Further, the more advanced the data and related AIOps algorithms, the more that can be detected, analyzed, and possibly auto-resolved before a human needs to do something. When fed with the best data, this model yields a NetworkOps workflow that reflects intelligent automation that is ‘telling’ network technicians what happened, what needs to be done and where (for those issues not already automatically remediated). In other words, when you adopt a proactive methodology for your network environment, there is only upside.

Figure 3: Intelligent Automation through Crowdsourcing + AIOps

The case for proactive service assurance

The confluence of intelligent automation and NetworkOps workflow not only results in better insight and actionability, but also a more consistent and proportional response from network operators on behalf of their organization and, in turn, the customers they serve. Here’s how:

Amplifies proactive vs. reactive handling: Identifying an acute problem before it becomes chronic and interrupts workflows nearly always results in a better outcome for everyone: internal resources, stakeholders, and customers alike.

Drives down the cost of credits paid out from missed SLAs. Customers expect you to meet the SLAs they’ve paid for. If you miss that target―in most cases just once―they not only begin to question your ability to deliver against them but also whether they made the right choice to partner with your organization in the first place.

Creates a less stressful work environment. Having NOC personnel plugged into your network, taking its pulse, and adapting quickly and uniformly to changes as required results in a less-anxious, less-pressurized workplace for them―and you.

Improves the customer experience. This is the goal of everything we do―whether we’re in the front office crunching numbers or sitting in the NOC and keeping an eye on our customers’ environments. If the customer knows they can depend on us, the rest typically falls into place.

To reiterate, as more proactive issues can be resolved prior to a service interruption, the number of reactive issues trends downward. This allows for controlled maintenance work that is meaningful while resulting in fewer outages, less overtime and improved customer satisfaction.

Looking forward: the future’s new operating model      

So, how will NetworkOps evolve over the next decade to improve the customer experience? Ultimately, this combination of crowdsourcing + AIOps will enable network operators to have at their disposal the best and most meaningful data, utilizing the best practices for resolving proactive and reactive troubles, as leveraged by their AIOps automation frameworks. The result gets human hands off the keyboard and human eyes off the glass—and preserves the integrity, quality, and reliability of the expected customer experience.

It's also likely to save the sanity of network operators everywhere.