The BigPanda platform can help enterprise ITOps and ITSM teams improve operational efficiency by reducing manual toil, ticket volume, MTTR, bridge call volume and duration, onboarding time, and training time. The reduced workload results in cost reduction, cost avoidance, or reallocation of resources. The resulting ticket volume and labor cost savings translate green or blue dollars.

Manual toil and labor cost avoidance

By automatically deduplicating, filtering, and correlating alerts, BigPanda helps customers reduce or avoid noisy alerts and incidents. It also reduces or eliminates the need for manual triage and monitoring.

For example, Table 2 illustrates how automation helped six BigPanda customers avoid manual toil and its associated labor costs. Based on the number of annual alerts, hours of manual toil per alert pre-BigPanda, hourly labor cost, and the number of full-time employees (FTEs) affected, the median annual hours of work saved were 14,909, representing a median annual labor cost savings of $539,500 (blue dollars).

This manual toil avoidance freed IT teams to reallocate the extra time by pivoting to new or strategic value-added initiatives, amplifying the business impact. This impact has the potential to be transformative for complex global enterprises

Reducing massive amounts of alerts:“BigPanda helped us reduce our alert volume, cutting noise by 97%—from about 3 million down to 75,000 a month.” —IT Operations Leader

Customer feedback on avoiding manual toil and labor costs:

• • Eliminating manual alert monitoring: “All alerts were manually monitored, deduplicated, and correlated pre-BigPanda, on a one-by-one basis. BigPanda saves us a lot of time and lets us focus on resolving issues instead of combing through thousands of alerts to identify the problems.” —IT Operations Leader
  • Scaling with business growth: “Before implementing BigPanda, our unit was growing rapidly, generating millions of data points and events. We had no processing layer in between events and our NOC. We were drowning in noise and unable to scale and keep pace with the growth of the business.” —Operations Manager
  • Letting BigPanda handle the noise: “BigPanda transformed how we looked at monitoring. We no longer say things like ‘silence this’ or ‘change this threshold.’ Now we’re saying firehose everything at BigPanda and let it do the heavy lifting.” —Engineering Leader

Before implementing BigPanda, most teams manually triaged, reviewed, and created tickets. BigPanda helps enterprise customers reduce or avoid tickets through deduplication and correlation.

Figure 2 shows the ticket volume reduction rate ranged from 10% to 87%, with a median of 43%. Over half (53%) reduced their ticket volume by at least 40%, including three (18%) that reduced their ticket volume by at least 70%.

Reducing duplicates and streamlining alerts: “From about 30 million events, we ended up with about 200,000 tickets—BigPanda deduplication and noise filtering played a key role in reducing duplicates and streamlining alerts.” —IT Operations Leader

Figure 3 shows that the ticket volume reductions resulted in considerable annual savings, ranging from approximately $70,000 to $13.6 million, with a median of $2,309,200 (blue dollars). Most (83%) achieved at least $500,000 in annual ticket volume savings, including half (50%) that experienced savings of at least $2 million and nearly a quarter (22%) that achieved transformational savings of $5 million or more annually.

Customer feedback on reducing and avoiding tickets:

• • Scaling faster by reducing ticket volume: “The ability to take highly enriched, highly contextualized alerts and turn them into way fewer and much more actionable incidents allowed us to scale significantly quicker. Before BigPanda, every alert was a ticket, and we actioned everything.” —Operations Manager
  • Avoiding ticket overload: “BigPanda really helps during peak volumes. Instead of a thousand separate tickets overwhelming the NOC, BigPanda correlates them so we can see they’re all related. That means one person can take the ticket instead of scrambling twenty techs to figure it out.” —Operations Manager
  • Keeping ticket volume flat: “We onboarded a lot more applications and service models in 12 months, but thanks to BigPanda, the number of user-created tickets hasn’t gone up. In fact, BigPanda-opened incidents have gone down, which shows the filtering and correlation are working as our environment grows.” —IT Director

Incident-related bridge calls often involve multiple teams and can be very costly due to the high number of participants and extended call duration.

For example, customer A in Table 3 below experienced over 100 major incidents in three months and reported that every single one triggered a bridge call. Another customer noted that their bridge calls last about two hours on average.

With BigPanda, teams can identify issues before they become major outages. When a major outage occurs and an ensuing bridge call is initiated, BigPanda pings only the relevant team members, arming them with the necessary information about what happened and how to resolve it, which leads to fewer and shorter bridge calls. The reduced call volume, duration, and number of attendees translate into considerable labor cost savings and decreased business disruptions (blue dollars).

In two customer examples, the average bridge call cost reduction ranged from 35% to 74%, resulting in annual cost savings of $1.8 million to $3.2 million.

Reducing and shortening bridge calls:“Bridge calls are fewer and shorter now. BigPanda definitely helps get the right people in faster.” —Monitoring Engineer

BigPanda also helps enterprise IT teams detect, diagnose, and resolve issues faster by consolidating and analyzing overwhelming alert data, enriching alerts with relevant metadata, and ensuring the right resources are attached. Automating and streamlining incident management processes helps reduce the internal labor costs associated with resolving incidents.

Table 4 shows that, based on the number of pre- and post-BigPanda MTTR hours per ITSM ticket for five customers, the MTTR reduction rate ranged from 19% to 81%. Factoring in the cost per ticket, the annual cost savings due to reducing MTTR with BigPanda ranged from $70,000 to nearly $1.5 million (blue dollars).

Customer E noted that the MTTR for tickets handled by BigPanda was appreciably less than that handled by other sources across all priority levels, with priority-one incidents resolved about 20 times faster. On average, all its high-priority tickets were resolved within one hour.

Customer feedback on reducing MTTR:

• Detecting earlier, resolving faster: “Centralizing our operations with BigPanda allowed us to have a much earlier MTTD, which gave us a head start in resolving operational incidents.” —IT Operations Manager
• Pinpointing issues faster: “BigPanda helps identify and pinpoint the issues quickly.” —IT Operations Director
• Showing value beyond dollars: “With how we structure contracts, costs aren’t tied to individual tickets or incidents. We pay by resource unit, like maintaining 2,000 servers. So, I can’t translate time savings directly into dollars. What I can show is the difference in hours—how much effort BigPanda helped us shave off and how that reduced MTTR. But it clearly shows value, even if not in dollar terms.” —IT Director

Detecting in one minute: “Biggy feeding directly to relevant Slack channels caused MTTD to go down to one minute.” —IT Operations Director

BigPanda enables enterprises to grow faster without scaling headcount, tool sprawl, or onboarding timelines.

With correlation, automatic ticket creation, and AI-powered triage and troubleshooting, BigPanda can help enterprises avoid additional headcount, reduce existing headcount, and reduce third-party contract spending on outsourced work.

Reducing staff or third-party contract spending on outsourced work translates to green dollars. Avoiding additional headcount translates to teal dollars—either blue dollars or green dollars, depending on whether the customer had an existing budget for additional headcount that they ultimately did not use. Enterprises can reallocate these dollars to higher-value work and scaling the business.

For example, an enterprise customer avoided $140,000 in yearly offshore contractor spending, which translated to green dollars.

Customer feedback on optimizing workforce and costs:

• • Delivering FTE savings through automation: “When we start adding up the time savings, we’ve got several FTEs worth of time that the roboagent is taking care of. That’s the value right there—a lot of work getting done that we didn’t have to have a human do.” —Senior IT Engineer
  • Avoiding additional hires: “Without BigPanda, I’d probably need four or five more people.” —Cloud Engineer
  • Covering more business lines with the same team: “We started by monitoring one business line. Now we’re covering all of them without growing the team. Our team would have grown if we still did this manually.” —Operations Director

Scaling business without linear NOC costs: “BigPanda allowed us to scale and take on more business without the linear cost of the NOC.”

BigPanda can help shorten onboarding and training timelines for new or junior employees by simplifying processes and automating tasks.

For example, a global enterprise customer onboarded and trained new hires twice as quickly with BigPanda, saving $67,000 annually in associated labor costs (blue dollars).

Cutting training time in half: “BigPanda helped us cut training in half, from six months to about three months. It also made onboarding the new team in India much smoother, with almost no need to travel.” —NOC Manager

While the current sample doesn’t include quantified data for these value drivers, customers consistently cite the following benefits of using the BigPanda platform (blue dollars):

• Reduced reassignment rates: By enriching alerts to provide the necessary context, tickets get assigned to the appropriate team or team member correctly the first time, improving workflow efficiency.
• Reduced incident escalations: Ultimately, routing incidents to the proper teams the first time saves enterprises time and money, freeing expensive engineering resources to focus on their primary responsibilities rather than troubleshooting routine issues.
• Improved employee experience, satisfaction, and retention: Lower employee turnover avoids the related loss of institutional knowledge and onboarding costs (hiring and training).

Providing AI-driven ticket guidance: “With BigPanda AI, we are making it easier for our L2 and L3 support teams to fix issues because each ticket includes the exact issue, suggestions to resolve it, and a note about the change that likely caused it.” —IT Operations Director

Customer feedback on reduced reassignment rates and incident escalations:

• Achieving measurable gains in MTTR and prevention: “We’re seeing real progress. Incidents are trending the right way. P1s and P2s are down about 15% and resolving about 20% faster year-over-year. That shows the observability work, including BigPanda, is paying off. We’re also catching more issues earlier at the P3 level before they escalate. When the right people engage in the first 10 minutes, MTTR drops by about 40%.” —IT Director
• Escalating faster to the right teams: “BigPanda has streamlined our escalation process. We can get tickets to the right engineering teams faster, without delay.” —Operations Director
• Auto-ticketing directly to resolvers: “With BigPanda auto-ticketing, we can get tickets straight into the hands of the people who will resolve them.” —IT Operations Director