Category: Insights

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IT Agility

Site reliability engineering for the connected world: Revolutionize your IT Ops

Modern business cannot afford the conflict between the urgent need to manage a dynamic situation and the strategic need to build for the future.

In today’s new-age markets, every major business is tech driven and, data is its backbone. Its IT success depends on its ability to develop, test, and deploy features (or products if you’re a pure tech player) at scale and at a faster rate than competitors. The speed at which changes roll out should match customer expectations, else you risk irrelevance.

For example, a business rolling out new products must contend with the constant tussle between the development side, which writes software, and those who run it. DevOps principles seem to alleviate the situation, as they spell out a way to harmonize the two silos. Perhaps your company has crossed this bridge.

But this perfect picture may not match your reality. Incidents and downtime may undermine the DevOps effort, forcing resources to manage them. A meltdown of IT Operations (ITOps) can bring development to a dramatic halt; or many small ones can bleed your operations to a state of stagnation.

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SRE effectively ends the age-old battle between development and operations.

The answer is Site Reliability Engineering (SRE) principles, which is a prescriptive way of implementing DevOps. SRE creates a playbook that streamlines ITOps and shields people from critical situations, while those are being handled.

Development teams can focus on feature development instead of achieving and maintaining service levels in the form of incidents and uptimes, thereby improving the reliability of the business-critical operation.

Categories
Cloud

Breaking the barrier between Machine Learning (ML) prototype and production

Leverage MLOps to scale and realize the ML use cases faster

Most businesses in the ‘Connectedness’ industry have started embracing Machine Learning (ML) technology to provide effective customer service to the customers. However, managing these ML projects and putting them into action is challenging. For service providers who strive to move beyond ideation and embed ML into their business processes, Machine Learning Operations (MLOps) will be a game-changer. According to Gartner, “Launching ML pilots is deceptively easy but deploying them into production is notoriously challenging”. Listed below are a few challenges that make it hard to scale ML initiatives.

  • Lack of automated mechanism to address the change request in ML pipeline
  • Inefficient ways of retraining and deploying the ML models to accommodate the data changes
  • Lack of in-depth visibility of the model’s performance

Service providers need to implement the MLOps approach to overcome these challenges, which automates and monitors the entire machine learning life cycle. It enables consistent improvement in the baseline accuracy and accelerates the production time of ML models.


Launching ML pilots is deceptively easy but deploying them into production is notoriously challenging.

The successful implementation of the MLOps approach requires the right set of enablers such as de-coupled architecture, standard change management process, automated retraining and deployment of ML models, and continuous monitoring.

Categories
Software Intensive Networks

Move Broadband rollout to the fast lane, with enhanced quality

Leverage Unified Automation Testing Framework that integrates various tools and systems to fuel quick and error-free product releases

While the need for speed is a famous mantra across industries, businesses in the connectedness vertical often struggle with longer roll-out times owing to evolving network technologies and frequent Customer Premises Equipment (CPE) upgrades. To generate new revenue streams, service providers need to accelerate their Broadband Residential Gateway Rollout (routers, modems, switches etc.) and at the same time keep their capital expenditures minimal.

Traditional testing methods with multiple testing tools and automation frameworks are often unable to meet the desired roll-out timelines, causing complexities and dependency on experts. Moreover, service providers also experience the perennial challenge of repetitive testing to cover all scenarios and features, which is tedious and might lead to human errors.

Service providers, today, must look beyond manual, monotonous, and vendor-dependent testing methods. Adopt a Unified Automation Testing Framework to enhance your testing methodology by seamlessly integrating multiple test tools and frameworks. This framework can:

  • Auto-learn the device configuration
  • Provide a customizable solution to accelerate the development time
  • Seamlessly integrate with the service provider’s test environments, test tools, and management systems for smooth execution of all test cases


While the need for speed is a famous mantra across industries, businesses in the connectedness vertical often struggle with longer rollout times owing to evolving network technologies and frequent Customer Premises Equipment (CPE) upgrades.

By implementing this framework, service providers can proactively solve broadband performance issues, improve customer experience, and accelerate the Broadband Residential Gateway Rollout Time.

Categories
Digital Customer Experience

Experience can make a huge difference – Get it right

Mastering the implementation of digital capabilities is the key to overcome experience disconnect

Would customers pay more for the delightful and seamless experience their favorite brand offers? In the coming years, most of them certainly will. Research shows that 86% of buyers are willing to pay more for a great experience. Experience has become a key brand differentiator, overtaking the price and product. Yet, many organizations may not grab this opportunity completely – as their customers may experience disconnect in the digital world.

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Getting the experience right requires implementing the right digital capabilities that consistently delight customers in every interaction.

The perception of a brand is built upon accumulated consistent interactions across multiple digital touchpoints. Getting the experience right requires an organization to implement the right digital capabilities that consistently delight their customers in every interaction. But as a matter of fact, most digital initiatives fail to reach their stated goals. One major reason is the gap between strategy formulation and strategy implementation. Incorrect implementation choices taken at the beginning of the project can make the organization rigid and unadaptable to deliver a seamless experience.

What can businesses do to make first-time right digital implementation choices? Critically evaluate the maturity of existing digital capabilities and plan the transition steps more methodically. Before starting the digital implementation journey, businesses must get the right answers to “Where to start?”, “How to start?”, and “How to get a head start?”.

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.

Categories
Cloud

To treat, or not to treat: Increase marketing ROI with targeted campaigns, through uplift modelling

While running direct marketing campaigns, businesses must map the right customers to a given promotional offer to maximize the campaign effect. For example, which customers should receive a discount on subscription, to minimize the business overall churn rate.

Different methods can be used to identify the right set of target customers for campaigns, such as, manual spreadsheet-based statistical modelling and outcome modelling. These methods, however, have some limitations like:

  • Randomized and inaccurate list of target customers
  • Lack of granular details such as which customers are most likely to respond to marketing campaigns
  • Low marketing ROI due to poor response rate from customers

Machine Learning (ML)-based uplift modelling is a promising approach to overcome the above limitations. It allows businesses to categorize customers as the ones who are likely to respond positively to a campaign and those who would remain neutral or even react negatively.

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An uplift model increases marketing ROI by determining the right target customers.

A well-executed uplift model would improve a business marketing efficiency and help in driving higher incremental revenue. The successful implementation of the model requires the right set of enablers such as raw data acquisition, feature engineering, and AI/ML model development.

Categories
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.
Categories
IT Agility

Modernize to move at speed

A cloud-native order management can boost speed, scale, and operational efficiency

Fulfilling customer orders timely and accurately has always been critical for businesses to succeed. But achieving this has become a lot harder with rising customer expectations in the digital era. Today’s consumers seek instant gratification. They want new digital services enabled instantly on the device of their choice, on any platform over the phone or online – all of these with as little friction as possible.

So, what stops businesses from exceeding their customer expectations while fulfilling orders? Why are there high order fallouts and failure to meet the promised due date of order activation? Why are the businesses not able to customize and deliver new product offerings quickly as per the varied needs of their customer? Even if they do so, why does it become so costly and time-consuming?

The core problem lies within the legacy order management application that has grown like a huge elephant over time – making the entire ecosystem more complex and rigid to process new orders. It stifles innovation and drives up costs. To overcome this, leading businesses have started their journey to transform legacy order management.


Cloud-native digital platform for order management boosts service providers’ speed, scale, and operational efficiency, enabling them to thrive in the digital era.

A cloud-native digital platform is an ideal transformation approach that can boost speed, scale, and operational efficiency. But that is easier said than done. Businesses need to re-construct the application ground up, which means the entire order management stack should be rewritten from scratch, including key applications like order capture, order execution, product catalog, asset management, user documentation, notifications, and more.

Categories
Cloud

Observability: Looking beyond traditional monitoring

Gain critical insights into the performance of today’s complex cloud-native environments​

As businesses transition towards multi-layered microservices architecture and cloud-native applications, they often struggle to gain granularity with the traditional monitoring tools. In the traditional method, teams use separate tools to monitor the logs, metrics, events, and performance, hindering unified analysis. Monitoring tools do not give the option to drill down and correlate issues between infrastructure, application performance, and user behavior. Teams often use logs for debugging and performance optimization, which becomes very time-consuming. Static dashboards with human-generated thresholds do not scale or self-adjust to the cloud environment. As thousands of cloud-native services are deployed on a single virtual machine at any given time, monitoring has become cumbersome. Further, conventional monitoring relies on alerting only known problem scenarios. There is no visibility into the unknown-unknowns – unique issues that have never occurred in the past and cannot be discovered via dashboards.​

Businesses need to make their digital business observable such that it is easier to understand, control, and fix.  Hence, they must​ look beyond traditional monitoring. With observability, businesses can gain critical insights into complex cloud-native environments​.​ Observability enables proactive and faster discovery and fixing of problems, providing deeper visibility about issues and what may have caused them.


With observability, businesses can gain critical insights into complex cloud-native environments​.​

Categories
Software Intensive Networks

Building high-speed internet for seamless digital experiences

Leverage Zero-touch Service Assurance Framework to proactively detect and auto resolve broadband connectivity issues

‘Being Connected’ is a human necessity. Today, the availability of high-speed internet plays a crucial role in accelerating connectedness in our lives. People from across the length and breadth of the globe stand to benefit personally and professionally from a reliable internet connection.

As a result, there is explosive growth in the number of internet users, which is bound to increase in the future.

Speeds that were good enough yesterday are insufficient to support the requirements of today. Businesses, thus need to step up their game and provide a rich broadband service. By failing to do so, they will not be able to catch up with customers’ evolving expectations, causing frustration and dissatisfaction. Customers may also switch to another business offering broadband services with better quality and speed.

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.


High-speed broadband supported by the ‘Zero-touch Service Assurance’ framework accelerates connectedness in our lives.

The 4 magic components of the ‘Zero-touch Service Assurance’ framework are

  1. Intelligent Insights Engine- Monitors the customer’s speed data on an hourly basis to detect any speed issues
  2. Diagnostic Engine- Buckets the issues into different categories. Auto-tickets are created for issues that cannot be auto-resolved
  3. Auto Resolution Engine- Executes autonomous actions like modem reboot or port bounce to quickly fix the speed issues
  4. Dashboard- Provides a real-time view of highly impacted customers, remediation steps, performance, percentage improvement in speed, outages, current and historical issues