Economic warning signs are flashing, and organisations of all sizes are balancing the need for fiscal discipline and efficiency while fighting to retain customers, when a single negative interaction can send them running to a competitor.
Business digital operations are more complex than ever, compounding the problem is that companies are still adapting to remote work and pandemic-driven digitisation. Our recent report confirms that delivery teams are facing increased pressures, unreasonable business demands, and higher rates of burnout.
Stretched and stressed digital operations teams lead to failures in service delivery and low customer satisfaction. But technology can provide the support to enable teams to move from reactive to proactive and reclaim their time from fire-fighting to building great customer experiences.
As the volume and velocity of IT and customer data increases, AIOps is now an essential capability to delivering great customer experiences. Consider one of the most vital areas, incident management: Warnings, changes, incipient and full-blown incident volumes have exploded. Tickets for routine activities are increasing 70% year-on-year. No wonder talent is burning out, and then walking out. Keeping great engineers and streamlining operations is vital to building operationally mature organisations that satisfy customers, and ideally, do more than merely survive. This is why organisations are looking to infuse technologies like AI and ML into their digital operations.
SIDEBAR: What is operational maturity?
Operational maturity describes how teams manage unplanned work and incident response. Organisations fall into one of five levels. Teams operating from a preventative stance have adopted event intelligence features in order to manage risks in advance. Teams stuck at ‘manual’ are still operating without inbound integrations or advanced configurations that support automation, and therefore are not well-placed to meet unexpected challenges.
From level one, organisations move from ‘reactive’ (has inbound integrations but not other configurations), ‘responsive’ (has schedules and multiple escalation levels), and ‘proactive’ (uses outbound integrations, service dependencies, change events, or response plays), before ultimately reaching the ‘preventative’ level.
Improving operational maturity is positively correlated with higher workday consistency, a more even distribution of work among team members, and more efficient response to incidents.
The role of AIOps in maturity
Automation-led AIOps can help transform processes from those riddled with inactionable incidents and unpredictability to well-defined, repeatable systems, with well-defined incidents and analytics leading to preventative measures and predictability. It consolidates and standardises data from sources including CI/CD, monitoring tools, ITSM, big data, security, etc., and can automate diagnostics or remediation based on those inputs. It strengthens IT processes and the staff managing the entire digital operations edifice.
It’s a particularly good time to use AIOps to regain control over fragmented incident response and remediation processes. In the right programme, AIOps will aid in balancing team workloads, enhancing job satisfaction and employee retention, all while fulfilling a primary objective of improving customer experience, impacting both revenue protection and cost management as these come into sharp focus.
AIOps can deliver improved outcomes as a foundational aspect of a well-managed IT operation. It gives air cover to teams, improving their speed and enhancing situational awareness by taking on the urgent work that interrupts the planned day. IT teams cannot move forward with their digital transformation initiatives with immediate break-fix work constantly interrupting them.
The promise of AIOps
Four areas that AIOps should focus on for immediate business benefit include:
- Automation: Do away with manual labour and escalations, reduce the duration of incidents, and standardise workflows. Automation should take on the rapid, routine, and critical tasks including diagnostics and remediation and staff should take on innovation, planning, and prevention tasks.
- Data analytics and insights: Ingest and understand all relevant data and use insights to power smarter operational and strategic decision-making.
- Event management: Data science and machine learning will improve focus by removing noise from signals and enable more effective event management.
- Incident response: Connected and properly orchestrated teams enable an intelligent and coordinated whole-enterprise response.
While every solution focuses on core measurements such as mean time to resolve (MTTR), the real promise of AIOps comes in delivering employee and customer-impacting metrics. Resolving incidents faster can be shown to improve other business outcomes such as reducing customer churn and improving experience.
Plan carefully for better AIOps-led outcomes
Best practices for improving outcomes include a seamless integration with the observability/monitoring tools in play, plus incident response processes. This allows IT teams to get the most from the tools they are used to, and integrates previously inaccessible data from platforms, infrastructures, and incidents without rip and replace.
It also requires collaboration between DevOps and Site Reliability Engineering (SRE) teams to support everyone from the operations team, customer service ops, to production and development. Only when looked at as a whole will the right changes build strong end-to-end processes leading to better business outcomes.
Machine learning algorithms are perfect for discovering opportunities to make workflows more efficient. Such automation-derived insights enable the organisation to adapt their hidden needs to their environment.
Start simple with automation. It’s crucial to listen to staff when they say how they use their tools so that AIOps are integrated to their working practices. The most ‘perfect’ IT operational efficiency and resilience means nothing if in reality staff can’t work with ease and simplicity in their daily roles. Leveraging automation for simple things such as diagnostics as a first step can enhance operations and support teams without introducing new risks.
Start soon to create a better-run business before the crunch
AIOps improves resilience in many more ways than mentioned here and can lead to better digital readiness, business innovation, and revenue growth. For this reason, AIOps may help organisations outperform their competitors and make good on their digital promises sooner rather than later, given the uncertainty from what is sure to be a testing economic challenge over the next few years.