Category: Operational Excellence

Leverage AI/ML to forecast delays and reduce customer churn

Fibre to the Premises (FTTP) service delivery includes deploying high-speed fibre optic connections directly to the customer premises, which involves several complexities and unexpected delays in order fulfillment. These delays can lead to missed SLAs, high customer churn, and compensation liabilities for Communications service providers.

According to Forrester, “70% of customers are likely to churn if orders are delayed, and proactive information about orders are missed”. Hence, an intelligent FTTP service delivery becomes imperative for service providers in the Connectedness industry.

Leveraging an AI/ML-powered FTTP service delivery framework can help service providers predict and address order delays before they impact the business. With the predictions from the ML model, the operations team can gain a view of the expected delays, root causes, and ways to overcome them. This helps reduce operational overload and customer churn.

Fig: Leveraging an AI-powered FTTP service delivery framework for on-time provisioning and improved customer experience

Utilize the FibrePro Analytics Maturity (FAM) Model for improved decision-making, enhanced customer satisfaction, and cost efficiency

While organizations have made substantial investments in data and analytics, an HRB report reveals that only 23.9% of companies identify as data-driven, and merely 20.6% have successfully cultivated a data-centric culture. The level of data analytics maturity is a critical element for fibre operators in transitioning from intuition-based decision-making to an insight-driven organization.

Below are the primary challenges faced by fibre operators in achieving data analytics maturity despite huge investments.

• Lack of data and analytics strategy aligning with business
• Cultivating a data culture that binds data talent, tools, and decisions
• Creating a robust data architecture that enables controlled, secured data access and utilization
• Building a skilled team with both domain and data analytics expertise

Employ the FibrePro Analytics Maturity (FAM) Model, a holistic framework for fibre operators to overcome these hurdles and build a fully integrated data-driven organization. FAM synchronizes data capability and adoption maturity to enhance data analytics maturity across the fibre journey. This model comprises 4 key stages: Descriptive, Diagnostic, Predictive, and Prescriptive & Cognitive.

This Insight delves into the journey of data analytics maturity for service provisioning use cases, underscoring its pivotal role in boosting revenue generation, competitiveness, and customer satisfaction for fibre operators.

Put your Fibre on the Fast Lane with the Fibre Design Framework (FDF) and get deliverables right the first time

As per Research & Market, the global Fibre-to-the-Home/Building (FTTH/B) market is projected to reach US$29.7 B by 2026, growing at a CAGR of 13.1%. Considering such enormous growth and demand for fibre, efficient and commercially viable fibre planning and design is becoming incredibly important.

However, fibre operators face several challenges in Plan and Design phase that lead to budget overruns, missed deadlines, and loss of competitive edge. Here are some challenges:

• Skill shortage: Slows down the fibre rollout
• Manual work: Takes longer duration due to multiple hand-offs and paperwork in the High-level Design (HLD) and Low-level Design (LLD) stages
• Unstandardized designs: Leads to quality/consistency issues in templates and documents
• Unstructured work culture: Generates incorrect/missed field inputs

To overcome these challenges, fibre operators must consider ways to automate the key fibre design processes. The Fibre Design Framework (FDF) discussed in this Insight can bring high levels of automation in the fibre design process, and accelerate rollout time by 2X. The framework encompasses key components such as –

• Automated HLD generator: Create an automated high-level design with defined design standards and parameters
• Task Collaborator: Manage workflows digitally, collaborating tasks across multiple teams, and systems
• Field Navigator: Capture video-enabled field inputs across existing and planned design network elements
• Quality Gateways: Integrate quality management gates at crucial junctures

Embed a Value Driven Continuous Improvement (VDCI) function in your operations organization for superior customer experience and operational efficiency

There is fierce competition between fibre operators to acquire the top spot. And one way to remain competitive is to constantly improve or advance their operations while keeping costs in check and ensuring a seamless customer experience.

However, 60% of all corporate six sigma initiatives fail. Talking specifically about fibre operators, we observed that they still rely on traditional operations improvement activities performed on a one-time or on-demand basis translating to a limited-time benefit only. Also, these activities need to catch up with the fast-changing fibre environment.

As a result, fibre operators suffer from various challenges, like the inability to meet coverage targets on time, overshooting budget, and delays in service delivery. Despite a lean operating model, they fail to sustain continuous improvement, resulting in poor customer experience, huge investments, and unsustainable strategies

The need of the hour for fibre operators is a massive shift in their culture towards continuous improvement. They must embed a Value-Driven Continuous Improvement (VDCI) function into their organization’s structure to instill a culture of constant advancement, reduce OpEx and stay ahead of the competition. The critical stages of the VDCI function are Discovery, Formulation, Execution, and Evaluation.

Leverage process orchestration framework to achieve faster integration with partner service providers and improve operational efficiency

Businesses in the Connectedness industry are actively looking to expand their roots into the untapped fiber market. And to do so, most of them prefer to go with off-net services, i.e., leasing network infrastructure from a partner service provider. It enables quick and cost-efficient customer acquisition for establishing a larger footprint.

As per the annual report of a leading full fiber operator in the UK, off-net revenues account for 50% of their total revenue. Therefore, service providers must overcome the challenges that hinder them from supporting lean off-net operations and improving customer satisfaction.

Service providers in the off-net space face the following challenges:

• Integration with multiple partner service providers is complex, time-consuming (18+ months for each integration), and expensive
• Lack of visibility into the partner service provider’s network leading to disjointed operations
• Lack of transparency across E2E process management, leading to multiple follow-ups
• Increase in Tail order processing cycle time (i.e., order processing time by partner service provider)
• Significant manual processes owing to the dependency on the partner service provider
• Lack of standardized processes and a unified way of handling the orders/cases

The above challenges call for a complete transformation of the off-net services. Use the off-net process orchestration framework that acts as a central orchestrator to bridge the gap between service providers and partner service providers. It reduces operation costs by 56% while providing better control and visibility into E2E processes. Experience 3X faster integration with partner service providers using the framework.

The key ingredients of the framework are:

• Simple interface aggregation: Use an interface aggregation platform to enable quick integration with the partner service provider and accelerate fiber adoption
• Unified task orchestration: Create an end-to-end process flow map to get a complete view of the order and issue status
• Point-to-point ticketing: Integrate customer self-service with automated troubleshooting. Use bots to raise tickets directly with the partner service providers
• Off-net SLA governance and reporting: Drive partner service provider-specific SLAs with automated follow-ups and real-time reports on aging and penalty metrics

Leverage RPA for Mobile Number Porting with lesser workforce and time, ensuring resolution at the first instance

Mobile Number Portability (MNP) is a facility which allows subscribers to retain their phone numbers even after switching operators, services, or locations. MNP implementation started in the late 1990s in mature European markets like The Netherlands and UK. It offers favorable benefits to customers like lifelong ownership of the number, better services due to increased competition and efficient mobile number planning & administration. But this comes at a cost to the operator with minimal impact on customer – setup cost, maintenance cost, and call routing cost.

All Call Query is the most widely used mechanism of MNP and is the most efficient method for large, interconnected networks. It’s a direct routing scheme which makes use of a centralized number portability database (CNPDB). The process is highly efficient as the donor operator is nowhere involved in the entire scenario.

Figure 1: All Call Query- Mechanism of number porting

Service providers often have to fetch orders from multiple customer portals, making it one of the biggest challenges in MNP. As a result, the process becomes more cumbersome and complex. Moreover, the process requires high manual intervention, making it prone to errors and reducing efficiency. Service Providers must embrace RPA to overcome these challenges. Using RPA, they can:

• Fetch orders from multiple portals
• Search and aggregate data from various web and Citrix-based applications
• Automate order entry in legacy applications

Automate processes and achieve faster ROI with full-featured RPA

Employing staff is the biggest operating expense for service providers in the Connectedness industry. Employees are also their greatest asset. Automation technology advances enable service providers with new ways to maximize employee productivity, revenue, and customer satisfaction while minimizing human error. One of those advances is robotic process automation (RPA), a broad, deep category of tools for automating business, network, and operational processes.

RPA can automate mundane processes which are tiring and boring for a human to do all day long – the kind of fatigue that results in mistakes and expensive turnover. By providing what customers seek faster than a live agent can, RPA eliminates one of their major complaints: wasting minutes on hold to speak with an agent or hours or days for a work order to be processed manually. The big advantages delivered by RPA are customer satisfaction, employee satisfaction, greater revenues and profits, security, and reliability. But the biggest obstacle to achieving these ends through RPA misunderstands how and where it can be deployed. This insight, sponsored by Prodapt and published by TM Forum, elaborates on how to embrace RPA across the business processes to achieve greater efficiencies, improved customer experience, and faster ROI.

Leverage AI/ML to enhance the efficiency of your day-to-day business operations and improve customer experience

Today’s digital-savvy customers demand advanced and ultra-rich experiences. Therefore, factors like service availability, turnaround time, and quality of service (QoS) are becoming increasingly important. But the question remains how can Service Providers bridge the huge gap that currently exists between customer demands and their fulfillment?

Service providers’ current infrastructure and service delivery approach are unable to match up with customer expectations. There is a dire need to enhance their key operational areas such as customer service, service assurance and network automation.

Artificial Intelligence/Machine Learning (AI/ML) technology, with its recent advancements, is fast becoming the choice of service providers to bridge this gap and improve operational efficiency. AI/ML systems, together with Bigdata, can process huge amounts of historical and real-time data from various systems such as CRM, billing systems, NMS/EMS, and product catalogues to provide actionable insights and predictions.

Service providers must adopt AI/ML solutions in their infrastructure to offer next-generation services and experiences.

• Intelligent software-defined approach for operations and delivery of services (virtualization, self-healing, and self-learning networks)
• Automation of customer service and customer experience improvement (chatbots, virtual assistants)
• Predictive maintenance and agile operations (automated problem detection, troubleshooting, and optimization of networks)
• Innovation in subscriber profiling, usage analysis, and personalized offers