CASE STUDY

The Challenge

For this project, the JV was supporting work to identify and reduce pollution across a waterway network, where ageing wastewater infrastructure was allowing leakage into the water environment.

To understand the condition of the network, an asset inspection firm carried out CCTV surveys using crawler cameras, documenting cracks, holes, breaks and other defects within the pipes. The resulting inspection data was shared with the client in GIS format, giving the project team a spatial view of pipe condition and remedial work requirements.

However, as more survey data was collected, inconsistencies in the GIS records began to create issues. Large volumes of pipe condition data needed to be reviewed, checked, summarised and reported each week, but duplicated network sections and inconsistent data quality made it difficult to maintain a clear view of progress.

The solution

Each week, the JV compiled all available data into a report, made up of multiple plans of the geographic area and maps of the pipeline network, highlighting sections that had been surveyed and those still outstanding. With inconsistencies in the data, and even whole sections of the network duplicated, MGISS was appointed to pinpoint the issues in data collection and processing, and to ease these complexities.

MGISS supported the JV by speeding up the production of these reports. Rather than manually sifting through data, we identified that automating the collation and management of data could bring greater efficiencies to the project.

We provided access to a data quality improvement toolbox for ArcGIS Pro, enabling the JV to inspect all records, count the number of completed sewers, log meterage and any critical defects, and generate a report. This was then translated into graphs highlighting week-by-week progress, giving the JV and its client complete visibility over critically damaged sewers in need of remedial work.

Alongside this, we also provided a data enrichment tool that added a further layer of visibility to the client’s data records. The tool logged all sewers requiring remedial work, along with geographic location, materials, inspection information, and a link to the associated CCTV footage, allowing the team to quickly click through to view the defects within each section of pipeline.

Both geospatial data tools improved data flow between systems and enabled the client to maintain complete visibility over the project’s progress, integrating all available data into a centralised platform that could be accessed remotely.

The result

Before working with MGISS, summarising the meterage of the surveyed sewer network took the client a full day to generate manually, a process that was time-consuming and left room for human error. With the toolkit, the client can now produce these plans in around an hour, a 15% productivity gain.

The data enrichment tool has also delivered considerable time savings. Previously, reviewing new CCTV footage and logging defects and remedial work required took a full day; this can now be completed in less than an hour.

Through implementation of the toolkit, MGISS has brought greater efficiency and accuracy to the JV’s collection and management of data, providing complete visibility over project progress and the remedial work needed to eliminate pollution from the water network.

Across both tools and the training provided, the data quality improvement solutions MGISS has developed have generated an overall time saving of 40%, reduced the need for long-winded manual data processing, and ensured greater consistency of data.

A project stakeholder commented: “MGISS added significant accuracy, clarity, and value to the project. They listened from the start and, following the initial requirements consultancy, were able to deliver efficiencies, consistency and insight to the project and client team.”

An MGISS Professional Services Consultant commented: “Having worked with the team to deliver a number of data-capture solutions, we were able to quickly engage with them on this project to build accuracy and insight into the large volume of data being processed. Our partnership continues to develop, and we look forward to supporting the completion of this project.”