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CHIPS Articles: Converting Data into Information for Improved Customer Support at the Surface Combat Systems Center

Converting Data into Information for Improved Customer Support at the Surface Combat Systems Center
By Steven Krumm - April-June 2006
The terms “data” and “information” are often used interchangeably. However, information is actually processed data used for enhanced decision making. Data analysts at Surface Combat Systems Center (SCSC), Wallops Island, Va., collect data from scheduling software and convert it into information that managers at multiple levels of the organization use to make decisions that result in improved customer service.

SCSC provides high-fidelity Aegis and Ship Self-Defense System (SSDS) combat systems in a maritime environment in support of Navy surface combatants. SCSC provides a service: use of our combat systems for testing. Customers conduct their combat system testing and training events on our combat systems in the ship configuration they specify.

SCSC customers schedule their events using an Oracle-based application called, “Scheduling Activity Module” or SAM. SAM enables customers to create a scheduling request for a date, time and combat system configuration for 500 available equipment sets. SAM produces a weekly schedule, and customers conduct their events, which are set up and supported by the SCSC staff.

Providing a service is different than producing a product, something tangible that customers take away with them. Quality is defined by the customer rather than a product’s conformity to specifications that could be sampled by quality assurance methods.

At the conclusion of their events, customers evaluate the quality of the service they received using an online questionnaire in SAM. Questions asked are below.

Amount of lost time? [in Hours]
Event Objectives accomplished? [None, Some, Most, All]
Was the system ready on time? [Yes, No]
Was the system configured as you requested? [Yes, No]
Was the system operational for the event’s scheduled duration? [ Yes, No]
Did you have SCSC equipment problems? [Yes, No]
Did you have SCSC software problems? [Yes, No]
Did you have customer software problems? [Yes, No]
Did you have any other problems (weather, power, etc.)? [Yes, No]

Based on the customer’s response, SAM calculates a summary site grade (1-5, with 1 being the best) for the event. All data pertaining to the event (description, configuration, date, times, customer evaluation, etc.) are kept in the database for later analysis.

Two basic types of SAM data analysis are performed: customer satisfaction and demand (utilization and forecasting). Producing information about customer satisfaction is the primary focus of SAM data analysis. Daily event reports are produced, and problems with customer events from the previous day are discussed during a morning staff meeting.

Tabular results are included in a weekly departmental situation report, so managers can compare the current week’s performance with the 12-month average for corrective action, if necessary. Monthly bar charts show customer lost time and readiness metrics by week. Lost time is the number of hours that were scheduled for a customer event, but not available to the customer due to a problem.

One example for improving customer service was the formation of a team, which included all stakeholders, to reduce the number of customer events that were not ready on time and not configured as requested. The team developed setup procedures and interface configuration checklists, which are now used by the SCSC staff during event setup and turnover of the lab to the customer.

A service-oriented Statistical Process Control chart (p Chart), see Figure 1, is also produced. The chart shows the percentage of defective customer events. Event defects are grouped into seven categories: SCSC equipment, personnel requested were not available, etor process improvement to help determine if the root causes of customer event defects are common causes (inherent problems in the process such as procedures or training) or special causes (random problems such as the illness of a key staff member).

The second type of analysis performed is customer demand (utilization and forecasting). Knowing the quantity of products produced or service provided is important for a number of reasons: scheduling, staffing, maintenance, etc.

Basic site utilization is tracked by system hours, which are the total number of hours combat system equipment is used for any purpose.

System hours are comprised of customer events, set up by SCSC staff, installation and testing of new combat system equipment, and both preventive and corrective maintenance. Customer hours, a subset of system hours, are the number of hours that SCSC customers use the combat system to accomplish their mission objectives. These are the actual hours of service provided (billable hours in a for-profit organization or units produced in a production organization).

The difference between system and customer hours can be thought of as overhead hours. Reduction of overhead hours, for example, may be a good cost-saving opportunity in the future, but you can’t compare results if you don’t collect the data now.

Forecasting is accomplished using historical data from SAM. Both SCSC customer and system hours exhibit “seasonality” over a 12-month period. Think of customer demand for snow shovels, and you understand the concept of seasonality. SCSC customer and systems hours also exhibit a trend. Trend is increasing or decreasing customer demand over a period. To model both seasonality and trend, Winter’s Model was selected.

Winter’s Model is an exponentially smoothed, adaptive model used to forecast monthly system or customer hours, up to 12 months in advance. Separate charts are produced for the SCSC Aegis and SSDS facilities since their customer bases are different.

Figure 2 shows fiscal year 2005 actual and forecast customer monthly hours at the SCSC Aegis Complex. The blue solid line indicates the number of hours actually used by customers and the red dashed line is the Winter’s Model forecast.

The seasonality of SCSC customer demand is clearly seen in this chart. Organizations that produce non-perishable products can meet seasonal customer demand by producing more during non-peak periods. However, that is not an option for organizations that provide services. They must either attempt to regulate customer demand or have sufficient surge capacity to meet peak customer demand.

Although SAM data are contained in a database on the local area network (LAN), analysts must extract and process the data to perform calculations to produce charts and report results. This is a labor-intensive activity that produces static results. SCSC is currently implementing a command dashboard to automate the display of information.

Each department will have an area to deposit its data, and the dashboard software will produce graphs to allow analysts and managers to view and drill-down to information online in near real-time. The dashboard software also enables information to be aggregated and displayed in different ways such as using color gauges to help data-overloaded managers to quickly understand the importance of what they are seeing.

SCSC is transforming data into information to improve customer support to realize our vision, “Our oceanfront warfare systems operate together as a premier proving ground to support the fielding and sustaining of improved warfighting capabilities.”

The Surface Combat Systems Center, Wallops Island, Va., provides a maritime test environment, an operational team, and combat systems of high fidelity to conduct realistic test events in support of lifetime support engineering activities and the upgrade of tactical computer programs. SCSC provides key services for performing systems developmental and operational tests, and for research, development, test and evaluation of potential upgrades in all areas of detection, control and engagement.

For more information go to the Surface Combat Systems Center Web site at http://www.scsc.navy.mil/.

Figure 1 shows the September FY05 Aegis Event Defect Control Chart.  The 12-month average defect rate was 10.7% and the rate for September was 8.7%.  The 12-month average process variability was 12.4% and the rate for September was 11.0%.
Figure 1. September FY05 Aegis Event Defect Control Chart.

Figure 2 shows the AEGIS Complex FY05 Actual/Forecast Customer Hours.  From May 2005 to September 2005, the actual customer hours exceeded the forecast.  September 2005 actual customer hours reached about 1,000.
Figure 2. AEGIS Complex FY05 Actual/Forecast Customer Hours.
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