On a verge of Paradigm Change
I joined Elisa Automate after spending 17 years in an international RAN (Radio Access Network) consulting company. During those years, I got firsthand experience on how operators in different corners of the world operate and optimise their networks. It took me by surprise to see how far the Finnish mobile network operator Elisa had got in terms of innovation and automation compared to other operators I have worked with.
I was seeking a place that shared my vision for digital transformation, and at Elisa Automate this has been embraced and put into practice. Elisa’s way of working is to automate all tasks that can be automated. Together with Elisa Automate, this change is getting fast-paced. During the last years, we have for example:
- Automated Network Operations Center functions (zero person NOC)
- Majority of customer impacting faults are predicted by machine learning algorithms before they occur and can be fixed by automation or field workers before customers notice service degradation.
- Elisa SON (Self-Organising Network) solution makes 4 million checks and 4000+ RAN optimisation actions daily without human intervention.
- Rollout and commissioning processes has been automated to maximal extent, Radio planners can concentrate in radio planning issues and in implementing further automation.
- Automated commissioning testing application guarantees that installation issues such as crossed feeders will be found before on-site installation mechanics leave the site
What Elisa has achieved so far is astonishing, but it didn’t happen by itself. I believe continuous learning is key for success for any company, that’s the case for Elisa Automate as well. And here we all have the chance to develop. I’ve also been participating machine learning courses sponsored by Elisa and have been able to apply the learnings directly in creating predictive algorithms addressing items related to radio network planning and dimensioning. Learning and understanding what’s behind the hype of artificial intelligence and machine learning, what it brings to operating and optimising networks, and the kind of analytic insights you can get through big data has been inspiring.
It’s an interesting time to be working in the field of radio optimisation. Growing computing capacity enables real time monitoring of user experience for all users. Combining capabilities brought by higher computing capacity with automated optimisation algorithms will result in paradigm change in radio network optimisation. Instead of optimising network performance for the average user, operators can soon optimise user experience for each and every individual user. This is quite a leap forward and something I’m excited to be a part of here at Elisa Automate.