Digital Customer Experience Insights

Intelligent automation – Combining RPA and AI to provide a delightful customer experience

Robotic process automation (RPA) in the Connectedness industry has mostly been leveraged for the automation of backend processes. But by integrating RPA with artificial intelligence (AI), service providers can expand its horizons to digital customer care initiatives. The implementation of an AI-enabled RPA platform would help service providers to deliver delightful customer experiences to millions of customers.

The following video insight shows how any service provider can integrate natural language processing, virtual assistants, and diagnostic tools with RPA solutions to provide digital omnichannel customer care. The benefits of intelligent automation include a 50-60% reduction in store visits, a 10-15% increase in NPS and cost savings in millions.

AI-enabled RPA platform will help service providers to deliver delightful customer experiences to millions of customers.

Original content- Video Insight: Providing delightful customer experience using AI-enabled Robotic Process Automation and digital care

IT Agility

Fix the broken dispatch process to improve field service

Spare location intelligence can enable efficient dispatch operations and reduce the issue resolution time by 45%

Most service providers are struggling with the rising cost of field service due to the increase in repeat dispatches and higher issue resolution time. It takes longer to repair faulty hardware, impacting the customer experience and leading to a higher churn probability. According to Forrester, 73% of customers consider time the most critical customer service point.

Spare parts information is critical to scheduling an efficient dispatch for repair activities. It is not only the right delivery of spare parts that matters but also the delivery should reach the right place at the right time. Getting this right, the first time is difficult as the current manual approach is error-prone and inefficient without any automation. With a wide gap between the availability of spare parts and onsite requirements, there is a high degree of unpredictability.

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

To provide an efficient dispatch, it is crucial to ensure the right spare parts are available and dispatched from the nearest warehouse location through the most optimized route. The Spare-Location Intelligence framework can enable service providers to get real-time spare availability across warehouse locations and the most optimized route to access them.

The Spare-Location Intelligence framework can enable service providers to get real-time spare availability across warehouse locations

IT Agility

Eliminating avoidable truck rolls to save costs and improve customer satisfaction

Leverage statistical analysis and service truck roll optimizer for better field service efficiency

Truck rolls are an integral part of field service operations. It refers to any situation in which a technician is dispatched to solve an issue. But often, a field technician is dispatched to a job that is temporary in nature or can be resolved in under five minutes with a quick fix. Situations like these have become a huge pain point for service organizations.

A peculiar challenge faced by most Service Providers is that 25% of the truck rolls in their fleet are deemed non-value-add (NVA) or avoidable, costing millions each year. The process of creating truck roll appointments and subsequent follow-up activities still involves a lot of manual work. The customer service representatives (CSRs) create work orders manually without thorough assessment, resulting in avoidable or non-value-added truck rolls.

Service Providers must adopt a proven approach to address truck roll inefficiency issues. Transform field service management processes using techniques like:

  • Service truck roll optimization– Filters the NVA truck rolls and updates the work logs in the CRM system. Only the work orders that do not meet the business filter criteria will result in truck rolls
  • Pareto principle and correlation analysis– Uses analytics to identify the main causes for NVA truck rolls

25% of the truck rolls in a service provider’s fleet are deemed non-value-add (NVA) or avoidable, thus costing millions each year.

Cloud Insights

Don’t let the infrastructure management cloud your mind

Implement Infrastructure as Code (IaC) to reduce provisioning time by 65%

IT infrastructures are generally imagined as big rooms with huge servers and systems connected with a web of wires. Provisioning of this infrastructure has always been a manual process for the service providers in the connectedness industry, which leads to a lot of accuracy and consistency issues. The advent of cloud computing helped in addressing most of these issues. However, the configuration consistency, manual scalability, and cost issues persisted. Also, deploying complex infrastructure solutions requires considerable effort from cloud architects. These efforts are neither easy to repeat nor modified in a single shot.

To overcome these challenges, service providers can implement a DevOps Infrastructure as Code (IaC) methodology, which helps in automating the manual, error-prone provisioning tasks. It allows service providers to define the final state infrastructure, application configurations, and scaling policies in a codified way. This, in turn, reduces the dependency on cloud architects and provisioning time significantly.

Infrastructure as Code (IaC) helps the service providers to define the cloud infrastructure, application configurations, and scaling policies in a codified way.


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​.​