A significant network outage by mobile operator Three has been ongoing for the last 12+ hours. This has affected voice, data and text usage and has been reported right across the UK. Three network have a 12% market share in the UK mobile network market according to Statista.com, implying well over 6 million people have been impacted.
The website Downdetector.co.uk has been monitoring the situation and at its peak received over 9,000 reports of failure at 8am this morning, compared with 22 reports of failure at noon yesterday. The biggest impacted areas include Manchester and London. Initially, Three made light of the situation by joking that upgrades by O2, a rival network, were the cause of the downtime. They tweeted: "Oi, did you unplug our network so you could plug in your 5G? not cool guys." However, this was followed by silence as they scrambled to fix the network problems. Finally at 7am this morning an official statement by Three read: "We are currently looking into an issue with our network."
Why does this matter? Well at CyberCube we analyse and model scenarios based on technological dependencies that could create a "single point of failure" and lead to a systemic impact. This type of event is not without precedent. In December 2018, O2 experienced an outage that lasted most of a day. It offered 10% compensation to pay-as-you-go customers and equivalent credit to monthly users, as well as dealing with specific separate compensation for knock-on effects. This proved an expensive incident for the company.
It's too early to tell the extent of the Three outage (at the time of writing there is still a notice on the company's website apologizing to customers) but it gives an insight into the potential significant economic (and insurance) impacts of this type of event. Indeed, one of our scenarios contemplates a cell phone network outage for 24 hours as a result of a malicious attack. It is not clear what the cause of the "technical difficulties" are, but events like today remind us that systems we rely on entirely are not flawless and planning ahead and modelling scenarios help us to measure these outcomes.