Whether AIOps is about insight or automation often is unclear, especially because the stated goal of AIOps to gain insights that lead to automated action, supervised or unsupervised by humans. Ericsson, for example, talking about applied artificial intelligence in communications networks, prefers the “automation” label.
In large part, that might reflect the particular challenges of the connectivity service provider industry, where many revenue and business problems grow from unhappy customers and poor customer experience (dropped calls, no coverage, slow internet speeds, poor connection quality).
“Previous Ericsson research shows that almost 50 percent of consumer network perception is based on personal experiences of the network, indicating the huge importance of network quality as the key to customer satisfaction,” Ericsson says.
Customer satisfaction, in turn, is believed to be causally related to word of mouth referrals, prospect perceptions of quality and value, customer churn, customer acquisition and therefore revenue, profits and market share.
“Whether customers give you US$2 or $20 ARPU, if you do not provide the quality they expect, they will churn,” says Vicente Cotino Director of Network Operation Maintenance, Orange Spain.
To be sure, network performance is not the only driver of satisfaction. “At least one-third of the total NPS (net promoter score, a measure of customer willingness to recommend a product or service to others) score is derived from network performance.”
Of the service providers surveyed by Ericsson, 80 percent use NPS as a key metric in operations. Also, several service providers indicate that 40 percent to 60 percent of operations key performance indicators are business-related.
Service providers, in other words, must do many things right, beyond ensuring that the network works as it is supposed to work. What is hard to untangle is the percentage of benefit that AIOps might provide, and whether it is automating changes or detecting issues that is “more important.”
Clearly the two are related. Action is not possible without insight; nor is insight useful unless changes can be made fast.
In surveys undertaken by Ericsson, 80 percent of respondents say automation is key for the cost and customer experience. About 90 percent of operations personnel say AI is important in protecting customer experience.
As always, methodology matters. I do not know how the questions were framed. It is not clear how the responses might have been different if poll takers were asked about whether better network and consumer behavior insight and prediction would protect customer experience.
But Ericsson frames the issue as one of “automation.” That might simply be a reflection of our general confusion about effectiveness and efficiency. People often speak about the importance of efficiency, which might be expressed as getting work done faster, with fewer people, at less cost or with fewer mistakes and rework.
Less common are evaluations of effectiveness, which might be expressed as “doing the right things” to produce value or desired outcomes. A traditional way of illustrating the difference is to note that an organization gains little to nothing by automating things that should not be done.
In principle, AIOps as applied to a communications network requires automated insight to produce proactive network responses. So far, we seem to have gotten better at insight, while IT managers still debate the value of unsupervised action by AI-driven systems to correct and modify network operations.
Put simply, “nobody trusts the system to behave autonomously” at the moment.
