ITAM: how AI can help us make better decisions

Concrete cases of data correlations between IT assets identified by AI.

How AI applied to ITAM allows the identification of significant correlations between data, helping us to make better decisions.

Algorithms can help us identify unsuspected connections between data: a well-known example is offered in the book “Creating Value with Big Data Analytics” by Verhoef, Kooge and Walk, which recounts the landmark case in which Walmart, the U.S. supermarket chain, had managed to identify, thanks to advanced data analysis, a counterintuitive relationship between diaper and beer purchases and  exploit it to increase sales.  

Today more than ever, AI can reveal meaningful correlations between seemingly separate data, leading to strategic decisions and surprising innovations . One of its areas of application could be precisely IT Asset Management , where vast datasets related to IT assets could be examined with speed and accuracy.

Why does ITAM offer fertile ground for AI?

ITAM has always looked for relationships between assets. Since the last century, best-practices in IT have emphasized the usefulness of having a populated CMDB, which, put simply, is nothing more than a list of assets (actually CIs if we want to use a technical term) whose map of interrelationships that exist between them and other elements (software, services, procedures, sometimes people) that contribute to the delivery of IT services is made evident.

All important activities should rest on this knowledge base: procurement planning, impact analysis, identification of the causes of problems. We could also descend into more security-related aspects and go on for hours.

So since time immemorial, IT managers have been chasing a detailed and reliable knowledge of assets to make informed decisions. But the main stumbling block is related to the difficulty and cost of keeping a CMDB up-to-date. If the data is outdated (i.e., doesn't match reality) it does more damage than anything else: think of the consequences of an impact analysis performed on the wrong dependency information.

Today, the evolution of AI allows us to revise our position on the topic: it can be used to correlate information from internal and external sources with the purpose of generate wisdom. In fact, in addition to internal operational data, it can also "read" information from external sources (industry trends, security and best-practices reports, etc.) in an integrated way: the result is a holistic and in-depth view of the IT asset ecosystem, from which actionable insights can be drawn.

A practical case: deciding on a purchasing budget

Let’s suppose we want to quickly and wisely answer a simple question: if I had to plan next year's computer purchases, how much should I budget? Here are some categories of relevant information:

[Internal Information]

• Current inventory of IT assets: details of current computers, including models, technical specifications, and maintenance status.
• Operational and technical requirements:specific needs of departments and users in terms of performance, processing capacity, memory, and storage.
• History of past purchases: analysis of past purchases, including information on suppliers, costs, and lifespan of assets.
• Feedback from users: evaluations and feedback from users on computers currently in use to identify any problems or unmet needs.
• Corporate policies and IT standards:corporate guidelines and requirements for compliance, security, and management of IT assets.
• Business trends: how the user population is growing, based on business strategy, by internal or external lines.

[External Information]

• Market and technology trends: information on new technologies and trends in the computer industry that could influence purchasing decisions.
• Industry reviews and ratings: analysis of hardware reviews and ratings from authoritative sources to identify the most reliable and best performing models.
• Performance benchmarks:benchmarking data to compare the performance of different computer models and identify those that best meet business needs.
• Market conditions and vendor negotiations:information on market conditions, current prices, and opportunities to negotiate with vendors for advantageous terms.
• Regulatory and safety updates:information on changing regulations and safety standards that might influence the choice of certain models or brands.

By having a structured ITAM solution in place, the internal information will already be in our possession and we are in a position to create structured entities to accommodate the external information.