 SBC states (before the Ameritech merger), only two states including California only designate primary lines for held orders. GO-133-B has no requirements for the installation of additional lines.

Shortly after the SBC/Pacific merger, the California Public Utilities Commission was deluged with in complaints regarding delayed telephone installations and repairs. These complaints received a lot of attention in the media. Pacific Bell dismissed the increase in complaints citing a variety of reasons including storm damage from El Nino and an increased demand for services. Pacific stated that the complaints were not geographically significant and that the numbers of complaints were insignificant compared to the total number of access lines maintained by Pacific Bell (Marshall, 1997). The increase in complaints was not reflected in the service quality reports submitted to the Commission and the Federal Communications Commission (FCC). It became evident that problems with California's telephone service quality existed, but were they not being detected by the standard reporting procedures.

Source ARMIS 43-07, 1998

While deployment was flat, demand for access lines was growing. Emerging local competition, improved technology, growth of home based businesses, and the Internet resulted in an increased demand for advanced telecommunications services. Figure 2 shows the growth of Pacific Bell Access Lines.

In December 1998 the Office of Ratepayer Advocates at the California Public Utilities Commission formed a working group to analyze the service quality complaints received by the Consumer Services Division local exchange carriers (LECs) in California. The complaints would populate a database that would be used to analyze these complaints. The research design utilized GIS analysis techniques to look at this data to answer the following questions:

• Do the complaint letters have geographical significance, or is Pacific Bell correct in their statement that there is none?
• Do the complaints represent service quality conditions in the entire state or are they just isolated incidences?
• Is GIS an effective tool for monitoring telephone service quality?

The research design contains a multi-step approach to answer those questions in addition to discovering what the service quality problems really are in California. The first step involved building a detailed database of consumer complaints from complaint letters sent to the Consumer Services Division of the CPUC. Next, use GIS to analyze the contents of the database to determine the geographic distribution and frequency of service quality problems.

Based on the results of the analysis, develop a survey that will test the database to determine whether or not the complaints are representative of service quality conditions in California. Conduct a random survey both business and residential telephone users, and perform a statistical and GIS analyses of the survey results. The results of the survey would serve as a benchmark to which the complaint database would be compared. Compare the results of the database and survey analysis.

The data used in this database was collected from formal and informal complaints to the California Public Utilities Commission regarding installations and repairs of residential and business telephone lines between the years of 1996 and 1999. These complaints consisted of files containing letters citing problem installations and repairs and their subsequent resolutions. Approximately 1600 complaints currently populate the database. Each of the letters were individually read and coded with the objective of extracting as much information as possible from each complaint including, whenever possible, a count of the number of days the customer was out of service or waiting for their phones to be installed.

The initial analysis of the data included the geographic distribution and frequency of the various categories of complaints. For the purposes of this analysis, the GIS were performed only on the infrastructure-related categories, which include "no facilities", "outside wiring", and "line noise". Delay related categories including missed appointments and days out of service were also mapped.

Zip code became the initial geographic identifier used to make the maps because zip codes were the most frequently used geographic identifier on the complaint letters. The complaints were also mapped by area code, but surprisingly, account numbers (telephone numbers) were not included in all complaints. The GIS was performed using ArcView 3.1.

Is the database an accurate reflection of service quality in California, or are these complaints isolated cases? The next step was to create a survey instrument that could test the complaint database. The survey was developed as a team effort and was designed to be a five minute telephone survey. The survey would act as a benchmark for future analysis of the complaint data. The survey was loosely based on an earlier service quality survey conducted by the California Public Utilities Commission in 1996. However, this survey included a number of questions derived from the database. These questions included the categories that had the highest frequencies of positive responses such as repair and installation delays, number of days, missed appointments, number of telephone lines, line noise, service outage, and reasons for delays such as lack of facilities

The survey was conducted on a representative population which was divided into two groups: business and residential. Approximately 30 people were surveyed from each group in each area code in California making a total of 60 people surveyed per area code. The population was restricted to people with listed telephone numbers. Within these parameters, the sample population(s) were randomly sampled.

The survey was conducted by Quantum Consulting, an independent survey company, between March 1 and March 17, 1999. A total of 782 residential and 777 small business customers were asked a series of questions about telephone quality and their perception of the service they were receiving from their local telephone company. For the purposes of this survey, a small business was defined as a business with less than five telephone lines.

The statistical analysis was performed by Jan Reid, a member of the team, who used a Probit model to test whether or not the problem rates and satisfaction scores can be explained by variables such as geographic location, household income, telephone carrier, length of service, and number of lines (Reid, 1999). Six separate regressions were ran: residential problem rates, residential satisfaction rates, business problem rates, business satisfaction rates, combined problem rates, and combined satisfaction rates. The combined regressions were used to test whether or not business users were less likely to have problems than residential users.

The survey data was mapped by zip code to show the geographic distribution of the survey responses and also by area code. Maps of infrastructure related problems such as line problems and service outages were created to measure the conditions described in the survey. In addition to infrastructure problems, average customer satisfaction, repair and installation delays was mapped by zip code and area code.

Comparing the complaint data and the survey results required both a GIS analysis of the raw survey data and geodemographic techniques to analyze the significant demographic information revealed in the statistical analysis of the survey data. First, the raw survey data was mapped in order to look at the distribution of responses to installation and repair questions. Next, geodemographic techniques were employed to determine how the demgraphic profile of the unsatisfied customer of the survey results compared with the demographic of the complaint database. Making this determination involved a number of steps including: 1) mapping the raw survey data, 2) normalizing demographic data into zip code boundaries, 3) establishing a demographic for the complaint database and comparing it to the demographic established by the survey results.

Reid's analysis found two significant variables within the 0.95 confidence level. These variables are LINES (number of lines per household) and I100 (household income of over $100,000). There is an inverse relationship between number of lines and overall satisfaction and income of over $100,000 and overall satisfaction. Overall satisfaction decreases with increases in the number of telephone lines and increases in income. This geodemographic exercise will only be performed with the income variable. The complaint database has fields for reporting additional telephone lines, but there was no way to determine by the data in the database how many complainants have multiple telephone lines since that information is the result of volunteer reporting. However, we should expect to find the relationship between income and satisfaction in the complaint database. This relationship can be found by applying some of the basic techniques of geodemographics. In this case, 1990 census income data that was projected to current year, 1999, was normalized into zip code boundaries.

Figures 3 and 4 illustrate the process of normalizing data from one type of geographic boundary to another. The first step in the normalization process is performing a "union" of two spatial data files. This is shown in figure 3. In this case census block boundaries were "unioned" with zip code boundaries. From the union of the two files, a third file will be created that has all the boundary lines and attributes assigned to each new polygon.

 Results

Is geography a significant factor in these complaints or are the complaints randomly distributed across the state as Pacific Bell claims? Figure 5 illustrates the geographic distribution of complaint letters received by the California Public Utilities Commission in 1977 and 1998. The complaints are mapped by zip code boundaries. The color of the polygon denotes the number of complaints from the zip code.

Figure 5: Distribution of 1997 and 1998 Complaints by Zip Code

1997 and 1998 were landmark years for complaints regarding telephone service quality at the CPUC. While Pacific provides 78% of the access lines in California, Pacific got the overwhelming majority of the complaints by receiving 98% and 97% of the complaints for 1997 and 1998 respectively. The complaints centered on long delays for repairs and installations of telephone service. The main reasons cited for these problems were infrastructure related (damaged or worn out cable and lack of facilities) which resulted in service outages and line noise and an inability to install telephone service in a timely manner. Table 2 shows the contents of the complaint database by category and frequency of response.

Complaints about delayed and faulty repairs dominated the database in 1997 (53%) and 1998 (57%). Many of these complaints were regarding reoccurring problems that jumped from 27% in 1997 to 44% in 1998.

Table 3 shows the ARMIS reports for 1996 - 1998 show Pacific's reported repair intervals as averaged out through the entire system. The report shows that repair intervals have increased over all three years. Between 1996 and 1998 repair intervals have increased steadily over all 3 years with a 40% increase for initial out of service reports and 23% for all other repairs. A comparison between the survey data, 1997 and 1998 complaint data and the ARMIS repair intervals indicates that repair intervals may be longer in duration than what is reported to the FCC.

Both years show the complaints concentrated in the Bay Area, particularly the Silicon Valley region. The data for Southern California is not complete for the year 1997, and there is no way to estimate the number of missing complaints or make assumptions about the nature of the complaints. 1998 data for Southern California is complete, but because of the problems with the previous years data, it is not possible measure with any certainty an increase or decrease in complaints. Because of this, the analysis will be confined to Northern and Central California.

Complaints to the CPUC reached an all time high in 1997. In 1998, the overall numbers of complaints declined; nevertheless, the reduction of complaints only occurred in certain area codes. Complaints declined in the Bay Area and increased throughout the rest of the state particularly the 916, 530, and 707 area codes. While the total number of complaints reduced in 1998, the number of complaints related to "reoccurring problems", "line noise", and "bandwidth" increased in overall numbers between 1997 and 1998.

The overall decrease in complaints during this period can be attributed in part to the effort of Pacific Bell to recruit and deploy additional service technicians particularly in the South Bay. Nevertheless, while the numbers of complaints decreased, the basic infrastructure related problems remained.

In his analysis of the survey data Reid found that "residential users experienced high problem rates in area codes 408 (17.14%), 510 (14.71%), 707 (20.59%), and 818 (21.21%), and business users experienced high problem rates in area codes 510 (18.18%), 530 (17.65%), 650 (20.59%), 707 (17.65%), 909 (17.65%) and 916 (20.59%). Reids residential problem rate regression revealed 3 variables that achieved 95% confidence level or better: Area code 707 (.95), number of lines (.98), and income of $100,000 (.97). However, within a 90% confidence interval, area codes 530 and 818 are significant at .93 and .94 respectively. The business problem rate regression has no significant variables at a 95% confidence interval. Within a 90% confidence interval area codes 650 (.93) and 916 (.92) are significant. Tables 4.21 And 4.22 show the results of these two regressions (Reid, 1999).

Reid also found a positive relationship between number of lines and problem rates with residential customers and suggested that this might be an indicator of a strained telecommunications infrastructure. The Probit regression found that the number of lines had a significant effect on the problem rates of residential users, but had an insignificant effect on the problem rates of business users (Reid, 1999). This could be due to a number of factors from infrastructure planning to a possible company hierarchical priority between business and residential customers.

The survey conducted in March, 1999 found that line noise and service outages were the most frequently reported telephone service problems. Line noise and service outage complaints and survey responses will be compared spatially and temporally in the next section

The database shows decreases in line noise related complaints in some area codes and an increase in others between 1997 and 1998. The trend shows a decrease line noise problems in the Bay Area’s 408 and 415 area codes. Increases in line noise problems occur in Northern California's 707, 916 and 530 area codes. This trend was first observed in the database and substantiated by the survey.

Complaints of service outages dominated the repair-related problems related to the CPUC and the survey. As with line noise problems, service outages appear to be on the decrease in the Bay Area area codes 408, 415, and 510 while increasing in the 707, 650, 916 and 530 area codes. Again this trend is verified by the survey results which show the highest intensity of service outage problems in the Northern California area codes where complaints are increasing, and a weaker intensity in the area codes where complaints have decreased since 1997.

Installation complaints include the categories "no facilities", "days without service", and missed appointments. Installation related complaints comprised 44% of the total in 1997, and fell in 1998 to 37% of total complaints. The most frequently cited cause of installation delays is a "no facilities" condition. No facilities is where there is a lack of available infrastructure necessary to complete a telephone installation. Usually this is related to using up all available working line pairs in a particular area.

Figure 10 shows the geographic distribution and intensity of no facilities related complaints. While no facilities complaints dominate the South Bay Area in both 1997 and 1998, the number of no facilities complaints increased in the Sacramento region in 1998.

Figure 4.4 No Facilities – 1998

How long were consumers waiting for installations of primary and additional phone lines? Depending on the location and type of service requested, installation delays range from one day to 7 months past the target installation date. In 1997 complaints about installation of primary service comprised 22.3% of total complaints and 22.4 % of total complaints in 1998.The provision of residential primary service is supposed to hold the highest priority for telephone service providers in California. GO-133B requires ILECS to report all primary line installations that were delayed 30 days or longer due to lack of facilities. Table 6 shows Pacific’s reported held orders and the database’s count of held orders for the years 1997 and 1998.

Table 7 shows the average installation intervals reported to the FCC. Figure 11 shows the average installation delays from the complaint database for 1997, 1998 and the 1999 survey. The data suggests possible discrepancies between the average installation interval reported to the FCC and actual conditions.

In Relationaddition to the service problems, the survey revealed that there was an inverse relationship between income and overall satisfaction. The higher the income, the greater the level of dissatisfaction with the telephone services provider. While the nature of the complaint database did not allow the collection of specific demographic information, the use of geodemographic techniques allows us to establish a baseline demographic of income distribution for all California zip codes. Like with the survey, income has a positive relationship with consumer satisfaction.

Figure 12 shows the results of the geodemographic exercise to test the fit between the complaint database and the survey results. Reid found that the variable which represents respondents with household incomes of $100,000 and above to be statistically significant. This variable has a positive relationship between income and overall satisfaction.

The Y axis represents all zip codes the complaint database with the relative frequencies of households with $100,000 or more income. The X axis represents number of complaints per zip code in the complaint database. The assumption is the more complaints in a zip code, the more dissatisfied the residents are with their telephone service provider.

Maintaining a geographical perspective is the foundation of GIS analysis. Keeping that perspective from the planning process, to data collection, and throughout the analysis allows the database to tell a story of telephone service quality conditions in California. The story extracted from the database should answer the following questions.

1. Who is complaining? Who is receiving the most complaints?
2. What are the complaints about? What are the problems?
3. Where are the problems located?
4. When are the problems located?
5. Why are the problems occurring?

Who is complaining? The majority of the complaints in the database came from residential customers. While residential customers dominate the complaints, the survey analysis demonstrated there is no appreciable difference between levels of satisfaction of residential and business customers with their telephone provider or problems with their service. The statistical analysis of the survey also revealed an inverse relationship between income and level of satisfaction. Geodemographic techniques allowed a direct comparison between an income demographic of the complaint database and an income demographic established by statistical analysis of the survey data. Both the complaint database and the statistical analysis of the survey contain this relationship.

Who is receiving the most complaints? That information is easily extracted from the database. The "winner" is Pacific Bell with a whopping 98% of the total complaints for 1997 and 1998.

What are the problems? By possessing geographic data in the form of a zip code, and area code, I was able to find the locations and frequencies of various problems and conditions. The complaint database leans heavily towards infrastructure related problems. Line noise, service outages, and lack of available facilities to complete installation suggests an aging infrastructure experiencing a growth in demand that exceeds expectations and available infrastructure. Additional symptoms of these problems include missed appointments and increasing installation and repair intervals. The intervals increased despite a hiring blitz by Pacific Bell (Zinko, 1998).

ARMIS reports also reveal increases in these intervals. While the increased intervals reported to ARMIS are cause for concern, do they really tell the whole story? Survey results show installation and repair intervals to be longer than ARMIS reported intervals in all but few area codes

Where are the problems located? Were the complaints randomly distributed throughout the state as Pacific Bell claimed? A look at the data reveals that complaints are clustered in certain geographical regions in varying intensities. In 1997 the majority of complaints came from the Silicon Valley Region especially the cities of San Jose, San Francisco, Palo Alto and Sunnyvale. The greater Bay Area came in second for complaints followed up by the Central Valley from Redding in the north to Fresno in the south particularly in the Sacramento and Santa Rosa/Petaluma regions. During 1998 the number of complaints reduced in the Silicon Valley and the Bay Area, but they increased in other areas particularly the Sacramento Region and Northern California. Nevertheless, the Silicon Valley remained the dominant problem area in the complaint database. This trend was confirmed in the statistical and GIS analyses of the survey data.

When are the problems located? By recording the dates of the letters, it is possible to map when the problems occurred (or when the complaints were written) and if there was change over time in respect to an increase or decrease in types of complaints while detecting changes in location. By being able to look temporal change for types and intensities of problems and their locations, the data allows us to see that the complaints were evenly distributed throughout the year and were not lumped into "El Nino" months as Pacific claims.

A properly done statistical analysis of a randomly sampled survey is considered to be, within a certain margin of error or confidence level, a reliable representation of a larger population. This study utilized such a survey and subsequent statistical analysis to act as a benchmark to determine how closely the complaint database resembles telephone service quality conditions in the state of California.

Many of the survey questions were derived from the database. These questions served as markers of the relationship between the database and actual conditions. These questions referred to such conditions as service outages, line noise, repair and installation intervals.

Both the survey results and the database had mutually supportive findings in the 1) geographic distribution of problems, 2) type of problems (line noise and service outages), 3) installation and repair delays and 4) the relationship between income and satisfaction. Based on the agreement of these four points between the survey data and the complaint database, there is sufficient data to suggest a positive relationship between the database and service quality conditions in the state.

The answer to that question is obviously yes. By analyzing the complaint and survey data using GIS a number of unique findings occurred:

• The GIS analysis of the complaint database established that complaints were not randomly distributed across the state. They were clustered and concentrated in specific geographic regions.
• Geodemographic technique helped establish the relationship between income and satisfaction in the complaint database.
• GIS revealed the existence of previously undetected problems because of inadequate reporting and analysis methods.
• GIS helps show the existence of trends in problems and their locations both spatially and temporally.
• GIS helped demonstrate that the complaint database reflects actual telephone service quality conditions in the state.
• GIS revealed possible inconsistencies between reported repair and installation intervals and actual intervals.

One of the most important lessons from this project is that aspects of Federal and State service quality reporting standards are in need of rehabilitation. Two reporting issues arising out of this study are installation and repair interval and geographic reporting standards. Current reporting practices contribute to the misrepresentation of telephone service quality conditions in California. This section will discuss those standards and make recommendations for improvement.

Of primary concern are the inconsistencies between repair and installation intervals between the survey and what’s reported to ARMIS and the CPUC. A comparison of the survey results and the ARMIS reports shows the average installation interval in the survey is 4.78 days and the average repair interval is 2.97 days compared to 2.2 days for installation intervals and 1.9 days for repair intervals as reported to ARMIS. The apparent inconsistencies between the survey-reported intervals and the Pacific Bell reported intervals require further investigation.

A serious discrepancy also occurs upon comparing the primary installation delay intervals (>=30 days) from the database to the reported held orders for GO-133B. There were more complaints about installations with primary service delays of over 30 days than there were reported held orders by Pacific Bell for both 1997 and 1998. The delayed installations occurred throughout the year particularly during the months of June, July, and August. In 1998, Pacific reported no held residential orders for the entire year, while the database contains 9 complaints of primary residential installations delayed 30 days or more past the target installation date.

Further evidence of Pacific Bell's approach to record keeping and reporting regarding held orders, comes from Cox California who states in their comments on the Service Quality Draft Decision.

Nevertheless, no matter how Pacific masks it’s actual installation intervals, many ratepayers are still waiting over 30 days for primary telephone service, and it is not reported to the Commission.

Pacific Bells problematic record keeping and reporting practices are not unique to reporting held residential orders to the commission.

Pacific is currently under scrutiny by the FCC in its record keeping and reporting practices resulting from the FCC’s audit of continuing property records. Not only did Pacific Bell apparently overstate its continuing property by some $499.1 million, but also they were not able to produce the adequate records regarding the costs and locations of central plant facility equipment. An additional $27.7 million in Undetailed Investment brings the total to $526.8 million, which the FCC has requested that Pacific Bell write off their books. The repeated discrepancies in this continuing property record keeping bring the auditors to the following conclusions.

"The inability of the company to demonstrate the existence of such a high percentage of the equipment contained in its records raises significant questions about the valuation of Pacific's plant accounts. At worst, failure to provide sufficient and convincing documentation for the acquisition of the assets in question and for their placement into regulated accounts raises doubts about whether policy makers can rely on these records" (FCC, 1998).

These examples are only a few of numerous similar occurrences. Pacific Bell has established a pattern of record keeping and reporting inconsistencies for service quality and infrastructure reporting that suggest that these inconsistencies may be more than simple oversights and errors.

Another problematic reporting standard at both the state and federal levels is allowing telephone service providers to aggregate data in large geographical areas or system wide data reporting standards, provides opportunities for large carriers to hide potentially serious problems in service quality.

As the data has shown, geographic significance can be associated with certain types and frequencies of problems. It is better to have companies report service outages, repair and installation intervals etc. at the wire center level. This provides the opportunity to examine service quality compliance from a geographic perspective allowing for better analysis.

Additionally, reporting service quality data by wire center allows for additional analysis using geodemographics. Marketing abuses can be detected by determining the demographic for the population serviced by the wire center?

Why doesn’t Pacific Bell provide better service quality to Californians? The answer is painfully simple. They don’t have to provide better service. While the service quality rhetoric bounces back and forth between Pacific Bell and the Commission, little significant action has been taken on either side to improve conditions for California residents and businesses.

"Examination of the service quality of a specific incumbent local exchange carrier (ILEC) has traditionally been done in the context of that company’s general rate case (GRC). For those ILECs under incentive regulation, the service quality review was part of that company’s triennial New Regulatory Framework (NRF) review. However, the issue of investigating service quality was specifically excluded from the ongoing third triennial NRF reviews of Pacific Bell and GTEC. It may also be excluded from consideration in the upcoming NRF reviews for Citizens and Roseville. Therefore, the only active forum in which the service quality provided by NRF ILECs can be examined is this OIR. (ORA, 1999)

As I mentioned previously, there are no standards for installation and repair intervals. There no consequences for Pacific Bell regarding excessively delayed installations or repairs. They only have to report held orders, and there may be so many loopholes and misrepresentations in the counting process that regulators and other analysts can’t get an accurate picture of actual service quality conditions in California

It’s critical that the Commission reopen the service quality dialogue in California. While it may be true that open competition will eventually end service quality problems the data strongly indicates that service quality has further deteriorated since the merger. In addition to improved service quality standards, reporting standards need revision as well. Implementing tighter geographic reporting standards and GIS analysis would help illuminate service quality problems where they exist. Trouble reports, service outages, repair and installation intervals should be reported at the wire center level and not averaged out over the entire system. Actual repair and installation data from Pacific should be scrutinized to determine if Pacific is in fact reporting service quality data accurately.

• A heartfelt thank you to my boss, Michael McNamara, at the Office of Ratepayer Advocates. This thesis would not have happened without his support. Not only did he pay for the data, buy the computer, deal with my crazy schedule, provide support and encouragement, he had the faith "to bet the farm." Thank you.
• My deepest thanks to Robert Waste, my major professor. Thank you for understanding the need for speed without sacrificing quality. Your accessibility and patience are ever so appreciated.
• Thank you Consumer Services Division of the CPUC for your support and encouragement.
• Thank you Jan Reid for your wonderful analysis.
• Thank you Art Stackhouse and everybody at Vestra for all your assistance to this project and ORA.
• There wouldn't be Chapter 3 without Theo.
• And for being there for me all these years, thank you, in no particular order, Jessica, Vicky, Abby, Frankie, and last, but not least, Bob.