Client Story: Artificial Intelligence Helps to Completely Restructure Business Processes in Just Over a Day
The current pandemic hit all companies equally unexpectedly. Like all others, Elisa Eesti AS had to react fast in order to enable nearly a thousand employees to work remotely. At that, the company had to continue all of its business processes without making any concessions to its customer support or service quality.
It has taken the past ten years of continuous work to perfect these business processes. However, because of the crisis, we had to turn everything upside down in a mere day and a half. Without the help of artificial intelligence, that would have been impossible.
Customer service robot Annika that has been developed in Estonia in cooperation with MindTitan has been working for Elisa already since 2017. Over time the robot has been getting more and more independent in servicing actual clients. When special conditions were applied due to the pandemic in the spring of 2020, we learned that Annika is not only a platform for service automation, but also a foundation for agile activities in providing our services.
From the client’s point of view, Elisa has operated as a fully traditional telecom company or any large service company for decades. Our service scopes are large – we make hundreds of thousands of contacts in each calendar month. A client may call Elisa or write to the company and we also call and write to our clients. We have a respectable e-channel and up until the middle of March it was possible to visit us at our service points in shopping centers. This set of service channels was a natural part of most of our processes and it enabled us to criss-cross between contact points. For example, a client would have been able to agree on the purchase of a product or a service on the phone, sign for it digitally, and then pick up the goods (e.g. their new phone) from a service point. Due to a large number of Elisa’s products and services, there’s a wide array of relevant combinations.
In retrospect, if Elisa would not have started to critically reason such service chains for the purpose of the robot back in 2017, we would have struggled to the point of chaos when our service points had to close due to the pandemic.
However, we didn’t struggle and that’s because we have Annika.
Annika is a service robot who cares very little about how things have been done until now. In order to assure that Annika would be able to serve each client fully, each product manager must describe every detail and every choice that may come up in the client process. Because of Annika, we have had to create a logic that would prescribe that, for example, a 65-inch TV can only be purchased so that it will be delivered by a courier, independent of which channel is used for the purchase itself. In the case of a tablet, on the other hand, the client may choose between various delivery options: courier, parcel terminal, or pick-up.
This example may seem trivial, but it is in fact essential. A 65-inch TV is not something you will simply sling across your shoulder and carry home in a tram, whereas one can do that with a tablet. However, for the system these two are both simply end-user appliances. This means that a large number of Elisa’s current service situations have been described for Annika in a way that focuses on the client experience. Of course, it may be argued that building services around the client does not necessarily need a robot, but would we have simply created a spreadsheet for this?
Anyone who has come to contact with a large service company knows that is highly unlikely. However, over the course of the past three years, Annika has put us in a situation where we have had to do that and build a completely new service process logic. This has mainly been our product managers’ effort. Either way, as the decision was made on the morning of March 16 that all Elisa service points are to be closed, we only needed a few minutes to identify processes where service points are of critical importance and to start redesigning these. Yes, we needed just over a day to actually complete the task. That was because we knew exactly what needs to be done and that saved us months of work.
All our service point employees were able to start work from Tuesday morning onwards side by side with Annika. The pandemic did not lessen the clients’ need for our services and in a situation where a service robot is able to independently satisfy the need of each fifth customer, we needed our service staff to be able to work as well.
Our staff needed a few days to get used to the new situation, but by today we are working smoothly together with Annika. In the course of this new practice, we have managed to collect highly useful training materials for Annika, that will enable us to learn and improve even more.
This means that our service staff will be freed of the tasks that are boring for humans and gives them the opportunity to spend more time on clients whose issues need more consideration and human interaction.
We are grateful to all clients who have been very patient with us at these tremulous times. We also send thanks on behalf of Annika to everyone who has been happy to have her on board. As for other large service companies – we can only recommend automating or robotizing processes – the sooner, the better. No matter whether the implementation of AI is caused by a positive or a negative change (or, indeed, a crisis), it is a decision that will help to gear up considerably and succeed also in the toughest of times.
Written by Mailiis Ploomann, Head of Telecom Services at Elisa Eesti AS.
Read more about AI solutions implemented in Elisa from our case study.
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Kristjan Jansons
Co-founder, CEO
Kristjan has been studying and working on machine learning projects for more than 7 years.
After acquiring a Master’s Degree in Computer Science and Machine Learning, he started working at Milrem Robotics as the Team Lead for Autonomous Vehicles, helping to build self-driving vehicles.
Kristjan also has experience in building intelligent systems for data centers, robots and electric formulas; also with computer vision and image recognition. He is especially fascinated by how people from different industries combine their knowledge with data science, arrive at new insights and help to accelerate innovation.