8 things to consider before buying an AIOps tool
To determine the worth of any technology, look at the specific value drivers. While you may think that the technology itself provides value, in many instances it does not. Worse, it could actually drive a negative ROI. Many examples of this exist in the history of IT.
AIOps is no different. While this new category of technology is based on traditional management and monitoring, the new features and functions that include the use of AI and data analytics require a deeper dive.
Here’s how to define the value drivers of AIOps and what they will likely mean to you, to help you select the right AIOps tool for your enterprise.
AIOps tools are most valuable to IT operations with high levels of complexity and heterogeneity. In other words, a higher number of system patterns in the operational domain equates to a higher need for AIOps.
While complexity can vary a great deal from company to company, it is certainly a factor in widespread adoption of cloud services, particularly multi-cloud deployments. And the more complex, the more costly the deployment is (see Figure 1).
Figure 1: The relationship between complexity and cost. Note the point where you reach negative value. Source: David Linthicum
There are two ways to deal with complexity. First, resist the need to deploy complex architectures. This means mandating that a single cloud platform is leveraged.
Second, you can adapt and deal with the complexity using automation and ops-related tooling. This solution doesn’t reduce the complexity itself, but it helps you deal with it. It uses an operational layer that abstracts the back-end native interfaces that holistically become part of the complexity.
While all AIOps tools have some sort of automation, they vary greatly, ranging from simple APIs to complete process and programming engines. Some tools have “canned” processes for self-healing—for example, automatically restarting a network device. With other tools you will need to create, test, and receive audit trail reports of what action was conducted.
The more automation an AIOps tool can provide, the more value the tool will bring. Automation capabilities can comprise up to 40% of the overall value, when you look at the ROI delivered to the enterprise. (There’s an approach for determining ROI in the next section.)
Most AIOps tools have a quick ROI—usually less than six months. When building a business case, focus on the “as is” state, and then on the “to be” state with the AIOps tool. The value lies in the inefficiencies you remove between the two.
Consider the table below. This is a rough calculation of the ROI gained from deployment of AIOps tools. However, it’s most of what you’ll need to estimate the value of AIOps, which is always the improved efficiency that the tool or tools can bring.
Table 1: Example of determining the value of AIOps. Source: David Linthicum
You need to know some historical operational data, such as the average number of ops incidents during a specific period. Also, understand which incidents are resolved by humans and how quickly they are resolved (as is). Then plug in the expected increase in efficiency through the use of the AIOps tool(s).
While this is up to the enterprise to determine, a reasonable range to expect would be a 30% to 40% increase in efficiency.
Finally, you need to understand the “as is” cost of humans, considering that part of the ROI accrues from saving time and money by using automation and abstraction. This includes the human time spent to resolve issues. You can see the calculation used above.
Again, this is only an example.
