Redefining RFT Field Operations Through Visual Automation – Opportunities for Full Fiber Network Providers

The race is on for FTTP operators to complete their network deployments, whilst juggling the challenges of build contractor shortages, network overbuild, rising cost bases, and most recently, consolidation, as market dynamics and insufficient scale prove unsustainable for some players.

Challenges arise as network deployments are often plagued with quality issues, leading to roll-out delays, additional costs, and customer dissatisfaction. Delays in roll-out, particularly in areas of overbuild, also create a missed opportunity to capture demand.

Once the network is deemed ready for service (RFS), there is also an ever-increasing focus on delivering the best possible installation journey, not just to differentiate, but to better manage the cost base, accelerate time to revenue, and ensure great Net Promoter Score (NPS) feedback when engaging with customers.

The relevance of RFT

Right First Time (RFT) operations have become the key metric of choice in helping operators address these challenges. It measures whether tasks are correctly completed to the required standard in the initial attempt, without the need for rework. RFT is a crucial metric for operators.

Whether at the stage of completing the network build prior to becoming Ready for Service (RFS), when installing a new customer, or resolving network faults, RFT reduces revisits, operational costs, and time spent on each task.  Achieving RFT also paves the way for an improved customer experience, with less disruption during the build phase and higher NPS feedback when the install or repair is completed in a single engineer visit.

The benefits of computer vision to Right First Time operations

In the highly competitive landscape of FTTP, computer vision solutions help operators significantly increase RFT rates through the immediate detection of anomalies and poor-quality operations, enabled by the automated analysis of visual data captured and uploaded by engineers or auditors in the field. The technology can be used to ensure quality compliance across end-to-end full fiber networks from the fiber exchange to the premise, covering both active and passive network equipment.

Potential use cases include verifying compliance against pre-defined quality standards through to detecting network anomalies or issues across an end-to-end full-fiber network, from equipment in the fiber exchange to cabinets and chambers housing primary and secondary nodes, to splice boxes and optical sockets at the customer premise.

Some specific use case examples are outlined below.

• Shared Infrastructure Access – many FTTP providers are reliant on access to third-party ducts, poles, and chambers to deliver and build out their own networks. In a shared infrastructure model, adherence to strict quality standards and compliance with photographic evidence is mandatory, such as Openreach PIA in the UK, NBN Co in Australia, or ONX in Canada. RFT is essential as non-compliant photos or sub-standard work can lead to delays and unnecessary costs due to resubmissions or additional engineer visits.
• Pre-RFS Quality Control – build quality is often compromised as networks are rapidly deployed. Computer vision can be used to ensure build standards are met prior to network sign-off, avoiding delays in handover and accelerating RFS network availability. Relevant for equipment across an end-to-end fiber network, automating real-time quality checks via AI significantly reduces rework, as well as the time, effort, and costs needed to complete desktop and site surveys.
• As-Built Network Reviews – AI-powered visual automation can help with retrospective network documentation and auditing of as-built networks. Whilst reviewing photos manually is resource-intensive, AI-powered analysis can scale up reviews, enabling post-build audits to be completed across an entire network footprint, which would otherwise be limited to a very small sample of the network estate.
• Customer Installations – issues with light levels, broadband speeds, reinstatement, or even poorly mounted ONTs can result in service delays, issues, or unhappy customers, where an additional site visit may be required. Using computer vision to automate install health checks, operators are able can detect any corrective rework needed on the day of install, as well as guarantee the best possible install experience for their customers, essential for maximising NPS feedback.
• Network Faults and Maintenance – empowering field agents to resolve faults on the first visit is a key objective for all operators, eliminating the need for an additional site visit or truck roll. Crucial for meeting SLAs, reducing time to repair, and ensuring customer satisfaction, an AI-powered visual automation solution can identify potential issues and propose step-by-step instructions to resolve, particularly helpful for complex issues or newer engineers that have less experience.

Vision AI – a better way to benefit from computer vision