Making a case for data maintenance outsourcing

Making a case for data maintenance outsourcing

Jason R. Scarlett
ASI Corporation, 11900 Crownpoint Drive, Suite 100
San Antonio, TX 78233, USA

Business Drivers
For utilities, the very nature, size and complexity of the physical networks they manage makes data maintenance a difficult challenge. Countless changes occur as a result of everyday activities:

Work orders must be posted.
New installations must be added regularly.
Records must reflect changes from periodic repairs and maintenance.
Effects of emergencies, like ice storms, blizzards, and heavy rains, must be recorded.

All of these events create inconsistencies between the database and the real world. This constant state of "data lag" creates problems for people relying on GIS data to do their jobs. Without reliable data, users cannot filly exploit the system. Without user confidence, the new GIS database is no better than the paper maps it replaced.

In addition to the challenge of maintaining the GIS database with the latest changes, the organization must also control costs in order to be competitive in the new utility marketplace. This situation is more aptly referred to as "doing more with less."

Developing a maintenance strategy
Utilities need to develop a strategy for assuring the accuracy and currency of their data. That strategy must be based on three important criteria:

Adopt a sustainable, consistent data maintenance solution.

Assure timely updates.

Assure optimum accuracy.

Outsourcing Benefits
Most utilities try, at least at first, to maintain their data in-house. While some maybe reluctant to relinquish control over a process that so directly affects their operations, many recognize that data maintenance is not a core competency within their operations. Actually it is a distraction that keeps qualified people away from mission critical jobs, and drains away resources. Data maintenance is like housework: it is tedious, time consuming, and it is never finished. With that recognition, many utilities are evaluating their outsourcing options based on a number of quantifiable benefits:

Economy and Efficiency
Instead of paying a fixed cost for a dedicated maintenance staff, utilities that outsource pay only for actual work accomplished. The service provider is dedicated to data conversion, whereas utility data maintainers have a variety of functions, of which data maintenance is only one. In addition, since the service provider has many years of data conversion experience working on a variety of projects, they can offer a number of unique data processing techniques that lead to a more efficient maintenance process.

Predictability
The contracted service offering includes all hardware, software, training, management, and technical support required for the maintenance activities. Since the service provider is responsible for these variable costs, the utility benefits from budgetary stability within the maintenance process.

Currency and Quality
Knowing that data would be accurate and up-to-date would allow utilities to focus on value- -added activities.

Flexibility
The service provider is able to support fluctuations in the maintenance work cycle, providing quicker turnaround time, reducing rework for users, and relieving checkout pressures. The utility can instantly re-engineer the maintenance cycle and keep pace with technological change.

Priority ReenEineering
Through the off-loading of non-core activities, the utility can refocus its resources to activities that provide higher value and return on investment.

Leverage Technology
In order to remain competitive, the service provider must stay abreast of the latest technology advances. The utility can be assured that they will be continually upgraded with the most modern developments in the GIS software industry.

Building an Outsouring Case
Data maintenance must be seen as a sustainable priority. What is the cost of outdated information? In the field it can mean missed repairs, incomplete regular maintenance, costly reworks, and inefficient scheduling and dispatch of field crews. In the office, it can lead to lack of confidence in the database, increased engineering and design costs, and other costly operational errors.

In evaluating the viability of an outsourcing strategy for data maintenance, utilities must consider several criteria. The objective is not just to control costs, but to optimize the use of resources to sustain data maintenance as a priority in an overburdened operational environment.

Identify True Data Maintenance Costs
Upon first review, many utilities encounter a kind of sticker shock, The long-term cost of outsourcing data maintenance may appear prohibitive. Based on traditional approaches to budgets, departments responsible for maintaining GIS data may feel they are better off absorbing those costs into their department and conducting data updates in-house. But the true costs of inhouse data maintenance may not be filly understood. Decision-makers must evaluate their decisions based on more thorough criteria, including:

The fill costs
The efficiency of the process
The optimal use of in-house resources

Components of Costs
Like all corporate activities, data maintenance costs include more than just an hourly labor. They must also include:

Employee benefits - Utilities' benefits may be equal to 30 to 50 percent of basic salaries. Even if the utility hires lower wage or temporary workers for data maintenance activities, their organizational structure adds higher costs to basic wages that cannot be easily avoided. Administration - It is difficult but necessary to calculate the administrative functions that go along with data maintenance activities. Someone has to manage the process and that management requires constant attention.

Equipment - Hardware, software, LAN connections, IT support, and other equipment costs must be calculated into the cost evaluation. Cost of ownership is a major IT issue for all corporations. Estimates run between $2,000 and $5,000 per year to maintain a personal computer within a corporate environment. For the engineering-grade workstations and PCs required to operate the GIS, these costs tend toward the higher side of the estimates. Facilities - Finally, utilities must also consider the costs of office space, energy consumption and other physical support for their data maintenance activities. wile these may be dii%cult to identifi and calculate, the cost of facilities can be important.

When in-house costs are filly accounted, the actual rate may be double, possibly triple, the basic hourly wage. In this light, the fee for outsourcing of data maintenance may prove to be substantially lower than a utility's true in-house cost. Service providers incur much lower real labor costs than utilities, especially when benefits are considered.

Additionally, service providers are able to match staff size to work volume, instead of laying off or carrying unneeded staff. By outsourcing, utilities only pay for the time spent directly on their project. Because the service provider can shift people on and off a project as the volume of work changes, utilities avoid the fixed cost of supporting an internal system that will be underutilized.

Increased Efficiency
By calculating the labor costs in this manner, utilities gain a more complete perspective on the amount and nature of resources they require to perform data maintenance or any other internal activity. But direct cost is not the only consideration when evaluating whether or not to outsource data maintenance. An outsourcing solution generally will provide a better quality service in a shorter amount of time.

This is probably the most difficult point for utilities to accept. However, consider the operational differences between an in-house and outsourced solution. First, a service provider has only one job, one reason to exist: convert and maintain geospatial data. The utility on the other hand, has a very different reason to exist: to create and deliver energy or other services to its customers. Whose resources will be most focused on developing and using the best, most efficient and most accurate data maintenance processes? If the service provider fails to deliver its services with optimum speed and quality, chances are it will go out of business. The service provider is completely focused on providing efficient data services as a matter of survival.

To that end, the service provider will have extensive quality assurance/quality control (QA/QC) procedures in place. It willingly invests in new tools, new technologies and new techniques that increase speed and reliability -- investments the utility would be better served to make in its own core competencies. By virtue of its experience gained on dozens of previous projects, the service provider has developed processes that reduce the time it takes to update records, increase operator accuracy and reduce clean up at the QA stage. Its staff is filly trained and singly focused on accurate, timely data services.

Optimizing Resources
When utilities perform data maintenance activities in-house, resources that must be committed to data maintenance are drained away from other activities. To address this consideration, utilities may give their data maintenance teams multiple duties. When an emergency arises or a project needs additional staff, the utility may divert its data maintenance team to other activities. With its in-house staff reassigned to handle repairs, maintenance and other tasks, data updates get delayed. This redeployment of staff may become more frequent, as new and more pressing situations arise. The backlog grows and the database is soon seriously outdated.

With deregulation, increased competition and changing business priorities, utilities need to deploy their resources more effectively to support their primary business processes. Outsourcing marginal activities frees up valuable resources for more critical jobs.

Approaches
The author has identified five major approaches in performing remote data maintenance services. Depending on the data maintenance situation, any one or a combination of these approaches may be implemented.

Extract and Post Methodology
The first approach, more commonly known as check-out/check-in, involves the copying of a portion of the system database records. Changes are made on the extracted copy, and then the updated copy is sent back to the host database for posting. With this approach, utilities essentially follow the same process used in their initial conversion process. Each sector of their service area is periodically revisited, and the required updates are made. Theoretically, with each pass through a section, there will be fewer and fewer updates.

In practical terms, this traditional maintenance approach is still the most popular, used by more than half of all utilities that have reached the data maintenance stage. However, its limitations motivate many utilities to explore other, more efficient techniques, with the objective of keeping their records current by reducing turnaround.

Remote Terminal Service
The second option involves the use of remote terminal technology. This approach allows realtime backlog and work order posting services directly on the utility's GIS database. Utilizing tools such as CitrixTMWinframeTM (included in Microsoft Windows 2000 (NT 5.0) as "Terminal Server") and a high-speed connection, the service provider makes updates directly to the utility's database.

While this approach may still require areas to be locked for updates, those areas can be broken into smaller sections. Newer systems that enable object-level locking do not have this limitation, allowing updates to be performed in real-time. The live remote approach offers several advantages. It reduces the time that sections of the database are locked out of service -- or eliminates the lockout problem altogether. Updates can be made in a much more timely basis, enabling the utility to work on a database that is continually more current than possible with traditional techniques.

Distributed Replication Technology
Additional options are becoming available as utilities move to object oriented and relationalbased graphics architectures, such as those provided by a standard RDBMS, like Oracle, Informix, or Sybase, and the next-generation GISS. The replication and caching functions of these systems can be used to update records automatically and track changes. Currently, for most utilities, this approach is limited to attribute editing rather than editing of spatial information. As this technology matures, full graphic and attribute updates will be possible on all the major GIS platforms.

With this process, the service provider sets up a duplicate (replicated) system and makes all changes directly into the system in real time. The system's built-in conflict management capabilities assure consistency and database purity before the replicated changes are delivered to the utility's core system.

Outsourcin~ Asset Records Management
The fourth option involves the complete outsourcing of all facility records management. With this approach, the service provider will develop, maintain, and support the GIS databases, providing scheduled digital updates to the utility. The provider will be responsible for all information, as well as the processes required to support all asset records.

Interactive Field Survey
Finally, utilities may require intermittent field verification of data. In this scenario, the service provider sends its teams of trained data collectors out to canvas an area, observe all elements of the physical plant, and input the information directly into digital field units with specially designed input forms (screens) that have an underlying rule table to prevent unwitting errors. The data collectors are able to gather the most current, accurate information possible. When they return at the end of the day, the new data is processed and uploaded into the host system and is ready for immediate use.

This data gathering solution is rapidly growing in popularity. It is fast and accurate. A traditional field survey requires many steps; paper maps are plotted; the field crews goes out to check the physical locations against the map; they note changes or differences on the map or on a separate paper form; and then the paper documents are delivered to a data input group that makes the changes into the system. The process is slow, costly, and has the propensity to introduce new errors into the database.

Interactive field surveys reduce the number of steps by more than half and eliminate virtually all ' possibility of error. In fact, it is so fast and so accurate that many utilities are using an interactive field survey for their initial data conversion efforts. They collect completely new data to populate their GIS without consulting their old paper documents at all.

Conclusion
With the rapid and dramatic changes faced by utilities, maximizing operational efficiency is a primary objective. In a performance-based business model, it can mean the difference between profit and loss. To gain this level of efficiency requires accurate, reliable information about the physical network. Many utilities are looking for data maintenance partners to help keep that information as current and accurate as possible.

By outsourcing data maintenance activities, utilities achieve a level of assurance that their data maintenance requirements will be consistently met and that their internal resources can be directed to the more pressing tasks of serving their customers. In an era where downsizing, deregulation, re-regulation, merger and acquisition, and competition have become the defining themes, the do-it-all-yourself model does not work as well as it once did. Companies must focus on their core competencies, delivering their products and services as efficiently as possible to assure profitability and to keep satisfied customers who now have a choice about from whom to buy.

Data maintenance is one of the first and easiest functions utilities can outsource. Compared to inhouse solutions, they can expect their real costs to decline, and their information accuracy and timeliness to increase. At the same time, they can re-deploy those in-house resources -- people, equipment, space and time -- to mission critical activities that will better benefit their top and bottom lines.