Extract and Archive Contextual Information for IT Ops

Once your IT team has automated and curated business processes that have a defined set of triggers or processes that follow software-driven logic, you can start freeing up high-level resources. What’s the smartest way to redeploy them?

There are many directions you could go, but best practices suggest you ramp up the customer experience by iteratively improving the rest of your business processes.

Hiding in Plain Sight
McKinsey researchers in The Age of Analytics concluded that, “Data and analytics are changing the basis of competition. Leading companies are using their capabilities not only to improve their core operations but to launch entirely new business models. The network effects of digital platforms are creating a winner-take-most dynamic in some markets.”

They found that while leading firms are increasingly able to dominate their verticals by extracting value from their own business process data, too many of their competitors fall behind despite having their own form of competitive advantage hiding in plain sight — structured and unstructured data on issue reporting.

It’s easy to allow vast sums of potential value to go to waste due to data rot. There’s no question that data has a shelf life and once the underlying conditions of the recorded processes have changed, the associated data loses some or all of its inherent value.

Learning how to extract and archive contextual information about your business processes – using data that already exists within your network – is foundational for optimizing workflows and refining execution.

3 Business Process Insights
Properly analyzed contextual information related to business processes will deliver three essential insights:

• You’ll be able to gain a top-level view of how data flows through each process from the perspective of a business transaction.
• You’ll see commonalities across development modules and skip right to the solution.
• You’ll be able to answer stakeholders more accurately in less time the next time they ask complex questions.

The key to all that is “properly analyzed,” of course. Structured data is hard enough to analyze, but unstructured data tends to defy logic, both in the way it is normally collected and the way it tends to be stored. Unstructured sources of data such as application logs and customer interactions (in chat windows, on social, in email) are often just dumped into massive data lakes that SQL doesn’t know how to handle.

Even structured data around application events, such as managed issue objects, managed IT notifications, FYI communications, and customer notifications, are too frequently neglected. And yet these data sources contain performance data essential to successful optimization projects and excellence in execution.

Mapping Unstructured Data
This process begins by mapping unstructured data into a structured, searchable format. For example, application log details can be nested and indexed inside the managed issue or IT notifications that relate to the error messages. Along the same lines, customer conversations in chat should be directly linked to the accompanying issue or issues, and remediation insights can be gathered into a higher-level report for more productive cross-team collaborations.

Stakeholders look for status updates and business impacts.

When internal stakeholders get involved in the issue-reporting process or come to you with questions before generating a report, there is rarely sufficient time to dig for the answers they need.

In the bigger picture, internal and external stakeholders alike are most commonly looking for status updates and business impacts. This is where knowing exactly what the customer said, or knowing the exact state of the application pre-error, can make all the difference in the world. This is the level of insight that technical teams need to take immediate action instead of trying to triage issues against the clock as pressure mounts.

What Went Right, What Went Wrong
Ideally, your team would be able to centralize communications and share data across systems using a single interface. As you pull in unstructured data to issue resolution methodologies, you can add relevant context and interactively update all systems. That way engineers can continue to work inside their preferred tools, instead of toggling back and forth between systems, where messages and static information are likely to get lost. The engineers can then immediately go to work on improving system performance while sending off a more intelligent, comprehensive assessment of the situation back to the stakeholder.

Taking a second look at this information in context is vital to the practical understanding of what went right and what went wrong in the past. Bringing back all that prodigal data is the final step in transforming your organization into one that is both agile and consistent.

How xMatters Drives Data Forward
As events unfold during a service outage or deployment, the hand-off from tool to tool and ill-defined communication processes slow organizations down. With more than 200 built-in integrations and unlimited custom integrations, the xMatters toolchain communication platform relays data between systems while engaging the right people to resolve incidents. xMatters ensures that the appropriate individuals and groups for any situation are identified, notified, and taking action.

But alerting is just the beginning. To close the loop, xMatters manages and drives forward the underlying workflow from originating systems until issues are resolved and service is restored. xMatters automates and brings structure to communication to help enterprises proactively prevent outages, manage incidents, and keep the right people informed.

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