Category: Insights

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Legacy infrastructure and outdated processes can hinder an organization’s ability to compete.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
Categories
Product Engineering

Deliver high-quality entertainment services at high speed and with flawless quality

Automate the end-to-end compatibility testing and rollout steps to deliver a seamless viewing experience across multiple digital platforms and form factors

A series of technological advancements has completely changed the way people consume video content. Compared to earlier days, when a television set was the primary source to consume videos, today’s consumers have many other options – smart TV, streaming box/stick, gaming consoles, DVR, set-top box, tablet, computer, mobile, etc. A recent ComScore OTT state report clearly shows the growing penetration of different digital devices among U.S households.


To deliver a seamless viewing experience, service providers need to ensure video compatibility across a broad range of device types, operating systems, browsers, and network types.

The end-users now have the flexibility to watch their preferred videos on any digital platform of their choice without being much concerned about the supporting operating systems, browsers, and network connectivity.

But if we look from the lens of service providers, delivering video service faster and with high quality has become much more complicated. It requires them to ensure feature compatibility with a broad range of device types with different operating systems, browsers, and network connectivity. This requires a humongous amount of testing in the background. And as digital-savvy users expect feature updates at lightning speed, service providers cannot afford to spend much time testing and rolling out services.

This mandates service providers to technically upgrade their way of working, the testing process, and existing release platforms.

Categories
Digital Customer Experience

Customer experience-centric contact centers- an evolution in digital age

Leveraging digital-first model and Artificial Intelligence technology to deliver a superior customer experience

In today’s fast-paced and competitive world, just having satisfied customers isn’t good enough. There is a dire need for businesses to innovate digitally to enhance customer service. But Customer Experience (CX) is beyond good service. CX is your customers holistic perception of the experience that they get from every touchpoint of your business or brand.

Having said this, most enterprises still rely on traditional models that are reactive, slow, complex, and disconnected. Due to this, they hold low Net Promoter Scores (NPS). And their inability to keep pace with the technological advancements in the contact centers is a primary reason for this.

Most businesses have been struggling with high call volumes and costs. As the number of calls rises, it becomes difficult for agents to handle customer queries quickly. Due to the long wait-time and the unavailability of agents, businesses tussle to provide a seamless and more intuitive customer experience. So diverse and vast are the communication systems and channels of today’s multifaceted contact center—that being ‘Connected’ demands a modernized and transformed customer engagement ecosystem.


A digitalized contact center can help you improve the Net Promoter Score (NPS), reduce call volumes, and save OpEx.

The good news is that realistic solutions exist to overcome this problem. Use enablers and tools like ‘360-degree view’ and ‘AI engine’ to help the agents with a holistic view of systems, provide quick diagnostics and intelligent recommendations. An ‘AI-based conversational engine’ helps customers with an intuitive self-service experience.

A digitalized contact center can help you improve the Net Promoter Score (NPS), reduce call volume, and save OPEX. It empowers your customers to make quick decisions using the multiple self-service options available at their disposal, hence diminishing their need for an agent. It marks the future of the digital-first age.

Categories
Digital Customer Experience

Bridging the digital gap

Implement a “Digital Enablement Layer” to blanket the back-end complexities and meet the digital goals

Most service providers aim to deliver digital capabilities to customers, but the legacy systems have been a hurdle to their digital transformation efforts. According to one McKinsey research, 70% of digital transformation projects don’t reach their stated goals. TM Forum Digital Transformer Tracker 2020 report states that many telcos that have started the transformation expressed frustration borne out of hitting roadblocks or not achieving the expected results.

However, these roadblocks must not deter the service providers from achieving their digital goals. Another McKinsey research shows that service providers with robust digital capabilities boast a profit margin of 43 percent, compared to their counterparts whose margins hover around 21 percent.

A Digital Enablement Layer is an optimal approach to blanket the back-end complexities and achieve smooth transition/IT transformation without significantly affecting the digital needs of a business. Moreover, service providers can achieve the transformation within a reasonable budget & timeline.


A Digital Enablement Layer is an optimal approach to blanket the back-end complexities and achieve smooth IT transformation without significantly affecting the digital needs of a business.

Categories
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
Categories
Cloud

Explainable Machine Learning (ML) models demystified

Enable 5X transparency in AIOps, achieving a more reliable and accurate business outcome

Service providers in the connectedness vertical embrace Artificial Intelligence for IT Operations (AIOps) to transform their businesses, but the users are hesitant in entrusting their operations to a complexly driven platform that provides no clarity and visibility into its functionality. Due to the lack of transparency, service providers are concerned about making bad decisions based on AI recommendations and the liability of such decisions and actions.

In their quest for autonomous operations, service providers seek to be more proactive with predictive analytics, where the machines make most of the decisions and help engineers take preemptive actions. However, the engineers need to have complete visibility into the underlying logic used by the AIOps and the ability to validate if the outcome is reliable.

Figure1: Assisted Artificial Intelligence and Machine Learning Framework


To accelerate AI/ML model development with enhanced transparency, enterprises must switch from existing auto-machine learning to assisted AI/ML framework-based solutions.

Explainable Machine Learning (ML) models aim to solve this problem by explaining the logic of the AIOps solutions so that the users can easily understand the outcome. The model explains the application of the AI solution and its result to the users in a way that they can clearly understand, rely on, and trust the outcome. Explanation in the ML model can be viewed as a means to transforming a black-box AIOps into a glass-box AIOps, by precisely lifting the veil on its computing and logic.