Leverage DesignBuddy to cut design cycle time by 30%, speeding up product time to market by 15%, and lowering design phase costs

Solution design is a crucial phase in software development, defining product architecture and requirements. Creating these software solution blueprints has traditionally been a complex and manual process. Gathering comprehensive requirements from diverse stakeholders while ensuring scalability and performance is challenging, often leading to cost overruns, potential errors, and inefficiencies.

Key challenges in the Software Solution design (SSD) creation process include:

• Knowledge Fragmentation: Design info is scattered across formats and systems, causing inconsistencies
• Knowledge Concentration: Reliance on a few experts creates bottlenecks & risks if they are unavailable; organizations with high dependency on key individuals experience 26% more project delays
• Technology Evolution: Frequent tech changes outpace manual design methods
• Inconsistent Quality: Manual designs are prone to human error, leading to inconsistencies; ~15 -20% increase in time-to-market due to delays in design retrieval and inefficient design processes

Failure to address these challenges can lead to missed revenue opportunities, loss of market share, or inability to scale innovations. Leverage Generative AI to address these challenges and revolutionize SSD creation by facilitating rapid knowledge gathering, retrieval, and content generation for designers. Implement the DesignBuddy Framework, powered by Generative AI, for an interactive and standardized automated SSD generation process. This framework systematically understands user demands, retrieves relevant data, conducts impact analysis, and generates tailored solution designs. As a result, it boosts design efficiency by 30%, accelerates time to market by 15%, and ensures consistent, rapid software releases to maintain a competitive edge.

Figure : DesignBuddy Framework and its four key components

Leverage Generative AI to enhance your agent productivity by 30% and cut your Business Process Services (BPS) costs by 20%

Outdated Business Process Services (BPS) operations are a critical barrier to efficiency and profitability for service providers. Legacy systems across crucial BPS functions, such as Order Management, Billing & Revenue Assurance, Network Ops, etc., create bottlenecks, forcing agents to navigate slow, error-prone processes.

Key pain points affecting the agent journey (plan & build, service delivery, service assurance)—spanning roles such as Assigners, Tech Support Specialists, Provisioning Specialists, etc., include:

• Delayed Training Deployment: Manual creation of training materials hinders timely deployment, leaving agents without access to essential knowledge when they need it most
• Lack of Intelligent Assistance: Insufficient tools for effective guidance, content generation, and summarization reduce agent productivity and diminish the quality of customer service
• Manual Information Consolidation: Reliance on manual processes to gather and validate information from multiple sources introduces errors, leading to rework and delays in order completion and service
• Inefficient Audit Mechanisms: Traditional audit processes lack real-time validation capabilities, resulting in unaddressed inefficiencies and missed opportunities for performance optimization

Agents hampered by these challenges face rising costs and inefficiencies. Manual processes add 20% to operations costs, and training gaps leave 30% of content uncovered.

The path forward is to reimagine BPS with modern, agile solutions. Leverage Generative AI to transform service provider agent journeys—across planning, service delivery, and assurance—boosting productivity. Implement the Agent Genie Framework , powered by Gen AI, to enhance the agent experience at every stage, reducing effort by 30% and cutting operational costs by 20%. The key components of the framework are:

• Empowerment Hub: Rapidly generate personalized training materials for swift and effective live deployment of agents; reduce agent onboarding time by 50%
• Intelligent Agent Playbook: Assist agents with a quick guide for the next best solution, content generation, and summarization of key information; Enhance response accuracy by ~98% while reducing agent effort by ~25%
• Audit Nexus: Employ an AI-driven audit process that minimizes manual effort and provides instant feedback to the agents. Ensure 100% audit coverage and improve productivity by 20%

Deploy Prodapt’s industry-leading Unified Operations Framework (UOF) as a strategic solution for a streamlined operating model transformation — Achieve a 25% OpEx reduction with Zero service disruptions

M&As in the Connectedness segment are expected to rise through 2024 as technology advancements and the release of pent-up deal appetite lead to a flurry of investments, according to this PWC report. Pursuing this route, Communications Service Providers (CSPs) may adopt shortcuts towards operating model transformation. However, a contrasting perspective from McKinsey emphasizes the importance of careful planning and execution when transitioning from two separate operating models to a newly integrated one. Even in ideal conditions, harmonizing operating models is complex, time-consuming, and challenging.

Several key challenges hinder the effective unification of operating models post-M&A. These include streamlining role redundancy, improving maturity levels across merged entities, and standardizing evaluation systems. Neglecting these aspects can lead to a sharp rise in operational expenditures, customer churn rates, and loss of competitive edge.

To address these challenges and unlock the full potential of M&A, CSPs can leverage the Unified Operations Framework (UOF). UOF offers a comprehensive approach to streamline processes, optimize resources, and integrate systems and teams effectively post-M&A. It employs a function and objective-driven approach to pinpoint areas for operational change and provides specific steps for implementation.

The three key implementation steps recommended by UOF are:

• Redesign business teams aligning with TM Forum’s eTOM framework
• Track automation and outsourcing maturity to enhance operational efficiency
• Define, measure, and monitor Key Performance Indicators (KPIs) to ensure performance transparency and accountability

By adopting UOF, CSPs can achieve a significant reduction of approximately 25% in Opex, and accelerate migration by 3X. This strategic approach ensures sustainable growth and competitiveness in the rapidly evolving connectedness landscape, strengthening the merged entity.

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

Adopt the GenCARE Framework to raise efficiency, streamline processes, and reduce Opex in contact centers

Contact centers deploying AI tools for customer engagement continue to report low satisfaction scores and delayed resolution. A lack of deeper understanding of human languages and inability to comprehend nuances in text and audio messages conveying the need for support are the key reasons. This deficiency results in customer dissatisfaction and, eventually, tremendous damage to the CSP’s brand value. Key challenges faced by contact centers include:

• Natural Language Understanding (NLU): Inability to accurately understand and interpret human languages. For example, misinterpreting customer inquiries (billing, service complaints) containing colloquial expressions leads to inaccurate responses
• Context Retention: Struggle to retain context, leading to disjointed and frustrating exchanges, especially in longer or more complex conversations
• Multilingual Support: Requires additional resources, training, and coordination, especially for languages with limited training data
• Emotional Intelligence: Empathy and emotional understanding are challenging to replicate in AI systems

These challenges significantly raise multilingual support costs (20%-30%) for contact centers, with low chat containment (<20%) necessitating more live agents. This contributes to customer dissatisfaction and increased churn risk, mainly due to prolonged wait times.

As per McKinsey, generative AI can reduce the volume of human-serviced contacts by up to 50%, depending on a company’s existing level of automation. Use our GenCARE framework to enhance contact centers through Generative AI and achieve a 40% cost optimization while boosting customer satisfaction. The key components of the framework are:

• NLU-based intent identification-Integrate the chat platforms with domain customized Generative AI models for quick and accurate query handling
• Context-enhanced agent support-Leverage context retention capabilities to quickly identify customer issues and generate automated notes to boost agent productivity
• Real-time sentiment analysis -Classify and score sentiments using the sentiment analysis module. Respond as per the customer’s emotional status
• Multilingual query resolution-Use language translation to achieve zero wait time with a language-independent unified team

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