At the peak of the Covid-19 pandemic, customer service agents at Telekom Malaysia (TM) were dealing with an influx of customer requests while working remotely. They had to process the requests quickly to ensure a good experience for customers.
The good news was that the Malaysian telco had been investing in automation prior to the pandemic and swiftly automated the creation of customer tickets, so that the agents could attend to more requests and reduce waiting time.
That is just one example of how TM has successfully harnessed automation, not only to serve its customers more efficiently, but also to improve a slew of backend business processes, from processing invoices to payroll reconciliation and network monitoring.
At the heart of TM’s automation efforts is Robin, a robotic process automation (RPA) bot augmented with artificial intelligence capabilities that was named Telecommunications Project of The Year at the Computer Weekly Innovation Awards APAC 2022. The project demonstrated what organisations need to get right before they can scale up an automation project with clear business outcomes.
By the end of 2021, Robin had automated a total of 70 processes covering areas such as network technology, customer experience, finance, HR and procurement, saving more than 270,000 annual hours, equivalent to 91 full-time employees, and about $2m (8 million ringgit) in costs.
In payroll reconciliation, for instance, the HR team was able save more than 4,000 hours and improved their execution speed. Robin has also improved the accuracy in resolving errors in call data records by 90%. And while it took 3.5 hours to reconcile each record manually, Robin could do so in less than 20 minutes.
What makes the Robin project unique is its strong buy-in from TM employees who have been picking up new skills and taking on RPA projects on their own. Out of the 70 projects, 40 were undertaken by internal teams, including 11 RPA-certified staff. This has reduced the outsourcing cost equivalent to almost $640,000 (2.7 million ringgit) worth of professional services.
Read more about CW Innovation Awards APAC 2022
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To ensure success in its automation efforts, TM started with addressing people-related challenges as it knew that one of the biggest roadblocks was the fear that automation would take away jobs. As such, it put together a communications plan, highlighting the benefits that automation would bring to the work lives of TM employees.
“We created images of Robin as a friendly persona who is not only helping with mundane and repetitive work, but also creating more space for them to build capabilities,” said Azni Risa, chief information officer of TM. “By creating a safe environment for people to learn and change, employees and departments are eventually driving RPA adoption.”
The partnership between business and IT teams was also instrumental to the success of the project. TM’s IT department initially sponsored the costs of the first few RPA deployments for individual departments and worked with their teams to identify simple processes that could be automated.
When this was understood at the grassroots level, all divisions began proactively identifying their routine transactions and rule-based repetitive tasks – basically standard processes that require many people to manage.
“Our tactical strategy was to ‘think big, start small’,” said Risa. “We started creating use cases which were propagated throughout the company, so that all departments could see how RPA would benefit them, how it was a growth lever and helped improve customer experience. All of a sudden, everyone wanted to jump on the RPA bandwagon, and they were lining up to automate their processes and get rid of their mundane processes.”
To address the challenge of implementing RPA amid limitations with legacy systems, TM embraced the agile way of working to promote collaboration across different teams, and encourage testing and learning to manage uncertainties during the implementation process.
It also embraced DevOps governance, documenting policies and best practices for bot creators to follow to ensure the quality of automation codes. These included checklists that must be complied with before a bot goes live, with an average bot success rate of 98%.