Categories
Operational Excellence

Artificial Intelligence in Action

Adding intelligence to robotic process automation

Robotic Process Automation (RPA) is a low-code, low-cost option for the service providers in the connectedness industry to automate high-volume manual processes, delivering cost, efficiency, accuracy, and transparency. By automating a large part of day-to-day activities, service providers can drive accuracy, improve employee morale and productivity, and ensure reliability and consistency of operations. However, to drive the intended benefits from their RPA initiatives, service providers need to understand the difference between the three primary levels of RPA maturity: Basic RPA, Cognitive RPA, and Intelligent RPA.

The Basic RPA relies on easy-to-implement and understanding fundamental technologies such as macro scripts and workflow automation. It is rule-based, does not involve much coding, and uses an ‘if-then’ approach to processing. Cognitive RPA, on the other hand, is a knowledge-based approach. It uses complex technologies such as natural language processing (NLP), text analytics, and data mining to automate parts of the process that Basic RPA cannot. But service providers can primarily benefit from Intelligent RPA, which uses AI/ML technology for decision making. With AI/ML, Intelligent RPA can go beyond data processing (gathering, sorting, calculating, and reporting), automate processes based on continuous analysis of incoming information, and learn to act smarter over time. This is especially beneficial for service providers dealing with large volumes of unstructured data. Furthermore, Intelligent RPA can gather insights and improve them over time while working together for the best results.

The insight elaborates on the three maturity levels of RPA and how to adopt them across the customer engagement lifecycle to help build out and deliver high-value use cases.


With RPA, service providers can drive accuracy, improve employee morale and productivity, and ensure reliability and consistency of operations

Three main levels of RPA maturity

    Authors:
  • Harsha Kumar, President
Categories
IT Agility

A comprehensive checklist to plan a successful migration

Leverage the migration strategy checklist for a quick, error-free, and resource-efficient migration

Migration allows service providers in the connectedness industry to get all the data they require in a single/centralized system. As a result, analysts and other employees have an easier time accessing the required data, which can be used to make better decisions, resulting in a faster time to insight.

Service providers opt for integration/migration programs for various reasons like integration post mergers and acquisitions (M&As), modernizing the legacy systems, changed compliance & regulatory requirements, and technology & feature enhancements. However, most service providers fail to migrate their systems effectively. According to Gartner, more than 83% of integration/migration programs either fail/exceed schedules and exceed budget by approximately 30%.

Leverage this insight for a quick and handy migration strategy checklist, covering both pre and post-migration activities. While the focus of the insight is on order management system migration, the same checklist can be used (with minor adaptations) for any transformation projects within the service providers’ environment.


According to Gartner, more than 83% integration/migration programs either fail/exceed schedules and exceed budget by approximately 30%.

Categories
Operational Excellence

Transforming Telecom Business Processes Using RPA

Leverage Robotic Process Automation (RPA) to accelerate business process transformation and innovation

Robotic Process Automation or RPA is widely used by companies around the globe to streamline their business processes. RPA creates software robots to automate the processes that are highly manual, voluminous, repetitive, and rule-based. Process automation increases work quality, minimizes errors, and allow organizations to scale rapidly.

The service provider’s operational landscape has many mundane processes like service fulfillment, service assurance, billing, revenue management, and network management. By adopting RPA, service providers can quickly and easily automate the manual and tedious processes, without much investment or hassle. As a result, service providers can reduce cost, improve data quality, boost customer service, and drive operational efficiency.

Figure 1: Some examples of processes from the Order-to-Activate(O2A) cycle suitable for RPA

RPA is being widely accepted across industries and serves as a guide to help service providers in their RPA implementation, right from business process assessment till rollout. Topics covered in the insight:

  • Why is RPA becoming popular in the telecommunication industry?
  • Preview of telecom processes with RPA potential
  • The RPA journey of a communications service provider – How to implement RPA successfully?
  • Common challenges faced during RPA implementation

By 2025, 3 out of 10 jobs will be done by software, robots, or smart machines allowing replaced employees to do more crucial jobs. -Gartner.

Categories
Operational Excellence

Data-driven Process Optimization to Accelerate Digital Transformation

With most Digital Service Providers (DSPs) investing in digital initiatives today, transformation is no longer a choice but a must-have!

According to a Celonis study, “Most organizations are struggling with transformation initiatives because they are diving into executions without understanding what to change first. In a rush to innovate, 82% admit that they do not review their internal business processes while setting initial goals for a transformation program”.

Also, DSPs experience increasing process inefficiencies due to the ever-changing landscape. Traditional approaches to handling these processes are more focused on process discovery. They do not provide an accurate view of these processes and the real bottlenecks. Hence DSPs need to embrace a data-driven process optimization approach to look beyond discovery.

This whitepaper details on leveraging a process optimization framework for the DSPs to set business objectives across the transformation journey. It helps identify critical processes, accelerates cost savings by 60%, and improves customer satisfaction by 30%.

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Fig. Key steps of process optimization approach

    Authors:
  • Tom Hoch
  • Rajesh Khanna
  • Sabharinath S
  • Priyankaa A
Categories
Operational Excellence

Robotic Process Automation: The key to accelerate digital transformation

To stay relevant in today’s digital world, the service providers in the connectedness industry should simplify their business and transform themselves into a digital organization.

The road towards digital transformation is a business-critical one, and the service providers embarking on this journey will need to consider how each aspect of their business can be optimized to fulfill the new digital objectives. To optimize the existing processes and keep pace with the competition, service providers should bring the power of RPA in digital transformation.

Automation is not new and Robotic Process Automation (RPA) with its highly evolved level of sophistication, has made it a lot easier to automate processes across a variety of systems and technologies and reap tangible ROI in a very short time. RPA is a delightful journey, and the end-to-end lifecycle needs to be planned across the below phases to accelerate digital transformation.


To optimize the existing processes and keep pace with the competition, service providers should bring the power of RPA in digital transformation.

    Authors:
  • Asad Nabi – Senior Director, Systems Engineering & Software Architecture, CenturyLink
  • Srikanth Pedamallu – Associate Director, Customer Success, RPA & Digital Transformation, Prodapt
Categories
Operational Excellence

Increasing the pace of your process automation programs

Leverage bot development framework to empower RPA Centre of Excellence with bot velocity

Most service providers across the globe have been leveraging robotic process automation (RPA) to increase their operational efficiency and are at different stages in their journey. RPA helps an organization automate repetitive and mundane tasks using the development and deployment of bots or software robots.

But scaling RPA and increasing bot velocity to make it an organization-wide success is a big challenge. One definite solution to this challenge is setting up a robust RPA Centre of Excellence, which not only defines the best practices but also strives to achieve the organization’s goal.

An ideal RPA CoE has the following 7 components:

This insight focuses on the third component, i.e., bot development, specifically on the bot development framework. It throws light on best practices to create a robust development framework for driving bot velocity by standardizing development across the organization. By following these guidelines, organizations can reduce the bot development, testing, deployment, and review time.

A robust bot development framework helps in reducing development, testing, deployment, and review time by 30%

Categories
Digital Customer Experience

Personalizing the customer experience: The key to shaping the future of service providers

In today’s digital world, the success of every service provider in the connectedness industry depends on the experience it provides at every point of customer interaction. But the evolution of customer behaviors and expectations has made it difficult for the service providers to maintain customer loyalty.

According to Gartner, “Despite a mandate to create a differentiated and innovative customer experience (CX) strategy that will drive business growth, over 70% of CX leaders struggle to design projects that increase customer loyalty and achieve results”. Hence to overcome the paradigm shift in customer interactions, service providers need to reimagine customer experience by embracing the ongoing technological advances.

This whitepaper details how service providers can deliver a personalized CX across customer journeys. Further, it elaborates the three key imperatives to create a unique strategy and reimagine customer experience. Service providers must leverage the key imperatives with the power of the cloud, data science and AI to achieve digital transformation and customer delight.

Fig.Reimagining CX with 3 key imperatives


To overcome the paradigm shift in customer interactions, service providers need to reimagine customer experience by embracing the ongoing technological advances.

    Authors:
  • Sarit Bose – Sr. Director – Cloud, AI/ML & Data Services, Prodapt
  • Satish Billakota – VP – Cloud Services, Prodapt
  • Priyankaa A – Analyst, Strategic Insights, Prodapt
Categories
Operational Excellence

Improving the efficiency of your Field Service Workforce

Leverage machine learning to eliminate blind dispatches and improve the first-time fix rate (FTFR)

Field Technicians are the face of your service organization, and it is imperative to equip them with the right tools and knowledge to handle any field challenges. With efficient management and empowerment of technicians, your organization can deliver fast, effective, and efficient services to customers.

A business should strike a balance between the speed and accuracy of on-site customer requests to increase the productivity of technicians and improve customer satisfaction. But, in reality, technicians are frequently not able to deal with customer problems on time and are forced to make multiple trips to the client location due to process inefficiencies. Thus, instead of servicing new customers or optimizing current customer relationships, technicians invest valuable time and resources in non-revenue-generating activities.

Today, 70% of field technicians visit sites without prior information about the nature of the problem, issue location and solution recommendation. It leads to repeated dispatches, longer resolution time and high customer churn.

Going digital is the cornerstone of success for a modern services organization. Adopt the ‘AI-Powered Field Service Framework’ to optimize field services and increase technician productivity. The framework encompasses three vital components to achieve a higher First Time Fix Rate (FTFR) and reduce Mean Time to Resolve (MTTR):

  • Fault Location Classifier– Predicts the fault location and sends email/SMS notification via mobile app to technicians
  • Recommendation Engine– Suggests guided actions and next best resolution steps to improve technicians’ efficiency
  • Technician Dashboard– Provides a one-stop view of all dispatches and actionable insights to technicians


70% of field technicians visit the sites without prior information about the problem leading to repeated dispatches, longer resolution time and high customer churn.

Categories
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.

Categories
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.