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The Reality of BSM Projects

Survey reveals: 75% of IT organizations fail to meet their Business Service Management goals

In October, Neebula conducted a Business Service Management survey, covering 84 companies that have recently completed BSM projects. For quite some time we've been getting informal comments about the frustration with BSM results and wanted to check whether they were pointing to a pervasive problem. Based on the survey results, it definitely seems so.

The majority of BSM projects took too long to complete, did not succeed to maintain accurate service models, and most of all, failed to meet their objectives.

Here's a summary of our findings, and a few conclusions as a summary:

Survey Sweet Spot: 50-500 business services, 700-5000 servers
The majority of respondents (44%) have 1500-5000 servers in their data center. The next group (25%) manages 700-1500 servers. These data centers enable 50-100 business services (34%) or 100-500 services (31%).

Over 2 years to complete a BSM project
The duration of BSM projects was one of the most surprising findings. Over 50% said projects lasted more than 2 years (2-3 years, 21%; more than 3 years, 32%), and 33% gave up before achieving satisfactory results.

10 days to map a single business service
We drilled down to understand the reasons behind the unending projects and asked how long it took to model a single business service. The answer - 10.5 days. This was split so that 2.1 days were spent on information gathering and 8.4 days on definition and mapping. If you consider an organization with 100 business services, this explains the never-ending projects.

5% of service models remain accurate over time
Being aware of how changes are introduced to IT with virtualization and the cloud, we asked users to rate the accuracy of their service model over time. 42% responded that their model had 'significant deviation' and 40% described their model as 'not accurate.' There were only 5% who could define their service model as accurate.

Up to 100 IT changes on a weekly basis
We wanted to quantify the changes to IT environments, leading to the inability to maintain accurate service models. The majority (48%) reported they had 10-100 changes on a weekly basis.

Fewer than 10% of business services covered
With such long projects, we were curious about coverage. How many business services were covered by the BSM solution? Over half of the respondents (51%) reported that only 5% of their business services were successfully covered. 32% said that the coverage percentage of their total services was between 5 and 10%.

Conclusion – How to achieve better results
It seems that there is a reason behind the frustration with most BSM project implementations - companies invest significant efforts over a long period of time, yet see a limited return on investment.

What can you do to be more successful? Here are our top two pieces of advice:

Building a service map that accurately maps the dependencies between a business service and its IT components is a complex and tedious task, which is always underestimated. If done manually, the recommendation is to drastically limit your project scope. A more practical way is to automate the discovery process using a tool that can accurately map all components, regardless of the environment.

Maintaining a service model that is accurate and up-to-date should be at the top of your list. The rate of changes is simply overwhelming, so that only a model that is automatically updated with changes to configurations will enable a successful BSM project with real time insight and control.

About Yuval Cohen

Yuval Cohen, Neebula CEO, has over 20 years of experience in the high tech industry. Prior to co-founding Neebula, Yuval was Vice President of Marvell Semiconductor and General Manager of Marvell Software Solutions, Israel. In these roles he was responsible for Marvell's successful software strategy, including enterprise and consumer networking software. Cohen joined Marvell in 2003 through the company's acquisition of Radlan Ltd., where he served as Chief Technology Officer and Vice President of Engineering.

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www.neebula.com

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The Reality of BSM Projects

Survey reveals: 75% of IT organizations fail to meet their Business Service Management goals

In October, Neebula conducted a Business Service Management survey, covering 84 companies that have recently completed BSM projects. For quite some time we've been getting informal comments about the frustration with BSM results and wanted to check whether they were pointing to a pervasive problem. Based on the survey results, it definitely seems so.

The majority of BSM projects took too long to complete, did not succeed to maintain accurate service models, and most of all, failed to meet their objectives.

Here's a summary of our findings, and a few conclusions as a summary:

Survey Sweet Spot: 50-500 business services, 700-5000 servers
The majority of respondents (44%) have 1500-5000 servers in their data center. The next group (25%) manages 700-1500 servers. These data centers enable 50-100 business services (34%) or 100-500 services (31%).

Over 2 years to complete a BSM project
The duration of BSM projects was one of the most surprising findings. Over 50% said projects lasted more than 2 years (2-3 years, 21%; more than 3 years, 32%), and 33% gave up before achieving satisfactory results.

10 days to map a single business service
We drilled down to understand the reasons behind the unending projects and asked how long it took to model a single business service. The answer - 10.5 days. This was split so that 2.1 days were spent on information gathering and 8.4 days on definition and mapping. If you consider an organization with 100 business services, this explains the never-ending projects.

5% of service models remain accurate over time
Being aware of how changes are introduced to IT with virtualization and the cloud, we asked users to rate the accuracy of their service model over time. 42% responded that their model had 'significant deviation' and 40% described their model as 'not accurate.' There were only 5% who could define their service model as accurate.

Up to 100 IT changes on a weekly basis
We wanted to quantify the changes to IT environments, leading to the inability to maintain accurate service models. The majority (48%) reported they had 10-100 changes on a weekly basis.

Fewer than 10% of business services covered
With such long projects, we were curious about coverage. How many business services were covered by the BSM solution? Over half of the respondents (51%) reported that only 5% of their business services were successfully covered. 32% said that the coverage percentage of their total services was between 5 and 10%.

Conclusion – How to achieve better results
It seems that there is a reason behind the frustration with most BSM project implementations - companies invest significant efforts over a long period of time, yet see a limited return on investment.

What can you do to be more successful? Here are our top two pieces of advice:

Building a service map that accurately maps the dependencies between a business service and its IT components is a complex and tedious task, which is always underestimated. If done manually, the recommendation is to drastically limit your project scope. A more practical way is to automate the discovery process using a tool that can accurately map all components, regardless of the environment.

Maintaining a service model that is accurate and up-to-date should be at the top of your list. The rate of changes is simply overwhelming, so that only a model that is automatically updated with changes to configurations will enable a successful BSM project with real time insight and control.

About Yuval Cohen

Yuval Cohen, Neebula CEO, has over 20 years of experience in the high tech industry. Prior to co-founding Neebula, Yuval was Vice President of Marvell Semiconductor and General Manager of Marvell Software Solutions, Israel. In these roles he was responsible for Marvell's successful software strategy, including enterprise and consumer networking software. Cohen joined Marvell in 2003 through the company's acquisition of Radlan Ltd., where he served as Chief Technology Officer and Vice President of Engineering.

RELATED LINKS

Related Links:

www.neebula.com

Business Service Management survey

7 Practical Tips for a Successful Business Service Management (BSM) Implementation

Hot Topics

The Latest

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

Cloud computing has transformed how we build and scale software, but it has also quietly introduced one of the most persistent challenges in modern IT: cost visibility and control ... So why, after more than a decade of cloud adoption, are cloud costs still spiraling out of control? The answer lies not in tooling but in culture ...

CEOs are committed to advancing AI solutions across their organization even as they face challenges from accelerating technology adoption, according to the IBM CEO Study. The survey revealed that executive respondents expect the growth rate of AI investments to more than double in the next two years, and 61% confirm they are actively adopting AI agents today and preparing to implement them at scale ...

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A major architectural shift is underway across enterprise networks, according to a new global study from Cisco. As AI assistants, agents, and data-driven workloads reshape how work gets done, they're creating faster, more dynamic, more latency-sensitive, and more complex network traffic. Combined with the ubiquity of connected devices, 24/7 uptime demands, and intensifying security threats, these shifts are driving infrastructure to adapt and evolve ...

Image
Cisco

The development of banking apps was supposed to provide users with convenience, control and piece of mind. However, for thousands of Halifax customers recently, a major mobile outage caused the exact opposite, leaving customers unable to check balances, or pay bills, sparking widespread frustration. This wasn't an isolated incident ... So why are these failures still happening? ...

Cyber threats are growing more sophisticated every day, and at their forefront are zero-day vulnerabilities. These elusive security gaps are exploited before a fix becomes available, making them among the most dangerous threats in today's digital landscape ... This guide will explore what these vulnerabilities are, how they work, why they pose such a significant threat, and how modern organizations can stay protected ...

The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute ...

As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...

We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...

Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...