This analysis provides a geographical view to quickly identify the VEE exception distribution in a specific region. The data is shown for the selected month.

Using this map, business users can identify areas with high VEE exceptions. They can also analyze the nearby areas and look for patterns in the exceptions. The tool looks for differences in geographic regions.

The color-coded region on the map shows the VEE exception count in that area, along with the city and state details.

Drill Down

The City,State link broadcasts the region details to the Exception Types and Exceptions by Month analyses on the same dashboard page.

Source Object

VEE Exception Fact

OAS Subject Area

MDM – VEE Exception

Metrics

Count of Exceptions

This analysis shows the exception distribution based on the exception type for the selected city. The data is based on the postal code selected on the Exceptions map.

Using this tool, business users can analyze the distribution of VEE exception in a geographical area (city) for the selected period. Users can “slice” the data using various view by selections, such as exception type, head end system, device type, device model, etc.

The View By drop-down slices the data by exception type, device type, head end system, service provider, manufacturer, or model.

 

The City,State drop-down filters the data for the area with the respective postal code.

 

The pie chart shows how each attribute of the selected segment are distributed as a percentage of total.

 

% of Total = (Count of Exceptions / Grand Total) * 100

Drill Down

The pie chart drills down to the Exception Trend or Exception Analysis dashboard pages for exception specific details.

Source Object

VEE Exception Fact

OAS Subject Area

MDM – VEE Exception

Metrics

Percentage of total

This analysis shows a 15-month trend in the VEE exception count in a geographical area. It also shows the yearly average. The data is based on the postal code selected on the Exceptions map.

Using this tool, business analysts can monitor exception trends for a specific city and compare the monthly total to the yearly average.

The City,State drop-down filters the data for the area with the respective postal code.

 

The bar graph shows the exception count for each month in the selected geographical area. The X-axis represents the month and year. The Y-axis represents the exceptions. Hover over the bars for specific details.

 

The line on the graph shows the average exception count for the selected year.

Drill Down

The graph drills down to the Exception Trend or Exception Analysis dashboard pages for exception specific details.

Source Object

VEE Exception Fact

OAS Subject Area

MDM – VEE Exception

Metrics

Count of Events (Bar), Yearly Average (Line)

This analysis shows the trend in the number of initial measurements with exceptions across various segments, for the previous 15 months.

Using this analysis, business users can monitor initial measurements, with exceptions, received by the utility. The analysis is an indicator of quality of the data being received from the head end system and possible problems at the service point, such as missing measurements, low usage, spikes, etc,.

 

The monthly graph also has bars to further classify the volume based on device type, head end system, service provider, manufacturer, and model. It helps users understand sub trends within the overall volume of exceptions.

The View By drop-down slices the data by device type, head end system, service provider, manufacturer and model.

 

The stacked bar graph shows the 15-month trend in the total number of initial measurements with exceptions per the selected View By option. Each stack indicates the number of initial measurements with exceptions of a particular type. The X-axis represents the month and year. The Y-axis represents the number of initial measurements with exceptions. Hover over the bars for specific values.

 

Use the slider to view the data for a specific month.

 

The bar graph shows the number of initial measurements with exceptions per each segment selected in the View By drop-down, for the selected month. The X-axis represents the selected segment. The Y-axis represents the number of initial measurements with exceptions.

 

The table displays the number of initial measurements with exceptions, initial measurements with no exceptions, and percentage of measurements with exceptions for the attribute in the selected View By option. The data is shown for previous 15 months.

 

% Initial Measurements with Exceptions = Initial Measurement with Exception/(Initial Measurement with Exception + Initial Measurement with No Exception) *100

Drill Down

The Month column link drills down to the Exception Analysis dashboard page for a granular view.

Source Object

VEE Exception Fact

OAS Subject Area

MDM – VEE Exception

Metrics

Count of Events (Bar), Yearly Average (Line)

This analysis shows the count of VEE exceptions by severity.

Business users can monitor the exception trends by exception severity. This tool shows which VEE exceptions were informational and which were more critical. It can also be used to help defined the exception severity configured in MDM. Perhaps some exceptions should be classified differently – either raising or lowering the severity classification.

The Exception Category, Exception Type, and Exception Severity drop-downs filter the data accordingly.

 

The bar graph shows the exception severity trend for each month, for the previous 15 months. The X-axis represents the month and year. The Y-axis represents the exception count. Hover over the bars for specific details.

 

The table shows the total exceptions and the exceptions against the selected severity for the previous 15 months.

Drill Down

The Month column link drills down to the Exception Analysis dashboard page for a granular view.

Source Object

VEE Exception Fact

OAS Subject Area

MDM – VEE Exception

Metrics

Count of exceptions, Trend compared to previous month

This analysis shows the number of exceptions for a combination of various segments, along with the percentage of total exceptions. The data is displayed for the selected month.

Using this analysis, business users can get a customized view of exceptions. The tool allows users to “slice” the database to perform custom data analysis. The three “View By” selections allow users to define the viewing hierarchy, such as all exceptions of this type, for this type of device and in this city. After the selection, the user is presented a summary of the data. The user can then drill into the details to see the particular device/service points in question.

The View By drop-down slices the details by head end system, device type, service provider, manufacturer, model, customer class, exception type, exception category, exception severity, postal code, or city.

 

The table displays the number of exceptions and percentage of total for each segment selected in the View By drop-down.

 

% of Total = (Exceptions / Grand Total) * 100

Drill Down

The Exceptions column link drills down to the Exception Analysis Detail dashboard page for a granular view.

Source Object

VEE Exception Fact

OAS Subject Area

MDM – VEE Exception

Metrics

Exceptions Count, % of Total

This analysis displays the VEE rules with highest VEE exceptions in the selected month.

This rule shows the VEE rules that have failed the most often and are generated the most exceptions. Users can use this information to look for problems. These problems could be metering issues, revenue protection issues, or MDM configuration issues. Perhaps the VEE tolerances are configured too tightly and the rule is generating false positives. Based on this information, business users may focus on taking corrective measures to reduce the number of exceptions generated.

The table shows VEE rules, their respective VEE groups, and the number of exceptions per each rule.

Drill Down

No drill down

Source Object

VEE Exception Fact

OAS Subject Area

MDM – VEE Exception

Metrics

Exceptions

This analysis shows a comparison of the exception count between the selected dimensional values based on the selected comparison dimension.

This analysis serves as a comparison tool for analysts to view the volume of exceptions for two specific values for any chosen dimensional attribute, such as head end system one versus head end system two.

The Comparison Dimension drop-down slices the data by head end system, device type, service provider, manufacturer, model, or city.

 

The Dimension Value 1 and Dimension Value 2 drop-downs filter the data by the available dimensions in the selected comparison dimension.

 

The bar graph shows the exception count against the selected dimension attributes for the selected month. The X-axis represents the exception category. The Y-axis represents the exception count. Hover over the bars for specific values.

 

The table displays the exception count and the percentage of total for each exception type in the exception categories.

Drill Down

Both Exceptions and % of Total column links drill down to the Exception Analysis Detail dashboard page for more details.

Source Object

VEE Exception Fact

OAS Subject Area

MDM – VEE Exception

Metrics

Count of Exceptions, % of Total

This analysis shows a list of the top 100 devices with the highest number of VEE exceptions in the selected month.

Business analysts can use this detail-level analysis to navigate back to the source Oracle Utilities Meter Data Management system and view specific details pertaining to a service point or device in the 360 Degree View portal.

The table shows the service point and device details, along with the exception count.

Drill Down

The Service Point and Device column links drill back to the 360 Degree View portal in the Oracle Utilities Meter Data Management system.

Source Object

VEE Exception Fact

OAS Subject Area

MDM – VEE Exception

Metrics

Exception Count