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IT and Business Alignment: Has APM Evolved to Fulfill the Promise of BSM? Part 1

Sridhar Iyengar

Over the years, IT systems management has evolved dramatically. What started as monitoring just the network infrastructure via ping/telnet/SNMP has transformed into monitoring and managing multi-tier, geographically distributed IT infrastructures and applications deployed on physical and virtual environments as well as private, public and hybrid cloud environments.

Around a decade ago, Application Performance Management (APM) emerged as an independent category within systems management. APM enables one to measure and eventually ensure availability, response time, and integrity of critical application services used by the business, i.e., the consumers of the IT application services. A couple of years later, another IT management technology called Business Service Management (BSM) emerged to align IT with business objectives.

Now, interest in BSM is resurging as companies strive to make their IT departments more responsive to their business needs. Simultaneously, APM has also emerged stronger in the last few years to encompass a broader scope in IT management. This two-article series looks at the evolution of BSM and APM, the key drivers for both technologies, and how we're seeing them converge to fulfill the promise of aligning IT with business.

Enter BSM

In the last decade, IT teams were often left in the dark whenever a problem in the IT infrastructure led to the unavailability or poor responsiveness of an IT application service used by the organization's business process. The problem? The lack of mature IT processes and tools meant IT teams rarely had any insight into the impact of the problem on the business.

As a result, IT was often criticized for being not aligned with the needs of the business. This led to the coining of the term "business service" which was different from an IT service. A business service was defined as an IT service that was provided by the IT team to the business and that had an intrinsic financial value associated with it.

Any impact to a business service always had a financial implication, and it was all the C-level executives cared about. This led to the pursuit of the lofty goal of identifying, measuring and ensuring availability and response time of business services, aka Business Service Management (BSM).

BSM dynamically linked business-focused IT services to the underlying IT infrastructure. It was what the CIOs and IT heads of the time wanted to hear, and the marketeers served up BSM to them as the holy grail of IT.

BSM promised:

- Alignment of IT and business: BSM was typically sold to the C-level executives as "The Tool" - a magic pill that could automatically help them align IT with business. Numerous productivity numbers and terms such as "time to gather business insights" were thrown up to justify BSM purchases.

- Faster time to resolve problems: BSM users were touted to be an order of magnitude faster in isolating and diagnosing problems compared to those not using it.

- Easier implementation: Not only could BSM improve IT productivity and business profitability, it was also supposed to be a breeze to set up and automatically configure.

- Better TCO and ROI: IT operations would be able to reactively and proactively determine where they should be spending their time to best impact the business. The cost savings in faster troubleshooting and increased business profitability would justify the investment in BSM.

- Power and control for business owners: Business owners were promised visibility and control into what was happening and how it could be fixed.

BSM Oversold and Under Delivered

As organizations started gradually buying and using BSM products, they realized that those products required a lot of manual effort and complex procedures to work. It was not the plug-and-play solution that was originally promoted.

BSM was a term coined to fill the gap between businesses' needs and IT capabilities. When business failed to see the value in BSM, the BSM promises fell flat.

So why didn't BSM live up to expectations? Probably because:

- BSM did not truly reflect the financial impact of IT on business.

- BSM did not have automated, real-time updates to reflect the current status of IT. As IT changed, BSM systems would either have older data or require manual update of the status.

- There was no easy and automated way to capture all the dependencies of a business process on the underlying IT components. Capturing such details was complex and often inaccurate, and it required a lot of effort.

- BSM was probably ahead of its time. BSM-required technologies such as automated discovery and dependency mapping and end-user monitoring were not sufficiently matured at that time.

As originally brought to market, BSM solutions failed to deliver the coveted alignment of IT and business. However, the initial failure did little to discourage organizations from pursuing their goal.

In the second article of this two-part series, we will take a look at the rising popularity of APM and the resurgence of BSM as companies continue to seek alignment.

Read Part 2 of this article: IT and Business Alignment: Has APM Evolved to Fulfill the Promise of BSM? Part 2

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IT and Business Alignment: Has APM Evolved to Fulfill the Promise of BSM? Part 1

Sridhar Iyengar

Over the years, IT systems management has evolved dramatically. What started as monitoring just the network infrastructure via ping/telnet/SNMP has transformed into monitoring and managing multi-tier, geographically distributed IT infrastructures and applications deployed on physical and virtual environments as well as private, public and hybrid cloud environments.

Around a decade ago, Application Performance Management (APM) emerged as an independent category within systems management. APM enables one to measure and eventually ensure availability, response time, and integrity of critical application services used by the business, i.e., the consumers of the IT application services. A couple of years later, another IT management technology called Business Service Management (BSM) emerged to align IT with business objectives.

Now, interest in BSM is resurging as companies strive to make their IT departments more responsive to their business needs. Simultaneously, APM has also emerged stronger in the last few years to encompass a broader scope in IT management. This two-article series looks at the evolution of BSM and APM, the key drivers for both technologies, and how we're seeing them converge to fulfill the promise of aligning IT with business.

Enter BSM

In the last decade, IT teams were often left in the dark whenever a problem in the IT infrastructure led to the unavailability or poor responsiveness of an IT application service used by the organization's business process. The problem? The lack of mature IT processes and tools meant IT teams rarely had any insight into the impact of the problem on the business.

As a result, IT was often criticized for being not aligned with the needs of the business. This led to the coining of the term "business service" which was different from an IT service. A business service was defined as an IT service that was provided by the IT team to the business and that had an intrinsic financial value associated with it.

Any impact to a business service always had a financial implication, and it was all the C-level executives cared about. This led to the pursuit of the lofty goal of identifying, measuring and ensuring availability and response time of business services, aka Business Service Management (BSM).

BSM dynamically linked business-focused IT services to the underlying IT infrastructure. It was what the CIOs and IT heads of the time wanted to hear, and the marketeers served up BSM to them as the holy grail of IT.

BSM promised:

- Alignment of IT and business: BSM was typically sold to the C-level executives as "The Tool" - a magic pill that could automatically help them align IT with business. Numerous productivity numbers and terms such as "time to gather business insights" were thrown up to justify BSM purchases.

- Faster time to resolve problems: BSM users were touted to be an order of magnitude faster in isolating and diagnosing problems compared to those not using it.

- Easier implementation: Not only could BSM improve IT productivity and business profitability, it was also supposed to be a breeze to set up and automatically configure.

- Better TCO and ROI: IT operations would be able to reactively and proactively determine where they should be spending their time to best impact the business. The cost savings in faster troubleshooting and increased business profitability would justify the investment in BSM.

- Power and control for business owners: Business owners were promised visibility and control into what was happening and how it could be fixed.

BSM Oversold and Under Delivered

As organizations started gradually buying and using BSM products, they realized that those products required a lot of manual effort and complex procedures to work. It was not the plug-and-play solution that was originally promoted.

BSM was a term coined to fill the gap between businesses' needs and IT capabilities. When business failed to see the value in BSM, the BSM promises fell flat.

So why didn't BSM live up to expectations? Probably because:

- BSM did not truly reflect the financial impact of IT on business.

- BSM did not have automated, real-time updates to reflect the current status of IT. As IT changed, BSM systems would either have older data or require manual update of the status.

- There was no easy and automated way to capture all the dependencies of a business process on the underlying IT components. Capturing such details was complex and often inaccurate, and it required a lot of effort.

- BSM was probably ahead of its time. BSM-required technologies such as automated discovery and dependency mapping and end-user monitoring were not sufficiently matured at that time.

As originally brought to market, BSM solutions failed to deliver the coveted alignment of IT and business. However, the initial failure did little to discourage organizations from pursuing their goal.

In the second article of this two-part series, we will take a look at the rising popularity of APM and the resurgence of BSM as companies continue to seek alignment.

Read Part 2 of this article: IT and Business Alignment: Has APM Evolved to Fulfill the Promise of BSM? Part 2

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...