How to improve customer experience with intelligent operations
Traditionally, operations were viewed from a cost-efficiency perspective, but today service providers are introducing more and more customer-centric KPIs. But how can operations continue to improve customer experience, while reducing costs? Intelligent business process operations could be the answer.
Imagine a typical day in an operations center: the back-office agent receives a customer complaint because they haven’t been able to upgrade to a new data plan. After being unable to rectify the seemingly complex issue, the contact center agent sent it to the back office. On receiving the complaint, the agent:
- Opens several screens to fetch the customer’s information across all journeys
- After corelating the information, the issue is identified as inconsistent product definition between CRM, order management and activation
- The agent applies the workaround and raises an incident for a permanent fix
Sounds familiar – doesn’t it? Approximately 25 to 30 percent of OPEX can be attributed to people performing a series of manual tasks in the back office while negatively impacting customer experience.
Complex and manual business processes create long issue resolution times, high operating costs and revenue leakages
Most service providers have evolved with multiple generations of technologies across networks and IT. For a time, new IT systems were introduced to cater to new services introduction, resulting in multiple systems and associated processes. This has resulted in fragmented processes and complex integrations in the IT landscape which increase OPEX and negatively impact the customer experience.
The introduction of IoT and 5G-enabled use cases will make business operations even more complex. Our recent survey - Supercharging customer experience through AI and automation - revealed that eight out of 10 service providers expect new services to increase costs and operational complexity. With new services being launched at CAGR of 20-25% till 2025, business operations will also become more complex, especially when it comes to order fulfillment, activation, partner onboarding and settlements.
Now, the challenge is to improve customer experience while remaining efficient.
How to improve customer experience without compromising efficiency
The three key components for improving customer experience in business process operations are: business process re-engineering, automation through Robotic Process Automation (RPA) and Run Book Automation (RBA) and improved intelligence through AI/ML. Let’s take a closer look at each one:
Business process re-engineering
The automation journey starts with assessing and re-engineering the processes based on leading global practices. Inefficiencies and repetitive manual steps identified in processes help determine automation potential, which can then be implemented using automation technologies. The fragmented sub-processes can also be identified, with the complete end-to-end process being orchestrated through a Business Process Management System (BPMS).
Automation through Robotic Process Automation and Run Book Automation
RPA and RBA technologies allow “software robots” to mimic human actions like mouse and keyboard actions or reading the screen output. These automations can then be orchestrated by BPMS to make the entire process single-touch and without any manual effort. For example, a South East Asian service provider implemented one-touch billing by automating the billing process. The billing process consisted of pre-billing activities, billing activities and the post-billing activities and had ~50 sub-processes. The system automated and orchestrated these sub-processes so that no dedicated agent is required. This not only improved the costs but also reduced the bill cycle time from four days to less than a day.
Reaching next level operations intelligence with AI and machine learning
The next breakthrough comes with using advanced data analytics, AI and machine learning (ML). The AI and ML-based solutions have the ability to collect and correlate data from multiple IT layers and systems and generate insights on the process performance. For example, after implementing AI-driven automation to improve the performance of order management processes, the order failure rates decreased by 90 percent for a North American operator. The AI system pinpointed anomalies in order flow by collecting and processing data from multiple IT layers – including hardware, databases, applications and multiple IT systems – service bus, order management, activation, charging, billing, and product catalog. The scalable and replicable AI framework analyzed root cause to predict and prevent order fallouts.
Starting the journey towards intelligent operations
The journey towards intelligent operations requires re-engineering business processes, building automation bots and implementing AI/ML models. These models need to be built, trained and continuously improved by expert staff with access to quality data sets. At Ericsson, we’re helping our customers on this journey by developing and continuously enhancing automation and AI/ML models using varied data sets. Our research and development team is continuously identifying and developing new RPA, RBA bots and AI/ML models and creating a repository of these use cases.
With this repository of AI/ML and automation use cases, Ericsson Automated Business Service Management can potentially reduce your OPEX by 25-30 percent and customer complaints by up to 30 percent. In the future, the scale of operations will be too huge to manage manually!
Learn more about Ericsson's approach
Would you like to know more about how Ericsson can help communication service providers to improve customer experience? Read more about Ericsson Automated Business Service Management.