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Why Incident Triage is a Key Element in Your MTTR

Yoram Pollack
BigPanda

One of the key performance indicators for IT Ops is MTTR (Mean-Time-To-Resolution). MTTR essentially measures the length of your incident management lifecycle: from detection; through assignment, triage and investigation; to remediation and resolution. IT Ops teams strive to shorten their incident management lifecycle and lower their MTTR, to meet their SLAs and maintain healthy infrastructures and services. But that's often easier said than done, with incident triage being a key factor in that challenge.


Why Incident Triage is Critical for Lowering MTTR

One of the main side effects of today's increasingly complex, hybrid and constantly changing IT environments is the proliferation of disparate ops teams, tools, apps and environments. This in turn leads to high volumes of IT incidents that lack full business context.

As a result, it has become increasingly difficult for first incident responders to triage incoming incidents: Without the ability to understand the incidents' severity based on their business priorities and their impact on services or customers, their routing information, and more — IT Ops teams often waste valuable time determining what to do next, and in doing so, lengthen the incident management lifecycle.

In essence, incident triage has grown to play a key role in determining MTTR in modern, hybrid environments.

Manual Incident Triage Can Be Painful

Because different applications and services have different impacts on customers, availability and revenue, when several incidents occur at the same time it is imperative for incident responders in IT Ops and NOC teams to identify the priority in which these incidents need to be dealt with, and how best to deal with each of them. For teams to be able to rapidly perform this triage, they need access to critical business context and business metrics:

■ The business severity of each incident

■ The services each of them impact

■ Whom to route them to

■ In which priority to do so

■ And other context based on the organization's relevant processes and services.

Without easy access to this information, the teams waste precious time tracking down relevant spreadsheets, runbooks, and other sources of tribal knowledge, as well as manually calculating the business metrics needed to help them understand the incidents' implications.

The more time that is spent on these manual steps, the longer the incident triage lasts.

And the longer that takes, the higher the probability that SLAs are violated, MTTR is kept high, and costs associated with high MTTR rapidly increase.

The solution? Automating incident triage.

Automating Incident Triage

Incident triage can be automated by following several key guidelines:

■ The first step is to allow relevant business context information to reside on the incident level, rather than on the alert level. This can be done by creating custom tags for incidents that can hold this information and be acted upon (filtering, sorting etc).

■ The next step is to create simple yet robust formulas that allow operators to automatically calculate the values and metrics held by these tags. For example — calculate the SLA values in an SLA tag, based on the customer and the service to which the incident is referring. By automatically calculating the values and attaching them to the incident by using tags, the need to search for this information manually within tribal knowledge sources is eliminated, as is the need to calculate the values manually when the incident happens.

■ Now — provide filtering and sorting capabilities based on these tag values, and facilitate effective visualization of these tags alongside the incidents, so teams can easily make decisions and act on the incidents based on what they are seeing.

■ Finally — allow routing automation based on the tag values, so large volumes of incidents can be dealt with by relevant teams or automated resolution processes.


The Short and Long Term Advantages of Automating Incident Triage

The first advantage of incident triage automation is self-evident in all that was just discussed, mainly a shorter incident lifecycle — leading to improved performance and availability for apps and services. It's simple — lower MTTR equals better service.

But let's not forget two additional, substantial gains.

First — improved NOC productivity. By providing the above-mentioned capabilities, a substantial part of the incident lifecycle becomes simpler, and teams can collaborate better — lowering stress and effort across the board. Over time, the collected information can also be used for ongoing improvements in tools and processes.

And second — reclaimed FTE hours, an often “hidden” cost-reducer and revenue-generator. By reclaiming thousands of operational “fire-fighting” man-hours and utilizing them to improve and develop new services, enterprises not only reduce costs but also accelerate their business.

Yoram Pollack is Director of Product Marketing at BigPanda

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Why Incident Triage is a Key Element in Your MTTR

Yoram Pollack
BigPanda

One of the key performance indicators for IT Ops is MTTR (Mean-Time-To-Resolution). MTTR essentially measures the length of your incident management lifecycle: from detection; through assignment, triage and investigation; to remediation and resolution. IT Ops teams strive to shorten their incident management lifecycle and lower their MTTR, to meet their SLAs and maintain healthy infrastructures and services. But that's often easier said than done, with incident triage being a key factor in that challenge.


Why Incident Triage is Critical for Lowering MTTR

One of the main side effects of today's increasingly complex, hybrid and constantly changing IT environments is the proliferation of disparate ops teams, tools, apps and environments. This in turn leads to high volumes of IT incidents that lack full business context.

As a result, it has become increasingly difficult for first incident responders to triage incoming incidents: Without the ability to understand the incidents' severity based on their business priorities and their impact on services or customers, their routing information, and more — IT Ops teams often waste valuable time determining what to do next, and in doing so, lengthen the incident management lifecycle.

In essence, incident triage has grown to play a key role in determining MTTR in modern, hybrid environments.

Manual Incident Triage Can Be Painful

Because different applications and services have different impacts on customers, availability and revenue, when several incidents occur at the same time it is imperative for incident responders in IT Ops and NOC teams to identify the priority in which these incidents need to be dealt with, and how best to deal with each of them. For teams to be able to rapidly perform this triage, they need access to critical business context and business metrics:

■ The business severity of each incident

■ The services each of them impact

■ Whom to route them to

■ In which priority to do so

■ And other context based on the organization's relevant processes and services.

Without easy access to this information, the teams waste precious time tracking down relevant spreadsheets, runbooks, and other sources of tribal knowledge, as well as manually calculating the business metrics needed to help them understand the incidents' implications.

The more time that is spent on these manual steps, the longer the incident triage lasts.

And the longer that takes, the higher the probability that SLAs are violated, MTTR is kept high, and costs associated with high MTTR rapidly increase.

The solution? Automating incident triage.

Automating Incident Triage

Incident triage can be automated by following several key guidelines:

■ The first step is to allow relevant business context information to reside on the incident level, rather than on the alert level. This can be done by creating custom tags for incidents that can hold this information and be acted upon (filtering, sorting etc).

■ The next step is to create simple yet robust formulas that allow operators to automatically calculate the values and metrics held by these tags. For example — calculate the SLA values in an SLA tag, based on the customer and the service to which the incident is referring. By automatically calculating the values and attaching them to the incident by using tags, the need to search for this information manually within tribal knowledge sources is eliminated, as is the need to calculate the values manually when the incident happens.

■ Now — provide filtering and sorting capabilities based on these tag values, and facilitate effective visualization of these tags alongside the incidents, so teams can easily make decisions and act on the incidents based on what they are seeing.

■ Finally — allow routing automation based on the tag values, so large volumes of incidents can be dealt with by relevant teams or automated resolution processes.


The Short and Long Term Advantages of Automating Incident Triage

The first advantage of incident triage automation is self-evident in all that was just discussed, mainly a shorter incident lifecycle — leading to improved performance and availability for apps and services. It's simple — lower MTTR equals better service.

But let's not forget two additional, substantial gains.

First — improved NOC productivity. By providing the above-mentioned capabilities, a substantial part of the incident lifecycle becomes simpler, and teams can collaborate better — lowering stress and effort across the board. Over time, the collected information can also be used for ongoing improvements in tools and processes.

And second — reclaimed FTE hours, an often “hidden” cost-reducer and revenue-generator. By reclaiming thousands of operational “fire-fighting” man-hours and utilizing them to improve and develop new services, enterprises not only reduce costs but also accelerate their business.

Yoram Pollack is Director of Product Marketing at BigPanda

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Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...