The most important take-aways from this case are that the average handle time per interaction was brought down, the number of applications the agents had to use during an interaction was also brought down, and the number of clicks which had to be made by the agents during an interaction were also brought massively down.
Who is the customer?
The customer is one of the biggest retail companies in the Nordics, dealing with a very high number of calls per year, around 1.600.000 interactions divided between phone, chat and email. And with more than 370 customer service agents working there.
What was the challenge the customer had?
One of the biggest challenges was that interactions was steadily increasing and the handling time for some of the complexed interactions was too long and creating long Q-time for the customers and the expected service level which stated that 80% of the calls should be completed within 60 seconds was not reachable at all.
One of the bottlenecks for not reaching their goals was the numbers of applications used, in some cases the agent needed to use over 12 different applications to complete one single ticket. They needed to solve this without increasing the number of agents.
How did we solve that challenge?
We went in and did a discovery for 3 days, to asses the situation. We sat down with agents, team leaders and internal IT teams to map processes and see where we could make an impact, with the lowest amount of effort and time, and decrease the average handle time (AHT), and free up the agents’ time, so they could interact with customers instead of navigating applications and doing manual and mundane tasks over and over in an endless circle.
We found 10 different processes that had great potential. Together with the customer we narrowed that list down to 3 processes with highest potential compared to delivery time.
We implemented a full RPA solution to perform and complete many complexed but routine back office tasks. This resulted in all agents were free to handle decision requiring interactions more efficiently and with more accurate, which then resulted in a higher customer and agent satisfaction.
Next step was to create 2 different processes with RDA. Here we connected some of the most and widely used applications and created an interface for the agents where we took down the number of clicks and navigations from 67 clicks and 10 different applications to 4 clicks and 3 used application per interaction, creating a lowered AHT of 2.5 minutes.
We were also a part of creating an internal center of excellence and trained agents to enable them to maintain the RPA solution, and program new features and processes themselves.
Today the team has over 15 RPA robots up and running day and nights taking care of manual repetitive tasks and creating a much better and effortless customer experience.