Data Quality Metric Library

The percentage of pavement layer records with a layer date in the reported financial year and a known material and source, recorded width when not full width and thickness between 50mm and 500mm.

Metric Purpose

Data validation check of the pavement layer records added in the reported financial year confirming correct pavement data recorded.

Consequence of Poor Quality Data

This can impact our analysis and investment decision making.

Potential reason(s) for not being at the expected standard unique to this metric

Untrained staff collecting as-built inventory data. Lack of data validation checks as part of adding inventory record to RAMM. The system allows for invalid records to be entered. Lack of data standard on how geotextile/fabric layers are to be recorded.

The percentage of pavement layer records entered to RAMM with a layer date in the reported financial year with a recorded Work Origin.

Metric Purpose

Confirm that pavement renewals are identifiable in RAMM for the reported financial year.

Consequence of Poor Quality Data

This can impact our analysis and investment decision making.

Potential reason(s) for not being at the expected standard unique to this metric

Poor or lack of process for the population of this attribute field.

The percentage of the achieved chipseal resurfacing renewals reported in TIO as-builted in RAMM (in m²) with a work category of 212 for reported financial year.

Metric Purpose

Confirm the financial years chipseal renewals achievement reported in TIO have been recorded, and are identifiable in RAMM.

Consequence of Poor Quality Data

Impact on modelling outputs and forward works programming including analysis, annual achievement reporting and investment decision making.

Poor data will impact the results of the ONRC Cost Efficiency Performance Measures.

Potential reason(s) for not being at the expected standard unique to this metric

Lack of, or poor process and trained personnel for recording correct work category in the carriageway surface table for sealed resurfacing work claimed under work category 212.

Reported achieved quantity from different source than as-builted records in RAMM.

Source data used for reporting achievement is not complete or up to date when needed.

Uncertainty around the work category to assign the surfacing component of the pavement rehabilitation to.

Specific comments on the metric

The metric compares RAMM totals to what is recorded in TIO. An exact match will give a metric result of 100%.

The threshold for minor issues is more than +/- 5% of an exact match i.e. RAMM is less than 95% of TIO or more than 105%.

The threshold for major issues is more than +/- 15% of an exact match i.e. RAMM is less than 85% of TIO or more than 115%.

The percentage of the achieved asphaltic concrete resurfacing renewals reported in TIO as-builted in RAMM (in m²) with a work category of 212 for reported financial year.

Metric Purpose

Confirm the financial years asphalt renewals achievement reported in TIO have been recorded, and are identifiable in RAMM.

Consequence of Poor Quality Data

Impact on modelling outputs and forward works programming including analysis, annual achievement reporting and investment decision making.

Poor data will impact the results of the ONRC Cost Efficiency Performance Measures.

Potential reason(s) for not being at the expected standard unique to this metric

Lack of, or poor process and trained personnel for recording correct work category in the carriageway surface table for sealed resurfacing work claimed under work category 212.

Reported achieved quantity from different source than as-builted records in RAMM.

Source data used for reporting achievement is not complete or up to date when needed.

Uncertainty around the work category to assign the surfacing component of the pavement rehabilitation to.

Specific comments on the metric

The metric compares RAMM totals to what is recorded in TIO. An exact match will give a metric result of 100%.

The threshold for minor issues is more than +/- 5% of an exact match i.e. RAMM is less than 95% of TIO or more than 105%.

The threshold for major issues is more than +/- 15% of an exact match i.e. RAMM is less than 85% of TIO or more than 115%.

The percentage of current top surface records, based on treatment lengths, with a valid chip size (AM>=7, CS<=6, 2nd chip recorded for 2CHIP, RACK, B/S, 3CHIP, CAPE, and COMB), surface function (AC <> "M"), a recorded binder type, and a recorded top surface life (not null).

Metric Purpose

Data validation check of the surface records added in the reported financial year confirming correct surface data recorded.

Consequence of Poor Quality Data

Surface records have no network level expected surface life. This can also impact life cycle analysis and investment decision-making.

Potential reason(s) for not being at the expected standard unique to this metric

Untrained staff collecting as-built inventory data. Lack of data validation checks as part of adding inventory record to RAMM. The system allows for invalid records to be entered.

Specific comments on the metric

There are surface records that will legitimately fail this validation test (i.e. Slurry surfaces). These typically constitute a small proportion of each network and have been considered in setting the grade ranges for this metric.

The proportion of the number of surface records entered to RAMM with a surface date in the reported financial year that have a recorded start and end displacement within the limits of the road as defined in the carriageway table, and have a recorded surface width no greater than 2m wider than the carriageway width.

Metric Purpose

Confirm that the recorded surface inventory records in the financial year align with the network as defined in the carriageway table.

Consequence of Poor Quality Data

Data used to support decision-making processes is potentially inaccurate. The data summarised into the treatment length table will not reflect the network dimensions.

Incorrect reporting of renewal quantity and achieved life feeding ONRC Cost Efficiency 2 & 3 Performance Measures.

Potential reason(s) for not being at the expected standard unique to this metric

Poor QA process around as-built data collection.

Carriageway sectioning not actively managed/maintained.

Terratrip used for measuring start and end displacements not calibrated.

Specific comments on the metric

Not greater than 2m wider than the carriageway width was selected based on the guidance in SHDOM that a change in width of >2m should become a new carriageway section.

The proportion of surface records entered into RAMM with a surface date in the financial year and an original cost recorded where the recorded works category is 212 or 214.

Metric Purpose

Confirm that the original cost is recorded against the surface inventory record for work category 212 and 214 activity in the financial year.

Consequence of Poor Quality Data

Reduced understanding of investment, and effectiveness of investment.

Incorrect reporting of renewal quantity and achieved life feeding ONRC Cost Efficiency 2 & 3 Performance Measures.

Potential reason(s) for not being at the expected standard unique to this metric

Poor or lack of process for the population of this attribute field. Lack of understanding of what costs are to be recorded.

Specific comments on the metric

30 June 2016 was selected as population of this field was requested of the sector from the 2016/17 financial year onwards.

The proportion of surface records entered into RAMM with a surface date in the last financial year and a work origin and category recorded.

Metric Purpose

Confirm that surface records associated with renewal activities can be differentiated from those that are not since the start of the last financial year.

Consequence of Poor Quality Data

Reduced understanding of pavement and surfacing performance through not screening out activity not associated with renewals.

Incorrect reporting of renewal quantity and achieved life feeding the ONRC Cost Efficiency 2 & 3 Performance Measures.

Potential reason(s) for not being at the expected standard unique to this metric

Poor or lack of process for the population of this attribute field. Lack of understanding of how to populate this attribute field in the asset inventory database.

Specific comments on the metric

30 June 2016 was selected as population of this field was requested of the sector from the 2016/17 financial year onwards.

The percentage of the length, based on treatment lengths, where the major top surface is newer than underlying major pavement layer, the recorded pavement layer date is less than 3.5 years old at the end of the reported financial year, and the major pavement layer coverage is >=50% of the treatment length.

Metric Purpose

Confirm that a surface record exists for all pavement layer records added to the database in the last 3.5 years.

Consequence of Poor Quality Data

Impacts on future renewal need analysis, forecasting and programming.

Incorrect reporting of renewal quantity and achieved life feeding the ONRC Cost Efficiency 2 & 3 Performance Measures.

Potential reason(s) for not being at the expected standard unique to this metric

No pavement layer data covering the majority of the treatment length section (i.e. major pavement layer and major surface records are for different portions of the treatment length).

Lack of use of pavement builder for completing inventory record updates in RAMM.

Poor, or lack of, process for managing and maintaining pavement and surfacing asset data.

Specific comments on the metric

The grade ranges make an allowance for treatment lengths which have little pavement layer data and the major pavement layer is associated with a shoulder widening, or similar.

The metric only includes treatment lengths where the major pavement layer coverage is >=50% of the treatment length.

The percentage of the total footpath length entered to RAMM during the three year period to the end of the reported financial year.

Metric Purpose

Confirm that footpath asset data is being maintained as new footpaths are constructed/vested, and others are renewed.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making, understanding of the effectiveness of investment and asset valuations.

Potential reason(s) for not being at the expected standard unique to this metric

Poor, or lack of process for updating the asset inventory table following renewal activity Renewal activity is delivered in quantities less than that identified for capitalisation by internal processes Lack of resources to maintain this dataset in a timely manner.

The percentage of footpath records with a valid recorded length (not null or zero), and width (>0.7m and <20m, and not null), an offset less than 40m (when recorded), surface date >= construction date and condition date (when recorded) >= surface date.

Metric Purpose

Confirm completeness of footpath assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

There will be instances where a footpath width falls outside the allowed range of this test. An allowance in the grade ranges has been made for this. Less than 3 years old has been considered a recent condition date.

The percentage of the total number of footpath records with a known purpose, asset owner, location (start and end displacements and side, or map coordinates), surface material and construction/surface date.

Metric Purpose

Confirm completeness of footpath assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

There will be instances where a footpath width falls outside the allowed range of this test. An allowance in the grade ranges has been made for this. Less than 3 years old has been considered a recent condition date.

The percentage of the total culvert length entered into RAMM during the three year period to the end of the reported financial year.

Metric Purpose

Confirm that culvert asset data is being maintained as new culverts are constructed/vested, and others are renewed.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making, understanding of the effectiveness of investment and asset valuations.

Potential reason(s) for not being at the expected standard unique to this metric

Poor, or lack of process for updating the asset inventory table following renewal activity. Renewal activity is delivered in quantities less than that identified for capitalisation by internal processes. Lack of resources to maintain this dataset in a timely manner.

The percentage of culvert records with a valid recorded length (not null or zero), and diameter/height (>=100mm and <8,000mm, and not null), an offset less than 40m (when recorded), and condition date (when recorded) >= construction date. 

Metric Purpose

Confirm completeness of culvert assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

An allowance has been made in the grade ranges for unknown constructed dates of 'older' assets, and the ease and value of estimating these. Less than 3 years old has been considered a recent condition date.

The percentage of the number of culvert records with a known drainage type, asset owner, location (displacement and side, or map coordinates), material, culvert type (i.e. not "unknown") and construction date.

Metric Purpose

Confirm completeness of culvert assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

An allowance has been made in the grade ranges for unknown constructed dates of 'older' assets, and the ease and value of estimating these.

The percentage of the total surface water channel length entered to RAMM during the three year period to the end of the reported financial year.

Metric Purpose

Confirm that surface water channel asset data is being maintained as new surface water channels are constructed/vested, and others are renewed.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making, understanding of the effectiveness of investment and asset valuations.

Potential reason(s) for not being at the expected standard unique to this metric

Poor, or lack of process for updating the asset inventory table following renewal activity.

Renewal activity is delivered in quantities less than that identified for capitalisation by internal processes.

Lack of resources to maintain this dataset in a timely manner.

The percentage of surface water channel records with a valid recorded length (not null or zero), an offset less than 40m (when recorded) and condition date (when recorded) >= construction date.

Metric Purpose

Confirm completeness of surface water channel assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

Excludes surface water channel types of SWCD, SWCS, and ESWC.

The percentage of the number of surface water channel records with a known channel type, asset owner, location (start and end displacement and side, or map coordinates) and construction date.

Metric Purpose

Confirm completeness of surface water channel assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

Excludes channel types of SWCD, SWCS, and ESWC. 

The number of streetlight lights recorded as replaced in RAMM for the three year period to the end of the reported financial year as a percentage of the total number of lights on the network. Excludes when only lamp and/or gear is replaced.

Metric Purpose

Confirm that streetlight asset data is being maintained as streetlight lights are replaced/renewed.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making, understanding of the effectiveness of investment and asset valuations.

Potential reason(s) for not being at the expected standard unique to this metric

Poor, or lack of process for updating the asset inventory table following activity by the maintenance contractor. Lack of resources for the timely maintenance of this dataset.

Specific comments on the metric

For RCAs that have migrated to AMDS, the metric will filter using the owner of the light. Where a light also has a sub organisation assigned, the light will be included if the owner type of the sub organisation is 'LA'.

For RCAs that have not yet migrated to AMDS, the metric will continue to use the owner of the carriageway section that the pole is located on, as the owner of the light cannot be accurately identified.

The percentage of the number of streetlight pole records located within the extents of the road as defined in the carriageway table and with an offset less than 40m (when recorded) or with a recorded GPS location, and with condition date >= installation date (when recorded).

Metric Purpose

Confirm that streetlight assets are correctly located in relation to how the network is defined by the carriageway table.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making and lack of maintenance response.

Potential reason(s) for not being at the expected standard unique to this metric

Untrained staff collecting as-built inventory data. Lack of data validation checks as part of adding inventory record to RAMM. Displacements recorded using an uncalibrated trip meter.

Specific comments on the metric

GPS location is based on NTZM within the limits of the North, South, Stewart and Chatham Islands. The NZTM location of each pole is not available in AMDS so this check is ignored for RCAs that have migrated to AMDS.

For RCAs that have migrated to AMDS, the metric will filter using the owner of the light. Where a light also has a sub organisation assigned, the light will be included if the owner type of the sub organisation is 'LA'.

For RCAs that have not yet migrated to AMDS, the metric will continue to use the owner of the carriageway section that the pole is located on, as the owner of the light cannot be accurately identified.

The percentage of the number of streetlight light records with a known pole and light owner, known pole make and mounting type, known light make and model, known lamp make and model and pole and light installation dates. (Pole make, light make and light model cannot be checked for AMDS RCAs.) 

Metric Purpose

Confirm that streetlight light asset records are complete with a known pole and light owner, known pole make and mounting type, known light make and model, known lamp make and model and pole and light installation dates.

Pole make, light make and light model are not in the AMDS standard so will not be checked for RCAs that have migrated to AMDS.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making and asset valuation.

Potential reason(s) for not being at the expected standard unique to this metric

Untrained staff collecting as-built inventory data. Lack of data validation checks as part of adding inventory record to RAMM.

The percentage of the total railing length entered in RAMM for the three year period to the end of the reported financial year.

Metric Purpose

Confirm that railing asset data is being maintained as new railings are installed/vested, and others are renewed.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making, understanding of the effectiveness of investment and asset valuations.

Potential reason(s) for not being at the expected standard unique to this metric

Poor, or lack of process for updating the asset inventory table following renewal activity Renewal activity is delivered in quantities less than that identified for capitalisation by internal processes.

Specific comments on the metric

For AMDS, this metric will check the barriers table.

The percentage of railing records with a valid recorded length (not null or zero), an offset less than 40m (when recorded) and condition date (when recorded) >= installation date.

Metric Purpose

Confirm completeness of railing assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

An allowance has been made in the grade ranges for unknown constructed dates of 'older' assets, and the ease and value of estimating these. Less than 3 years old has been considered a recent condition date.

For AMDS, this metric will check the barriers table.

The percentage of the number of railing records with a known railing type, asset owner, location (start and end displacement and side, or map coordinates), material and installation date.

Metric Purpose

Confirm completeness of railing assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

An allowance has been made in the grade ranges for unknown constructed dates of 'older' assets, and the ease and value of estimating these.

For AMDS, this metric will check the barriers table.

The number of signs recorded as replaced in RAMM for the three year period to the end of the reported financial year as a percentage of the total number of signs on the network.

Metric Purpose

Confirm that sign asset data is being maintained as signs are replaced/renewed.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making, understanding of the effectiveness of investment and asset valuations.

Potential reason(s) for not being at the expected standard unique to this metric

Poor, or lack of process for updating the asset inventory table following activity by the maintenance contractor.

The percentage of the number of sign records with recorded owner, class, type, material (background and legend), colour (background and legend), and installation date or recent known condition.

Metric Purpose

Confirm completeness of sign assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making, maintenance needs and asset valuations.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

An allowance has been made in the grade ranges for unknown constructed dates of 'older' assets, and the ease and value of estimating these. Less than 3 years old has been considered a recent condition date.

For RCAs that have migrated to AMDS, the metric will check sign type and class for Traffic Control Device (TCD) signs and will just check type for non-TCD signs. Also none of legend material, legend colour, and background material are in AMDS.

The percentage of the number of sign records located within the extents of the road as defined in the carriageway table and with a location and an offset less than 40m (when recorded) or with a recorded GPS location, a height >=50mm and <=5000mm (when recorded), a width >=100mm and <=5000mm (when recorded), and condition date >= installation date (when recorded).

Metric Purpose

Confirm that sign assets are correctly located in relation to how the network is defined by the carriageway table.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making and lack of maintenance response.

Potential reason(s) for not being at the expected standard unique to this metric

Untrained staff collecting as-built inventory data. Lack of data validation checks as part of adding inventory record to RAMM. Displacements recorded using an uncalibrated trip meter.

Specific comments on the metric

GPS location is based on NTZM within the limits of the North, South, Stewart and Chatham Islands.

The sign height limit is set to 50mm to allow for shorter height signs such as No Exit signs

The percentage of the total retaining wall length entered in RAMM for the five year period to the end of the reported financial year.

Metric Purpose

Confirm that retaining wall asset data is being maintained as new retaining walls are constructed/vested, and others are renewed.

Consequence of Poor Quality Data

Poor data has the potential to impact our investment decision making, understanding of the effectiveness of investment and asset valuations.

Potential reason(s) for not being at the expected standard unique to this metric

Poor, or lack of process for updating the asset inventory table following renewal activity. Renewal activity is delivered in quantities less than that identified for capitalisation by internal processes. Lack of resources to maintain this dataset in a timely manner.

The percentage of retaining wall records with a valid recorded length (not null or zero), average height >=0.3m and <10m, an offset less than 40m (when recorded) and condition date (when recorded) >= construction date.

Metric Purpose

Confirm completeness of retaining wall assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

An allowance has been made in the grade ranges for unknown constructed dates of 'older' assets, and the ease and value of estimating these.

The height limit is set to 10m to try to catch cases where the height has been entered incorrectly eg 1.5 has been entered as 15.

The percentage of the number of retaining wall records with a known type, asset owner, location (start and end displacement and side, or map coordinates), material, and construction date.

Metric Purpose

Confirm completeness of retaining wall assets attribute data is adequate for planning and decision-making purposes.

Consequence of Poor Quality Data

Poor data has the potential to impact our renewal programme development, investment decision making, asset valuations and LoS delivery.

Potential reason(s) for not being at the expected standard unique to this metric

Attribute data not known for 'historic' assets. Poor, or lack of, clarity on what attribute fields are to be collected and maintained for this asset type. Poor, or lack of quality control undertaken on inventory data.

Specific comments on the metric

An allowance has been made in the grade ranges for unknown constructed dates of 'older' assets, and the ease and value of estimating these.