Break IT Down: Five Ways Cognitive Delivery Insights Can Resolve IT Incidents
IT is the underpinning of an enterprise’s delivery of digital services and empowers organizations to stand above the competition. But the flip side of digital delivery is the threat of disruption — businesses can’t afford to stumble on unexpected interruptions that diminish quality of service.
With the stakes higher than ever, Cognitive Delivery Insights (CDI) ensures your IT infrastructure doesn’t miss a beat by using automation and artificial intelligence to address the many incidents that result from the complex integration of on-site systems and cloud services that drive business today.
CDI allows enterprises to proactively eliminate incidents. It links the data from a multitude of sources and automatically applies a range of insights and intelligence to provide early warnings, eliminate system noise, and learn how these data sources work together. By harnessing the power of automation, CDI helps enterprises seamlessly transition from a people-led, technology-assisted IT approach to a technology-led, people-assisted strategy. With CDI, your IT infrastructure can run and learn from itself.
If your enterprise is on the fence about automating its IT infrastructure, consider these five ways that CDI can resolve incidents in a complex IT environment.
1. Improve Quality of Service
Insights can vary wildly when practitioners, assisted by technology, lead IT. The IT staff must review a seemingly endless stream of data from disparate sources to determine which routine events need remediation. Forget trying to get to the bottom of underlying issues — a stressed IT team only has the capacity to prevent bottlenecks from obvious incidents.
CDI coalesces and standardizes various sources of data across domains and accounts to provide a framework for the seamless addition of more data sources, including the data center, cloud applications, and end-point devices such as laptops, smartphones, and printers. The cognitive analysis of CDI prioritizes incidents to allow IT to work down the list to tackle core events that threaten to rear their disruptive heads.
2. Analyze Structured and Unstructured Data
CDI’s natural-language processing capabilities and machine-learning algorithms work in tandem to interpret and analyze the many types of unstructured data that underlie IT. Incident tickets and other unstructured sources can all be understood by natural language.
While practitioner-led IT might miss patterns within unstructured data, the machine-learning algorithms of CDI mine data and discover patterns associated with various incident symptoms, major incident root cause analysis, and opportunities for service delivery improvement.
3. Gain Standardized Visibility
With cognitive insight, enterprises can source, analyze, and interpret all types of data. Data is standardized into a universal viewpoint that offers direct and contextual signals, allowing IT to make changes with confidence.
Backed by this informed insight, IT can tackle quality initiatives and continuous service improvement activities in areas without mature industry standards and agreed-upon quality metrics. For example, analytics performed on many accounts can inform which ones would be better served with learnings from a variety of automated functions.
4. Automate Improvement
CDI upends the traditional means of manual IT oversight, which is anything but consistent. The automated patterns of CDI constantly work to improve the quality of IT delivery. By regularly making even small changes, automation can significantly decrease the number of severe incidents.
Because CDI generates insights prompting corrective responses, sources of trouble can be easily spotted and removed. For example, insights can reveal that the threshold to provision a new disc is set too low, which affects storage and eventually life cycle value. Not only will CDI detect and solve this issue, but it will then always recognize that new threshold. This simplifies IT management. IT can use new insights to discern which changes to make and which ones to avoid.
5. Link Changes to Solve Incidents
As CDI learns the nature of your infrastructure, it intuitively navigates domains and continuously links incidents, change requests, and end-point device data. It associates incidents and change requests with corresponding servers and connects change requests with incidents. It then links incidents caused by a change to the change that caused the incident. If it seems like a growing autonomous loop, it is.
High-level analytics can outline patterns where the same types of incidents always require the same types of change requests. Automation creates a map to show the best paths for remediation. It can address stubborn, recurring incidents and create new thresholds to prevent them from happening again.
There’s no denying the power of data. It drives business by providing insight into how to solve problems, increase efficiencies, and serve customers. Enterprises need to be agile and always-on to stay ahead. With data-informed insights on your IT services, your enterprise can unleash a new way of doing business.
Learn more about CDI and IBM Services Platform with Watson.
John R. Hoffman, Dynamic Automation/Cognitive Delivery Insights Advocate at IBM, contributed to this article.