During the next few years, the discipline of IT asset management is primed for a dramatic transformation – fuelled by technology advances in the fields of artificial intelligence (AI) and machine learning. When companies emerge from this transformation, they will have an entirely different perception of their assets and how to manage them. This is a digital transformation story about to unfold.
If you were to ask most IT professionals today to describe asset management, then they would likely say inventorying devices, mapping dependencies, auditing for quality, managing asset lifecycles and depreciation, among others. Those are rather good descriptors of what asset management is today – but it’s about to change.
Legacy asset management is built on the notion that a company has physical assets that it owns and uses to support its business activities. To reduce waste and control costs, the company must have a clear picture of its assets and a set of processes to manage and refresh them as they lose value during time. The problems with this perspective are threefold:
- Assets are treated as a source of cost, not as a source of value.
- The definition of assets as “owned” doesn’t fit the model of a modern digital enterprise.
- Asset-management activities are focused on the objects themselves and not the impact they have on the environment in which they occur.
As mentioned above, there are 2 technology trends poised to disrupt the way companies think about IT asset and inventory management.
Machine learning is computer programs with the capability to change without reprogramming when exposed to data. Machine-learning technology has progressed to the point where it can be used to make legacy asset-management processes of discovery, association and dependency mapping, and even monitor utilization and performance relative to potential almost entirely automated. During the next couple of years, the need for 80–90% of the manual activities of the asset-management discipline today will be eliminated through automation.
Artificial intelligence (AI)
Artificial Intelligence is the second technology trend that will disrupt asset management, but in a different way – focusing not on existing activities, but unlocking a new set of more advanced capabilities that were previously unattainable. Artificial intelligence (applied to IT asset management) is not just about learning and executing repeatable patterns and automating tasks, events, etc. based on business rules – but being able to identify, associate, recognize and interpret accurately both usage context and intent and frame the asset in the context of the business and operations environment in which the asset exists.
In simpler terms, AI will enable us to expand our picture of assets beyond the technology and develop an understanding of the entire enterprise (akin to seeing the whole forest, not just the trees).
Asset Management – The Next Generation
Once we can see the bigger picture clearly, the conversation within IT will shift from optimizing assets to optimizing impact on the enterprise. A next-generation set of asset-management capabilities (enabled by AI) will enable this shift and will include:
- Cost optimization by dynamically shifting workloads to the lowest cost resources
- Almost 100% resource utilization through active capacity management
- Risk mitigation and real-time redundancy planning using analysis and simulation
- Automated diagnosis and repair to increase asset availability
- Dynamic sourcing and cost arbitrage across service providers
As these new capabilities mature, the definitions of “What is an asset?” and “What is covered by the asset-management process?” will change. Companies will realize that enterprise optimization involves managing not just physical assets and not just assets the company “owns” – but also creating a need for IT asset-management capabilities to include leased, contracted, subscriptions and employee-provided resources that someone owns other than the company, but the company utilizes to support operations.
The definition of assets will also expand to include data in addition to technology requiring active management, as companies develop a deeper understanding of the durability and strategic importance of data assets in their organization. This expanded understanding will be necessary to leverage fully the power of AI to impact enterprise performance.
Machine learning and artificial intelligence will be critical to enabling the rapid maturation of asset-management capabilities during the next few years. These new technologies will break through the present limitations that human actions and cognitive processing are placing on company’s asset-management potential – unlocking a new set of digital capabilities that are faster, have greater capacity, never sleep, can recognize patterns almost instantly and never forget events and observations of the past. Once this digital transformation occurs, IT asset management will never be the same.
Check out the most efficient way to track your inventory here.