IT Agility

Self-healing tool is the answer for order fulfilment woes

Achieve automated resolution of order fallout issues and recurring requests.

Service providers in the connectedness industry face the challenge of meeting customer order fulfilment deadlines. With the introduction influx of complex convergent services, which require bundling of different product offers, order fulfilment is becoming more unstable and delayed. The ongoing mergers and acquisitions in the telecom industry make the process much more complex, leading to higher order fallout rates. Order fallout in the order orchestration life cycle results in customer churn and revenue loss for service providers. Hence, a swift resolution to the fallouts is a prime necessity.

Improve incident resolution time by up to 98% using a holistic tool that reduces order fallouts in the Order-to-Billing journey.

IT Agility

Cure data pollution at source with data intelligence engine

Leveraging data-driven network inventory wizard to arrest 90% of errors

Service providers in the Connectedness industry manage inventory data, consisting of their assets and services that are critical to their operations. These assets grow every day, making them difficult to manage. In general, the service providers manually register their inventories once their capacity management team forecasts and decides to expand the network. Hence, building an efficient inventory management system with an intelligent User Interface (UI) becomes important to guide the users in the registration process. The lack of such intelligent registration tools will hinder the ability to plan optimized networks resulting in delayed service, poor customer satisfaction, and loss of revenue.

Some of the key factors that lead to inventory data issues are

  • Manual registration of assets and services in the OSS inventory
  • Duplication of records due to lack of efficient validation tools
  • Multiple siloed inventories

To overcome the above-mentioned issues, service providers need to Introduce a data-driven inventory wizard with business rules to improve the registration quality and arrest the errors at the source, thereby maintaining a high quality of data in OSS inventory.,/p>

With a data-driven inventory wizard in place, service providers can realize major benefits in data integrity of inventory, such as:

  • Timesaving: Improves manual registration time by 87.5%.
  • Accuracy in data: Registration accuracy on an average improves from 70.5% to 98%.
  • Reduced efforts: Reduces manual data entry by 65% and the rework to be done due to errors during manual registration

Regardless of the tools or technologies used to tackle data integrity issues, discrepancies still happen. This issue must be fixed during the manual registration process to have a high-quality inventory data.

Fig: Key Capabilities to be built on data-driven inventory wizard

Operational Excellence

Creating a smart field workforce with an AI-powered video guide

Leverage video AI to improve field engineers’ efficiency, reduce site visits, and accelerate install to commission cycle time by 3X

Inefficiencies in field services contribute the most to the capital expenditure of service providers. One of the major reasons for field service inefficiency is repeat site visits or rework, leading to a 5X increase in repair cost and delay in order delivery time.

In the case of field surveys, data shows that 40-60% of installation orders require a site survey, out of which 18% require repeat surveys. The sites survey is done manually, requiring manual data capture and physical audits leading to errors and incomplete data. Hence, the process becomes extremely time-consuming.

To overcome these challenges, service providers must leverage the power of video intelligence. Prodapt’s AI-driven video intelligence framework powered by Vyntelligence can create a smart field work force. Surveyor captures a video and voices it over, using a guided storyboard. The framework auto-captures the details and sends alerts for missing details. A survey is submitted with 100% details and can be a point of reference for specific details or future changes. This leads to 3X acceleration in installation time and improved customer experience.

Enable field engineers with AI-powered devices to improve ‘right-first-time’ field work and enhance customer experience through reduced

The three main components of this framework are –

  • AI-assisted video guide – Provides a structured guided storyboard for field engineers to effortlessly capture the data
  • Recommendation engine – Enables guided actions to various business stakeholders. Gives AI-powered recommendations and real-time visibility into the jobs to supervisors, auditors, and field engineers
  • Smart dashboards – Provides end-to-end visibility into jobs driving smarter actions for management and business as a whole
Operational Excellence

Combining the power of RPA and AI to keep customer experience unharmed during network outages

Leverage RPA and AI to build and implement a proactive two-way Conversational Framework to reduce OpEx, boost agent productivity and improve NPS

According to recent statistics, 30% of the service providers’ contact center calls are network outage related. Their inability to predict these outages on time and provide prior information to the customers results in contact center call spikes, customer dissatisfaction and a low NPS score. This also increases the OpEx for contact centers and may lead to a reputational loss for service providers.

To overcome these challenges and improve NPS, service providers must create a central Intelligent platform capable of orchestrating seamless conversation between the contact centers and customers. This is established by implementing a “Two-way conversational Framework”. The steps involved are:

  • Step 1: Auto-identification of outage information
    Build a standardized process to identify relevant outages in the network monitoring systems. Integrate them with an outage monitoring dashboard for BOT to auto-extract outages and store them in a central database.
  • Step 2: Schedule notification
    Perform automated validation and intelligent scheduling to send proactive notifications to the impacted customers in a well-organized structure.
  • Step 3: Notify and engage with customers using a Conversational AI BOT
    Send proactive notifications, and if the customer has additional queries, the bot can engage in a conversation using the conversational AI

Conversational AI Bot orchestrates bi-directional communication and provides seamless customer experience during common network outages.

Digital Customer Experience

Making of an intelligent Virtual Agent to transform Customer Experience

Leverage a Machine Learning-based approach for optimizing Virtual Agent Training to improve its precision, recall and accuracy

Virtual agents are an integral part of businesses with an online presence as they provide round-the-clock assistance to customers. They augment teams to enable a rich experience for both customers and live agents.

The success of any Virtual Agent (VA) depends on its Natural Language Understanding (NLU) training, which should not be just a one-time activity before the configuration, but a continuous process. The challenge is to provide the right set of representative examples from historical data for the training. Identifying a few hundred sample examples from millions of historical data is a herculean task. Moreover, this task is often done manually. Thus, the task of finding the most suitable examples becomes questionable as well as extremely time-consuming.

Service Providers must develop a Machine Learning (ML)-based tool to identify the most appropriate and small data set of representative examples for training. The examples cover maximum scope for the respective intent, making NLU training highly efficient with improved precision, recall and accuracy. The ultimate benefit of this is improved customer experience, containment, and reduced abandonment. Since this is a tool-based approach, it also saves a lot of time in comparison to the manual process of identifying the training examples. Improved training efficiency in the first go also saves time and effort during subsequent re-training.

Figure 1: ML-based intent analyzer tool

VAs often fail to satisfy the customers due to their inability to identify the right intent. And this is the effect of wrong or inadequate training of VA’s natural language understanding (NLU) engine.

IT Agility

Close the gap in network inventory to improve customer service

Leverage an RPA-based solution strategy to address inventory data inaccuracies and have a better insight into your network

Network inventory is the cornerstone for any service provider. To deliver seamless network services, assets and infrastructure (computers, routers, servers etc.) are a must. And the inventory available with an operator determines the kind, quality, and capacity of any services they offer. Therefore, these assets are crucial as service providers in the connectedness industry cannot operate without them.

However, service providers face several challenges in managing the completeness and accuracy of inventory data. Inventory data issues majorly arise due to human errors by field engineers, multiple sources of truth as a result of mergers and acquisitions and non-digital data storage formats. These issues eventually increase the lead time for new installs/repairs, high volumes of calls by field technicians to the customer care, frequent provisioning fallouts, etc.

Service providers must take a holistic solution approach to tackle the core challenges that are crippling them from effectively managing the network inventory data integrity issues. Manual data reconciliation projects are proving to be ineffective as they are labor-intensive, time-consuming and cannot handle network environments that are rapidly changing. Adopt an RPA-based automated inventory reconciliation framework to accelerate data integrity programs and improve service.

Figure 1: RPA-based Automated Inventory Reconciliation Framework

Service providers’ network inventory systems are often 20-30% out of sync with the physical and logical state of the network. An RPA-based automated inventory reconciliation framework can accelerate data integrity programs.

Software Intensive Networks

Building a 360° Network Cockpit

Implement an intelligent network visualization solution powered by Graph technology to deliver network insights faster.

Owing to rapid network expansion, major service providers in the connectedness industry are facing a critical challenge with the rise of data silos in their ecosystem. As a result, network data is dispersed across a variety of siloed and disjointed systems. This makes deriving insights from data collected across diverse assets more difficult. Several disconnected systems that consist of untraceable integrations and interfaces must be integrated to get a comprehensive view of the massive dataset. As a result, the service providers face inefficient network and resource utilization, delays in rolling out new network designs, and ineffective network troubleshooting.

There is a necessity for service providers in the connectedness industry to build a real-time 360° Network Visualization to drive smart decision making. Most service providers have started to implement Graph databases to address the problem of data silos and information irregularities in Network management. To be effective, service providers must develop both upstream and downstream data ingestion strategies. In this insight, we explore these two key components in-depth and identify the key capabilities required to build them effectively. Incorporating the 360° real-time network visualization approach can create a convergent and intelligent view of the network. In the Connectedness market, it helps to meet the growing demands of Network Planning, Network Operations (NOCs), and various user communities.

Eliminate data silos and irregularity challenges in Network management and accelerate design rollout by 33%.

IT Agility

Attract and retain customers with enhanced broadband service coverage

Leverage a unified serviceability framework to improve the service qualification

Today, most service providers in the connectedness industry are challenged in determining the service availability for different customer addresses as it is cumbersome and time-consuming. Ineffective broadband service qualification results in the poor customer experience of the existing customers and the unserviceability of new customers. Hence service providers need to focus on improving the serviceability for retaining and enlarging the customer base. The major factors contributing to ineffective service qualification include:

  • Lack of support for multiple technologies (e.g.) Copper, Fiber, IPTV, Cable, Fixed Wireless
  • Lack of agility to accommodate the real-time needs of the customer
  • No standard address and service repositories
  • Inaccurate measurement of loop length, resulting in reduced service offering

Service providers can leverage a unified serviceability framework to overcome these challenges and improve the serviceability of the customers. It assists in responding to customer requests rapidly with improved customer engagements and real-time responses for service qualification inquiries. Further, it helps to improve the overall broadband qualification coverage and customer experience.

Ineffective broadband service qualification results in the poor customer experience of the existing customers and the unserviceability of new customers.

IT Agility

Achieve security objectives at speed with automated vulnerability management

Reduce time taken to fix security vulnerabilities by 50% with vulnerability analysis best practices

Cyber-attacks are increasing every day and are now the third-highest global risk, according to the World Economic Forum. GSMA’s mobile telecommunications security threat landscape report of 2019 says, “there was a 55% increase in breaches caused by open-source software vulnerabilities”.

Addressing security vulnerabilities is a top priority for service providers in the connectedness industry because a cyber-attack could disrupt services for millions of customers, impact customer’s trust, and deteriorate service provider’s brand & reputation. To achieve the required security objectives, service providers must adopt a structured approach to vulnerability management. Vulnerability management, which is the process of finding, assessing, remediating, and mitigating security weaknesses for known assets, gives service providers the ability to assess the status and risk of unknown hardware/software.

Depending on the service provider’s infrastructure size and state of the configuration management database (CMDB), finding the responsible asset owner can be a highly challenging and cumbersome task, resulting in lead times of up to many weeks. Therefore, vulnerability management must include automation to discover new vulnerabilities, perform risk assessment, and assign it to the right team for a quick resolution.

Addressing security vulnerabilities with speed is a top priority for service providers as a successful cyber-attack can essentially disrupt service for millions of customers

Fig:  Steps followed in field service operation showcasing the importance of spare information

Software Intensive Networks

Accelerate SD-WAN service delivery to serve the pent-up demand for the enterprise connectivity

Automate and digitize workflows to achieve touchless SD-WAN configuration, provisioning, and activation

Before the pandemic, SD-WAN was primarily marketed to enterprises to reduce costs and improve flexibility. As businesses realized the pressure to go digital, cloud applications became the foundation for most organizations, enhancing their productivity and collaboration. What eventually evolved into an absolute necessity was to run these essential applications more efficiently, on a more reliable network -which is why SDWAN has become one of the most successful networking functions in decades. What will further fuel this adoption is the recent shift to a mostly remote or hybrid workforce model. According to a report by IDG Research Services and Masergy, over 90% of organizations expect to adopt an SDWAN solution eventually.

For businesses, Managed SDWAN Services provide attractive opportunities to tap into the growing SDWAN market and create new revenue streams. As per Markets and Markets Research, the global SD-WAN market size is expected to grow from USD 1.9 billion in 2020 to USD 8.4 billion by 2025, at a CAGR of 34.5% during the forecast period.

But businesses can seize this opportunity only if they fulfill their customer needs on
time – by quickly activating the SD-WAN services. Potential roadblocks such as validating network compatibility, managing the service across multiple platforms, and solving the integration, operational and process-centric challenges can significantly delay the order to activate journey – leading to revenue loss and missed opportunities.

To accelerate the entire Order-to-Activate journey, businesses must eliminate process inefficiencies and embrace automation and digitalization at various levels.

To accelerate the entire order to activate journey, businesses must eliminate process inefficiencies and embrace automation and digitalization at various levels. This also means building a holistic tool that enables consolidating and automating workflows to achieve touchless SDWAN configuration, provisioning, and activation.