Category: Operational Excellence

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Operational Excellence

Turn your network issues into customer delight

Leverage automation strategies to streamline the Trouble to Resolve (T2R) process, providing customers with quick resolution and greater satisfaction

TM Forum, a global industry association for service providers and their suppliers in the telecommunications industry, has a business process framework -eTOM’s (Enhanced Telecom Operations Map) Trouble to Resolve (T2R) process. It reveals how to deal with a trouble (problem) reported by the customer, analyze it to identify the root cause of the problem, initiate resolution to meet customer satisfaction, monitor progress and close the trouble ticket.

Most Service Providers follow the eTOM T2R process, however, they encounter key challenges that affect the overall T2R operational efficiency and increase the OPEX.

  • Multiple siloed systems to complete a network event’s lifecycle leads to high manual effort and increased OPEX
  • Difficulty in identifying the right impact of a network event-
    • No proper tools for auto-identification & prioritization of critical events that would cause major business impact
    • Resource wastage: Network Operation Centre (NOC) tends to spend a significant amount of time handling huge volumes of
      alerts
  • Difficulty in meeting business KPIs due to unavailability of fully integrated systems and automated processes

Service Providers in the connectedness industry must develop an effective strategy for integrating the systems and bringing end-to-end automation to the T2R process flow. The majority of service providers have a basic level of automation, however, there is a huge scope for complete lifecycle automation. This Insight showcases an effective approach for implementing end-to-end automation of network event lifecycle from event creation to resolution. The approach is based on the implementation experience of leading service providers at multi-geographic locations.

“According to a report by McKinsey, many service providers have complex fundamental processes with multiple system integrations and are labor-intensive and costly. Leveraging digital technologies to simplify and automate operations makes them more productive and results in a significant cost reduction of up to 33%.”

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Operational Excellence

Steering data migration, powered by RPA

Leverage RPA based Automation Framework to accelerate data migration and improve accuracy

Data migration involves moving data between locations, formats, and applications. This need is on the rise due to ongoing trends such as mergers and acquisitions (M&As), migration of applications to the cloud, and modernization of legacy applications. However, the execution of data migration using traditional methods is not at par with the increasing frequency!

According to Gartner, 50% of the data migration initiatives will exceed their budget & timeline by 2022 because of flawed strategy & execution. Most of the service providers in the connectedness industry adopt the traditional approach for data migration that involves three broad steps: migration planning & preparation, establishing governance, and execution.

Service providers follow the fundamental extract, transform, load (ETL) data migration execution methodology, which is full of challenges. It entails high cost and time due to mock runs and testing for each module. Moreover, it involves manual efforts, which leads to a lot of re-work due to errors and causes fallouts due to data integrity issues. Also, ramping up and down the teams is difficult.

To overcome these challenges, an RPA based automation framework for data migration execution could be an effective approach. The framework encompasses components such as:

  • Smart processor: Identifies data quality & integrity issues in the source data at a very early stage
  • Automation bot: Performs migration/upgrade by extracting & updating data at various layers of the application
  • Fallout management mechanism: Automates the fallout handling, i.e., Fix data quality & integrity issues in CRM, inventory systems, etc.

” According to Gartner, 50% of the data migration initiatives will exceed their budget & timeline by 2022 because of flawed strategy & execution.”

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Operational Excellence

Go Beyond RPA to Speed Up Transaction Processing Time

Leverage effective continuous improvement techniques to achieve a high straight-through processing rate

Straight-through processing (STP) refers to the automated processing of transactions without manual intervention. Transaction processes are usually multi-staged, requiring multiple people across different departments and sometimes even involving paper checks. Companies often adopt RPA as a one-time solution to complete transactions and achieve a high STP rate. But is it really effective?

The estimated STP rate for any service provider in the connectedness industry is 75%-85%. However, the actual realization is only 30%-50%. One of the reasons that has contributed to the average rate is implementation of only RPA by service providers. Other widely used continuous improvement techniques like occasional continuous improvement and analytics-driven continuous improvement have proven to be less effective to achieve the targeted STP rate. Service providers must adopt effective continuous improvement methods to get more value from their existing RPA implementation.

Adopt the Automation Optimizer Framework, an efficient continuous improvement strategy to improve your STP rate. The framework identifies automation inefficiencies, root causes, and solutions for the identified gaps and continuously monitors the STP rates- all in an automated manner. Its key components are:

  • Intelligent RCA (Root-cause analysis) Engine: Drills down to transaction-level information to automatically identify the root-cause for fallout
  • Integrated Solutionizer: Constantly analyzes the output from an Intelligent RCA Engine and triggers respective action based on the identified root cause
  • Continuous Monitoring Tool: Tracks the STP rate progress over time for the defined objectives, KPIs and milestones


The estimated STP rate for any service provider is 75%-85%, however, the actual realization is only 30%-50%. Only RPA implementation will not suffice if the STP rate has to be improved.

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Operational Excellence

Giving wings to your standard RPA bots

Combine the power of RPA with NLP to improve the automation potential of service provisioning

Most service providers in the Connectedness industry have started leveraging Robotic Process Automation (RPA) to automate various processes, especially in service provisioning. However, the standard RPA bot alone cannot automate the end-to-end provisioning process, as it involves a lot of unstructured data that requires manual intervention for processing. According to Gartner, “Today, 80% of enterprise data is unstructured”. Processing such a huge amount of unstructured data and performing end-to-end automation with a standard RPA is a major challenge for service providers.

To overcome this challenge, service providers can combine the power of RPA bot with a Natural Language Processing (NLP)-based engine capable of extracting information and processing the unstructured text. It further helps in deriving insights and providing the next best action, all in an automated way. This end-to-end automation helps the service providers to reduce the cycle time and provide efficient services to their customers.


According to Gartner, “Today, 80% of enterprise data is unstructured”. Standard RPA alone cannot process such a huge amount of unstructured data and perform end-to-end automation.

    Authors:
  • Madhusudhanan S
  • Velmurugan M
  • Gurunath L V
  • Mogan A.B.

Categories
Operational Excellence

Breaking down the barriers to scale RPA across the enterprise

Proven methodologies to create a steady pipeline of processes to be automated

Service providers across the globe are at various stages in their journey to embrace robotic process automation (RPA) to increase their operational efficiency. But scaling RPA and making it an organization-wide success is a big challenge. As per Deloitte’s Global Robotics Report 2018, over 80% of organizations implementing RPA were happy with the results, but only 1% of them could scale considerably in the past 1 year (50+ bots in a year).

The inability to identify appropriate use cases after initial implementations are the major bottleneck for service providers. The lack of end-to-end visibility of the process by the siloed business units further adds to this plight.

Service providers must explore various methodologies to create a steady process pipeline that can be automated. These techniques are – comprehensive analysis, design thinking workshop, and process mining.

Figure 1: RPA Demand Generation Methodologies

Download the Insight to learn about the techniques in detail and learn how to choose the correct method as per your organization’s maturity stage.


As per Deloitte, 80% of organizations implementing RPA were happy with the results, but only 1% of them were able to scale considerably in the next 1 year

Categories
Operational Excellence

Fiber is fast, but rollout needs to keep up

AI/ML can forecast delays before they occur, making the service delivery predictable and fast

The global pandemic has highlighted the fact that high-speed broadband is a necessity, not a luxury. And fiber is one of the ways to faster broadband. This appetite for fiber means that service providers need to roll out fiber-based connectivity services faster. However, with the rising complexities in the order management process, delivering the service within the specified timeline is becoming a nightmare. The main business issue is unpredictability, which may be as important as speed. Its absence means frustration for service providers and their customers.

The main cause of this lack of predictability stems from the structure of the process. In many cases, the enterprise service delivery process has evolved and grown organically. The most common causes of dysfunction are:

  • Multiple teams operating in silos prevent a clear view of the process and a single source of truth
  • Manual hand-offs leading to errors and delays
  • Dependency on external vendors, resulting in vendors operational issues being transferred to the service provider
  • Lack of strategies to forecast order delays
  • Lack of mechanisms for real-time tracking of service delivery flow

To overcome these challenges and tap into the next wave of opportunities, service delivery operations will require an advanced vision. AI/ML is at the heart of that vision. With AI/ML in service delivery, enterprises can predict and address delays before they impact the business. Enterprise AI can, over time, improve the prediction of potential delays and delivery dates at all points of the order journey. Over time, enterprises can achieve faster processing of orders with improved predictions.

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The appetite for high-speed broadband demands a faster rollout of fiber-based connectivity services.

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Operational Excellence

Accelerating Digital Transformation with Hyperautomation

Leverage the power of RPA, process mining and AI for end-to-end process automation to increase automation rate, reduce operational expenditures and improve customer experience

‘Hyperautomation’ is one of Gartner’s Top Strategic Technology Trends for 2022. Hyperautomation aims to identify, analyze, and automate business processes to the greatest extent possible. It involves orchestrating the use of multiple technologies, tools, and platforms to streamline business processes.

Legacy infrastructure and outdated processes can hinder an organization’s ability to compete. Automation of only task-based processes will not deliver the cross-functional results needed to drive business decisions and outcomes. By automating as many processes and tasks as possible, hyperautomation transforms an organization.


Increase connectivity, efficiency, and agility in business operations with hyperautomation.

As per Gartner, hyperautomation will lower operating costs by 30 percent or more by 2024, thereby increasing connectivity, efficiency, and agility of business operations. The businesses in the connectedness vertical can achieve end-to-end process automation and scale up the automation rate by building and implementing a hyperautomation framework that includes four key components:

  • Intelligent Process Orchestrator: Orchestrates bots, people, and IT applications for end-to-end integration of any business process.
  • Conversational AI: Automates all sub-processes that requires a conversation with humans. Conversational AI understands natural language and converses with the customer.
  • Low-code Applications: Helps to automate the sub-processes that require aggregating data from humans by building applications/interfaces rapidly.
  • Unified Hybrid Dashboard: Provides a real-time integrated view of the order completion process, resolution time, automation success rate, and many other KPIs. It also highlights the actionable insights.
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Operational Excellence

Accelerate cash flows by faster order processing

Managed Digital Transformation to reduce Order-to-Activate (O2A) cycle time and increase new business wins

The Order-to-Activate (O2A) process is at the heart of every business operation. Simply put, it refers to the end-to-end process of receiving, processing, and fulfilling a customer’s order. A smoother and more efficient order flow will allow the company to process more orders, thus allowing the business to grow more quickly.

The Order-to-Activate process cannot be conducted in isolation; it depends upon numerous roles, departments, and systems. For example, a typical digital service provider takes 15+ teams to traverse through 55+ systems to complete one order. These complexities and increasing inefficiencies in the O2A process leads to longer cycle time, delayed revenue realization, and higher cost.


The complexities and increasing inefficiencies in the Order-to-Activate process lead to longer cycle times, delayed revenue realization, and higher costs.

Businesses need to ensure that their business runs smoothly, and the orders are delivered efficiently and accurately, with minimal chances of error. Adopt the Managed Transformation Model to achieve long term sustainable business benefits like reduced cycle time, accelerated revenue, enhanced customer experience, and maximized cost savings. By doing this, a business can transform its operations holistically and address all the challenges in the O2A process.

Businesses can ensure a reliable and undisrupted high-speed broadband service by adopting the ‘Zero-touch service assurance’ framework. This framework enables continuous remote monitoring to detect connectivity issues proactively and provide automated resolutions.

The model encompasses transformation levers such as:

  • Agile Work Cell: Consolidates multiple functional roles into one hence, reducing the touchpoints in the O2A process. It ensures better control, promotes transparency and eliminates handoffs
  • Process Optimization & Automation: Analyzes the current performance and cycle time elongation factors to identify and implement improvement opportunities
  • Operational Accountability: Provides a Dashboard with end-to-end visibility into each order and the milestones. It also helps in governance, performance tracking and reporting
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Operational Excellence

Shift gears to an automated RPA code review for faster development of bots

Most service providers in the connectedness industry have started leveraging Robotic Process Automation (RPA) to streamline their business processes. Standardizing the bot development process and scaling the bot velocity are the most important goals of any RPA Center of Excellence (CoE). One of the major roadblocks faced in this mission is the manual review of the RPA code, which is a highly tedious task. It is not only cumbersome but also time-consuming and prone to errors. Although the RPA code review process is of utmost importance to reduce post-deployment defects and costs, the manual approach is crippled with challenges and is highly inefficient.

To overcome these challenges, service providers should automate the code review process. To achieve this, service providers can leverage a platform-agnostic RPA code reviewer bot that can review

  • Hundreds of variables, arguments, activities and message boxes
  • The logic for exception handling, custom logging, queues and credential management

Fig. Leveraging code reviewer bot to automate RPA code review process


Although the RPA code review process is of utmost importance to reduce post-deployment defects and costs, the manual approach is crippled with challenges and is highly inefficient.

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Operational Excellence

Optimizing RPA implementation with increased automation potential

A lot of players in the connectedness industry have started embracing Robotic Process Automation (RPA) to automate different tasks across various systems and streamline their business processes. However, service providers are still finding it difficult to optimize one of the most important success factors of RPA implementation – the automation potential. Incidentally, the answer to this challenge lies in the initial steps of the implementation roadmap itself.

An ideal RPA implementation roadmap consists of seven steps, from Proof of Technology (PoT) to the actual go-live of RPA. The key to increasing the automation potential of any process lies in effectively performing the first 3 steps – Proof of Technology, Process Assessment, and Input Standardization. This insight elaborates on specific tools and techniques to excel in these steps and increase the automation potential by 25%.


One of the most important success factors of RPA implementation is increasing its automation potential.