Insights 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.

Insights 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.

Insights 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.

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

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.