The Business Value of the BigPanda

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

Implementing the BigPanda platform can also help enterprises improve operational efficiency by replacing or reducing their IT spend, including software, hardware, infrastructure, maintenance, and third-party support services. The resulting IT cost reduction translates to green dollars.

BigPanda customers report IT spend reductions of up to $2.7 million annually, including examples outside the study sample.

For example, an enterprise customer reduced its annual IT spend by $284,000 through tool rationalization, including $110,000 from licensing costs and $174,000 from other IT expenses, such as maintenance, infrastructure, and contractors.

Customer feedback on reducing IT spend:

• Consolidating tools to unlock savings: “We were being asked to cut operating expenses and consolidate tools. BigPanda ingests events across our tech stack, giving us the visibility to evaluate which monitoring tools to keep. We’ve consolidated from about 60 tools—spanning more than 500 applications—down to one, and redirected the savings toward higher-value work.” —IT Director
• Unifying data cost-effectively: “BigPanda gives us a cost-effective way to unify data from any monitoring tool into ServiceNow without vendor lock-in. Unlike single-vendor platforms that charge heavily for ingestion, such as Dynatrace, BigPanda is an aggregator that lets us add new collectors easily and scale at our own pace, making it a more sustainable long-term strategy.” —Systems Engineer
• Reducing PagerDuty license needs: “We experienced fewer escalations and bridge calls with BigPanda. We also used agentic AI to respond to alerts. These efficiencies meant we needed fewer PagerDuty licenses, which saved us about $250,000 per year.” —Operations Director

The BigPanda platform can help enterprise ITOps and ITSM teams enhance service reliability by reducing the number and duration of major incidents, reducing service-level agreement (SLA) penalties, and improving customer satisfaction and retention. Maximizing uptime results in revenue protection.

Major incident duration reduction, avoidance, and revenue loss prevention

By reducing the number and duration of major incidents and outages, the BigPanda platform helps enterprises enhance service reliability, prevent revenue loss and internal costs from downtime, and ultimately protect revenue (teal dollars).

Three customer examples in Table 5 demonstrate how the BigPanda platform helped reduce the average duration or MTTR of major incidents by 72% to 90% (resolved 4x to 10x faster). Shorter durations prevented an estimated $1.9 million to $21.8 million in annual revenue loss.

Transforming outage reduction: “There has been a huge reduction in major outages over the last couple of years—both in volume and duration—and this can be attributed to BigPanda. I’ve been at this game for over 20 years, and this is the first time I’ve had any real success in doing that. It’s really transformational and game-changing.” —IT Operations Director

Customer feedback on reducing or avoiding major incidents and preventing revenue loss:

• Auto-resolving the majority of incidents: “Just to put the numbers in context, about 80% of monitoring incidents come through BigPanda and get auto-resolved without anyone even touching them. The real value here is in avoiding outages altogether, and when that’s not possible, cutting their duration as much as we can.” —IT Operations Director
• Delivering best-ever year-end performance: “Since implementing BigPanda, this past year-end was our best period ever for major incidents—in both total count and impact. The BigPanda major incident tickets had a significantly lower MTTR than tickets created manually. We’re seeing real time-to-resolution benefits.” —Monitoring Engineer
• Proactively preventing outages: “BigPanda enabled about 40 preventative interventions, compared to about 200 handled manually, which shows its ability to stop incidents before they become outages. The next step is quantifying the impact by linking these prevented incidents to avoided transaction failures and the resulting cost savings.” —IT Manager

Unquantified outage impact reduction

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

• Reduced SLA penalties indicate that an enterprise has made tangible improvements to its incident management process to resolve incidents more quickly and efficiently. These improvements prevent breaches of customer/compliance SLAs, as well as the related costly penalties, translating to green dollars.
• Improved customer satisfaction and retention indicate that an enterprise has improved service reliability, reducing the impact of outages on customers. These improvements build trust and demonstrate reliability (satisfaction). They signify that customers are not just using a product or service, but are also highly satisfied with its reliability. This customer satisfaction, in turn, encourages them to renew (retention), translating to blue dollars.

Renewals are one of the clearest signals of the business value BigPanda delivers. Customers overwhelmingly choose to renew when financial savings are proven and communicated to decision-makers.

Driving retention as the ultimate metric: “Our performance is measured by five KPIs: customer acquisition, customer retention, revenue, cost of acquisition, and customer experience. In operations, we track availability and MTTR, but the real success is measured by its impact on customer retention. BigPanda helps by cutting down the noise, speeding up resolution, and giving us the visibility we need. All of that adds up to fewer disruptions and a smoother customer experience, which is what actually moves the retention number.” —Head of Infrastructure Operations

The annual benefit value of the BigPanda platform consists of the total quantified and annualized financial savings—including labor, ticket volume, MTTR, bridge call, onboarding and training time, additional headcount, existing IT spend, and major incident duration costs—for 22 customers.

annual benefit value 🟰 (sum of quantified benefits ➗ months of observation) ✖ 12

Figure 4 shows that the total average annual benefits ranged from $300,000 to over $25 million, with a median of $2.85 million.

• Most (59%) enterprise customers had annual benefits between $1 and $10 million, while three (14%) achieved transformational outcomes of more than $10 million.
• Nearly three-quarters (73%) received at least $1 million in annual benefits from BigPanda, including about a third (32%) that received $5 million or more.
• Even at the low end, every BigPanda customer sees at least hundreds of thousands in yearly value.

Validating ROI and cost savings: “The BigPanda business value assessment confirms what we’ve experienced and known. We trust BigPanda is correlating alerts, saving us from duplicate work and looking at too many tickets. The value is understood and appreciated. It certainly backed up our assumptions and aligns with and validates what we see in our internal reporting. The ROI and cost savings it showed are exactly what we expected.” —IT Infrastructure Manager

Each customer’s ROI was determined by subtracting the annual BigPanda investment from the annual BigPanda benefits and then dividing that amount by the annual BigPanda investment.

annual ROI 🟰 (annual benefits ➖ annual investment) ➗ annual investment

ROI results across 22 BigPanda customers were consistently positive. The data show that enterprises of all sizes realize material returns with BigPanda, with several outliers demonstrating transformational impact.

Figure 5 shows the average ROI ranged from 40% to 2045%, with a median of 430%. In other words, on average, customers netted $430 for every $100 invested in BigPanda.

• Two customers achieved a transformational ROI of over 1000%.
• Most (91%) BigPanda customers realized an ROI of well above 100%, including nearly half (46%) that realized 500% or more, which is compelling.
• Even at the low end, all BigPanda customers saw a meaningful return on their investment.

Proving ROI through enrichment: “We were able to impact MTTR directly with enrichment. That really helped immediately prove the ROI of BigPanda. We saw an immediate decrease in customer complaints, and we were able to focus our energy on things that drive the business.” —Operations Manager

Figure 6 shows that most (70%) BigPanda customers typically go live in three to nine months, with a median of about six months. This implementation time is fast by enterprise standards, especially for an event intelligence platform embedded across tools and teams.

Based on the implementation time and total year-one costs and benefits for three BigPanda customers, Table X shows that the payback period was less than a year, ranging from as low as seven months to 10 months. These findings indicate that BigPanda delivers rapid ROI.

Customers have also reported operational outcomes that extend beyond the quantified benefits outlined in this report. While not formally measured in this dataset, these themes highlight potential areas of value, including:

• Improved data quality through increased alert correlation accuracy, faster and more informed incident triage, and enriched service desk tickets helps ensure that the data flowing into the incident management system is accurate, complete, reliable—and more actionable.
• Increased accountability and visibility for incident ownership, service health, and tool efficiency through enhanced root cause analysis (RCA) and better data enrichment help ensure operators can quickly pinpoint the right teams, reduce reassignment delays, identify recurring incidents to address systemic issues, and analyze which monitoring and observability tools contribute to actionable alerts versus alert noise.
• Increased innovation, predictability, and agility can be achieved through streamlining incident management processes and reducing the time spent on manual incident investigation, escalation, and firefighting. This efficiency helps teams free up valuable time and resources, enabling them to be more innovative, proactive, and agile, and focus on strategic, forward-looking projects.
• Stronger business-IT alignment through unified analytics dashboards and improved transparency enables a direct connection between IT performance and overarching business goals. This visibility demonstrates how investments in IT and AI directly contribute to financial success and key business objectives, linking technical metrics to business outcomes such as service availability and customer retention.
• Improved governance and risk mitigation through standardized, AI-assisted runbooks and proactive risk detection help provide clear ownership and step-by-step guidance. Centralized context speeds handoffs, reduces variance, and cuts compliance risk. With transparent audit trails and pattern learning (including root cause, resolution steps, and changes), teams can prevent repeat issues and reduce SLA breaches and end-user impact.

Prioritizing by business impact: “We’re maturing in how we measure IT performance to match how the business sees it. For example, if a server goes down but customers aren’t impacted, that shouldn’t be a P1. BigPanda helps us make that distinction by tying IT signals to real business impact. It’s a big step forward.” —Chief Operating Officer

Customer feedback on additional operational outcomes:

• Normalizing across tools: “Different tools often describe the same issue in different ways—Splunk says one thing, Dynatrace says another. BigPanda helps normalize and correlate those alerts so we can quickly see which backend service is actually impacted. That kind of consistency saves us critical troubleshooting time.” —Enterprise Monitoring Manager
• Centralizing in a single pane: “Before BigPanda AIOps, we had a lot of challenges. As a result of growth, we had multiple, scattered dashboards, and these disparate systems increased our MTTD. BigPanda centralized all those dashboards into a single pane of glass.” —IT Operations Manager
• Proactively detecting and preventing issues: “With BigPanda, we’re seeing all the precursor events before systems fail to get ahead of things, have a chance to remediate the problem, and create an automation to ensure it won’t ever happen again.” —IT Operations Director

About BigPanda business value assessments

A BigPanda business value assessment is a collaborative, customer-facing process tailored to each organization’s needs. Each custom assessment is meant to provide updates and insights, quantify key metrics, and provide a snapshot of the business value and impact of the BigPanda platform. These assessments help organizations justify their BigPanda platform spend, quantify their ROI, and identify areas for improvement.

BigPanda also conducts business value assessments with interested prospective customers who want to understand the potential impact and realities of an agentic ITOps platform.

Business value assessment methodology

The BigPanda business value services team works closely with key ITOps and ITSM stakeholders at each organization, as well as its BigPanda account management team, to conduct the assessments and present the findings to key executive stakeholders. The following members of the BigPanda business value services team conducted the assessments and contributed directly to the findings summarized in this report:

• Kamil Brozek, Vice President of Value Engineering at BigPanda
• Elad Golan, Senior Business Value Manager at BigPanda
• Westin Haas, Senior Business Value Manager, BigPanda
• Juan Serrano, Senior Business Value Manager at BigPanda

Their domain expertise and direct customer engagement were essential to the data used in this analysis.

The BigPanda business value assessment process they use is methodical and standardized, but flexible enough to meet customers where they are. The assessments typically take two to four weeks to complete and involve the following phases:

• Discovery: The BigPanda business value services team meets with key customer stakeholders to identify objectives, gaps, and decision criteria, and collects other data and qualitative details needed for the assessment.
• Creation: The BigPanda business value services team quantifies KPIs, conducts an ROI analysis, creates value maps, and identifies areas for improvement.
• Presentation: The BigPanda business value services team presents the quantitative and qualitative findings to the customer and collects feedback.

BigPanda value framework and definitions

The BigPanda value framework helps uncover areas customers want to explore. It focuses on cost reduction and avoidance, revenue protection, and risk mitigation, covering various types of data, benefits, results, and impacts.

Data types

This report includes quantitative and qualitative data about the business value of the BigPanda platform.

Benefit and result types

The BigPanda platform’s value drivers fall into two primary benefit types: improved operational efficiency and enhanced service reliability, which result in either cost reduction and avoidance or revenue protection.

How BigPanda processes data

When reviewing the value drivers and benefits of the BigPanda platform, it helps to understand how BigPanda processes data.

Enterprise ITOps and ITSM teams use the BigPanda platform to detect events during pipeline processing, including:

• Correlating alerts across applications and services
• Enriching alerts for greater intelligence
• Minimizing alert noise and fatigue

Structured data is ingested into BigPanda as events from monitoring, observability, configuration management database (CMDB), and other tools, and is unified within the BigPanda IT Knowledge Graph. BigPanda compresses the events into alerts via deduplication and alert filtering, enriches them with additional context, and correlates related alerts into high-level incidents. Actioned incidents represent the outages and system issues that team members acted on, including opening an ITSM ticket.

This workflow enables IT teams to identify, triage, and respond to problems quickly before they escalate and reduces noise by up to 99.9%.

It also enables the BigPanda team to provide additional value by helping customers evaluate the effectiveness of their monitoring and observability tools for IT event management.

For example, the median ITSM ticket distribution and data for 17 customers show that BigPanda (49%) or other tools (6%) proactively generated over half (55%) of their ITSM tickets. Users, usually those in the service desk, retroactively generated the remaining 45%. This finding suggests that monitoring and observability tools failed to detect nearly half of all incidents. BigPanda uses this and other data to help customers rationalize their monitoring and observability tool spend.

Engaging developers in monitoring: “We actually have devs who get into BigPanda now and take an interest in their event flow. Nothing like that ever happened before. It used to be a black box.” —Monitoring Engineer

About this report

This is the first report to showcase the business value of the BigPanda platform based on quantitative and qualitative customer feedback.

Report methodology

This report was authored by Alicia Basteri, Principal Content Manager at BigPanda. It is based on quantitative and qualitative findings from business value assessments conducted by the BigPanda business value services team for 23 BigPanda customers between November 2024 and July 2025.

The observation period for each organization’s business value assessment ranged from two months to two years. Most organizations (87%) were observed for at least six months, including 52% for at least a year. The median observation period was 12 months.

Demographic and firmographic information is based on ZoomInfo data from March 2025.

BigPanda anonymized and aggregated the relevant data to give a general overview of the business value of the BigPanda platform. Any detailed information that could help attackers and other malicious parties was deliberately excluded from this report.

All quotes included in this report are based on customer feedback. While quantitative findings are limited to the defined sample, illustrative quotes may include insights from additional customers. All dollar amounts are in USD, and all data are based on UTC (Coordinated Universal Time), also known as GMT (Greenwich Mean Time).

To protect customer confidentiality, all customer-specific identifiers, including company names, detailed job titles, and potentially identifying operational metrics, have been anonymized or generalized in this report while preserving the substantive insights and business value outcomes.

Outliers usually skewed the average (mean), so the median was more representative of typical behavior and was used throughout the report. Aggregate medians are shown as calculated.

Citing the report

Suggested citation for this report:

APA Style:
BigPanda (October 2025).The Business Value of the BigPanda Platform. BigPanda. https://www.bigpanda.io/resource/report/business-value

The Chicago Manual of Style:
BigPanda (October 2025). The Business Value of the BigPanda Platform. BigPanda. https://www.bigpanda.io/resource/report/business-value

Demographics and firmographics

This report is based on business value assessments completed between November 2024 and July 2025 for 23 organizations using the BigPanda platform.

The study represents both new and loyal BigPanda customers. The time each organization had been using the BigPanda platform, as of the business value assessment completion date, ranged from approximately four months to over seven years. Most (83%) had been using BigPanda for at least a year, including 44% for at least three years and 17% for at least five years. The median time using BigPanda was 2.7 years.

Organization size

The BigPanda platform was designed for enterprise organizations, so all organizations included in this report were large enterprises. In fact, the typical organization in this study is significantly larger than the average enterprise.

Nearly two-thirds (62%) were on the 2024 Fortune 1000 list (US only), a third (33%) were on the 2024 Fortune 500 list (US only), and 17% were on the 2024 Global Fortune 500 list.

This underscores the ability of BigPanda to drive business value across some of the world’s largest, most operationally complex enterprises.

Annual revenue

All organizations had an annual revenue of at least $35 million. Over three-quarters (78%) had an annual revenue of at least $1 billion, including 57% with at least $5 billion, 39% with at least $10 billion, and 17% with at least $25 billion. The median annual revenue was $5.97 billion.

Number of employees

The median number of employees was 9,000. Nearly half (48%) of the organizations had 10,000 or more employees, including 26% with 20,000 or more and 17% with 100,000 or more employees. Less than a third (30%) had fewer than 5,000 employees, including 13% with fewer than 1,000.

Number of locations

However, most (91%) of the organizations included in this report have multiple locations, and many are global enterprises.

The median number of locations per organization was 23. Over three-quarters (83%) had at least five locations, including nearly half (48%) with 25 or more and one in six (17%) with 50 or more. Less than a third (30%) had fewer than 10 locations.

Industries

BigPanda delivers business value in nearly every vertical, including mission-critical, regulated, and customer-sensitive sectors. This study represents 10 industries, with a particularly strong presence in those where uptime, scale, and complexity are vital, such as financial services, insurance, technology, healthcare, managed service providers, and manufacturing.

BigPanda delivers agentic automation for ITOps. We enable enterprises to keep the digital world running by transforming manual, reactive human processes into intelligent, autonomous systems that detect, respond to, and prevent IT incidents at machine speed. That’s why the world’s most trusted brands rely on BigPanda to improve operational efficiency and deliver exceptional service reliability to their customers.

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