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CMDB/CMS Use Cases: Asset Management and Financial Optimization

Asset Management is often the fastest use case to deploy for an initial phase CMDB/CMS because, as one vendor put it, “It’s the most linear use case” and generally speaking the least time sensitive. As a result it’s probably the most popular initial use case for CMDB/CMS initiatives -- which doesn’t mean it’s necessarily the right first phase deployment for you. You should start where your needs, and your readiness, combine to give you greatest value –- which could be any one of the three here.

Some specific use cases for asset management include:

Asset and Inventory Analysis: This most often comes up in broadly based asset management initiatives, but it is also relevant to the other use cases – and ALWAYS a challenge.

Asset Lifecycle Management: This includes SLAs, maintenance windows, and service contracts, and is central to managing assets effectively across their lifecycles. Strong support for SW license management is also important. This is often achieved through separate but well integrated solutions –- including third-party solutions.

Compliance Audits: These can now be far more effectively automated and structured based on consistent policies once assets are mapped into a CMDB/CMS system.

Financial Optimization: This is essentially optimizing your IT mission from a dollars-and-cents perspective. CMDB/CMS-driven asset and service management initiatives lay the core foundation for capturing and analyzing cost and value metrics in a substantive and contextually consistent way.


Figure 2: The darker the color, the more central the capability is to the use case. As you can see, the core CMDB, asset management and configuration management are all in black. Next in line are application dependency mapping, capacity, usage and optimization, and application development (as new application services can also be viewed as assets and relevant to asset planning and financial optimization).

EMA had four categories for assessing vendors in its radar: Value Leader, Strong Value, Specific Value, and Limited Value –- from highest to lowest. The value leaders from the radar in Asset Management and Financial Optimization were:

ASG

ASG is arguably the most platform-like of all the vendors in the radar in terms of breadth of capability and function, ASG was one of four Value Leaders in Asset Management where it received the highest overall score of any vendor. Relevant to this, ASG-Trackbird for asset management also received a Value Leader ranking in EMA’s May, 2011 radar on Software Asset Management. ASG offers a CMDB design that’s matured to focus on real needs and use cases -- with an exceptional ability to take in third-party information from a wide variety of sources.

iET Solutions

iET Solutions received especially high ratings in Cost Advantage but clear dominance in all function-related and cost-related vectors. The company’s strengths come in part from well thought out process flows to support asset lifecycle management along with its solid integration capabilities for third-party sources. It was really a balanced solution -- and offered the only deployment where the CMDB was working across a fully third-party management landscape.

LANDesk

LANDesk Service Desk Suite excelled across all areas for Asset Management and scored a first place total score (closely followed by ASG) across all eleven vendors for Asset Management and Financial Optimization. LANDesk’s Service Desk Suite is enhanced by integrations with its own Asset Lifecycle Manager which was one of the Value Leaders in EMA’s Software Asset Management Radar from May, 2011.

ServiceNow

ServiceNow's CMDB outperformed the vendor average in all areas -- with especially strong support for Integration and Interoperability and top-ranked scores for automation in Functionality. ServiceNow’s capabilities to assimilate relevant third-party sources, map them via strong discovery and inventory, and set up process automation for lifecycle control are all impressive. As you may know, ServiceNow also shook the industry by successfully establishing the SaaS model in this space –- and it continues to grow at a dramatic pace.

Click here to read the CMDB/CMS use cases for Change Management and Change Impact Analysis

Click here to read the CMDB/CMS use cases for Service Impact Management

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CMDB/CMS Use Cases: Asset Management and Financial Optimization

Asset Management is often the fastest use case to deploy for an initial phase CMDB/CMS because, as one vendor put it, “It’s the most linear use case” and generally speaking the least time sensitive. As a result it’s probably the most popular initial use case for CMDB/CMS initiatives -- which doesn’t mean it’s necessarily the right first phase deployment for you. You should start where your needs, and your readiness, combine to give you greatest value –- which could be any one of the three here.

Some specific use cases for asset management include:

Asset and Inventory Analysis: This most often comes up in broadly based asset management initiatives, but it is also relevant to the other use cases – and ALWAYS a challenge.

Asset Lifecycle Management: This includes SLAs, maintenance windows, and service contracts, and is central to managing assets effectively across their lifecycles. Strong support for SW license management is also important. This is often achieved through separate but well integrated solutions –- including third-party solutions.

Compliance Audits: These can now be far more effectively automated and structured based on consistent policies once assets are mapped into a CMDB/CMS system.

Financial Optimization: This is essentially optimizing your IT mission from a dollars-and-cents perspective. CMDB/CMS-driven asset and service management initiatives lay the core foundation for capturing and analyzing cost and value metrics in a substantive and contextually consistent way.


Figure 2: The darker the color, the more central the capability is to the use case. As you can see, the core CMDB, asset management and configuration management are all in black. Next in line are application dependency mapping, capacity, usage and optimization, and application development (as new application services can also be viewed as assets and relevant to asset planning and financial optimization).

EMA had four categories for assessing vendors in its radar: Value Leader, Strong Value, Specific Value, and Limited Value –- from highest to lowest. The value leaders from the radar in Asset Management and Financial Optimization were:

ASG

ASG is arguably the most platform-like of all the vendors in the radar in terms of breadth of capability and function, ASG was one of four Value Leaders in Asset Management where it received the highest overall score of any vendor. Relevant to this, ASG-Trackbird for asset management also received a Value Leader ranking in EMA’s May, 2011 radar on Software Asset Management. ASG offers a CMDB design that’s matured to focus on real needs and use cases -- with an exceptional ability to take in third-party information from a wide variety of sources.

iET Solutions

iET Solutions received especially high ratings in Cost Advantage but clear dominance in all function-related and cost-related vectors. The company’s strengths come in part from well thought out process flows to support asset lifecycle management along with its solid integration capabilities for third-party sources. It was really a balanced solution -- and offered the only deployment where the CMDB was working across a fully third-party management landscape.

LANDesk

LANDesk Service Desk Suite excelled across all areas for Asset Management and scored a first place total score (closely followed by ASG) across all eleven vendors for Asset Management and Financial Optimization. LANDesk’s Service Desk Suite is enhanced by integrations with its own Asset Lifecycle Manager which was one of the Value Leaders in EMA’s Software Asset Management Radar from May, 2011.

ServiceNow

ServiceNow's CMDB outperformed the vendor average in all areas -- with especially strong support for Integration and Interoperability and top-ranked scores for automation in Functionality. ServiceNow’s capabilities to assimilate relevant third-party sources, map them via strong discovery and inventory, and set up process automation for lifecycle control are all impressive. As you may know, ServiceNow also shook the industry by successfully establishing the SaaS model in this space –- and it continues to grow at a dramatic pace.

Click here to read the CMDB/CMS use cases for Change Management and Change Impact Analysis

Click here to read the CMDB/CMS use cases for Service Impact Management

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...