What Is IT Operational Intelligence
by Taurai Mutimutema
Knowledge is more important than ever in businesses of all types. Each time an engineer makes a decision, the quality of outcomes (always) hangs on how current and thorough the data that brought about their knowledge is. This data-decision relationship brings to mind the idea of operational intelligence (OI). Operational intelligence is a combination of two terms that together, are responsible for the success of businesses through decisions made from fresh knowledge.
This post discusses OI concepts. After a quick list of its benefits, we will clarify the elements of OI and suggest how to attain it.
IT operational intelligence places a focus on analyzing the most recent data gathered from your infrastructure to inspire intelligent decisions. Focusing on data makes it easier to understand how OI impacts all areas of IT.
Let’s look at why you would need IT operational intelligence in the first place by discussing some of its advantages.
4 Benefits of IT Operational Intelligence
As we list these benefits, you’ll quickly notice that operational intelligence is data reliant. Every step on the pathway to achieving its benefits requires the tactical use of intentionally collected information. Let’s look at four important benefits.
Knowing that each business process runs on a piece of software that has metrics is the first step toward continually fine-tuning your processes towards perfection, which will give you an advantage over your competitors. It doesn’t have to be a software company. Even a hospital performs better with the framework of continual improvement in play.
IT OI pulls data you’d have otherwise lost in the noise of productivity. Data from one business application will go unused because it hasn’t been normalized to make an impact up the chain of decision making. Such data can quickly be converted into action, or at the very least, influence key decisions. Obtaining full visibility of this data often requires the integration of software applications in use across departments. Without integration, some software applications you’re using are essentially blind to potentially useful data from the rest of your outfit.
Unless you already have the tools and strategies to efficiently collect and process data, you’ll always take too long to make smart decisions. A good operational intelligence approach produces reports ahead of time (customized to your case). Eliminate application network latency from the equation and you’ll get close to real-time snapshots of your key business variables. Think about how application performance monitoring (APM) software works.
Ample intelligence about operations makes you an actor, whereas most companies can only react. Analytical tools that turn patterns and thresholds into alarms eliminate tedious fault-finding missions. Incorporate artificial intelligence (AI) to enact strategies based on your business’s data and you could take out the need for human intervention.
From this short detour, you can see how all four advantages rely on data collection and processing. It’s not surprising then that many confuse business intelligence (BI) with IT operational intelligence. Before we get deeper into the concept of OI, let’s differentiate the two.
IT Operational Intelligence vs. Business Intelligence
Both intelligence concepts strongly rely on data to facilitate smarter decision making. However, there is a notable disparity between their approaches and outcomes.
- Data focus: The tools and methods used in BI comb through historical data with the sole intent of improving the position of a company through simulations. On the other hand, IT OI places its main focus on real-time data. As such, OI analytical tools and methods detect current trends and provide fresh insights for decisions other than (but including) financial ones.
- Areas of application: IT OI integrates data from more of your applications, and thus, it often applies to multiple business practices. When intended, it can incorporate business intelligence as well. Conversely, BI pulls data to analyze from one application. In the end, IT OI is just a myth if data collection doesn’t include the entire layout of an organization’s applications.
- Insight actionability: Business intelligence analysis concludes with dashboards and pattern visualization, and the action is left to a human actor. On the other hand, the most intuitive IT OI completes the lifecycle of data. This could happen without the need for human intervention in cases where AI implements actions.
3 Steps to Attain Operational Intelligence
Consider everything we’ve mentioned above as the groundwork for a holistic understanding of OI in the IT context. At this point, let’s pull the pieces together and reveal how to build an operational intelligence blueprint. As you can imagine, IT OI is more of a journey than a destination. As such, even after attaining it, you must continuously work to maintain it.
- Change Your Perception of Data
The sooner you treat data as an asset, the more you can start squeezing out of each data stream flowing within your company. Consequently, the more sources of data you tap into, the more complete your decisions become. This new paradigm makes every last byte equal to or just as consequential as actual money bleeding out. Integrating your data sources (work applications) with toolsets that take advantage of them for processing is the first strategic step toward operational intelligence.
- Process Your Data
Unprocessed data is as good as uncollected. There’s no point in having terabytes of data if you’re not using them to connect the dots for better decision making. It stands then, that your analytics tools make or break how intelligent your operations are. At this juncture, monitoring, test orchestration, and automation tools come into play. The data processing stage is where dashboards emerge. As you already know, these provide an actual glimpse into the data streams your business pumps from work applications.
- Create Action Policies
Each data point is a potential trigger for an event that can correct or improve your business processes. As such, it’s wise to strategically set policies that set events in motion based on processed data. At this stage, consider infusing some AI into your OI blueprint.
While all this is happening, it’s very important not to take your eye off the security side of operational intelligence. To start with, when collecting data, sealing out unauthorized access is key to a robust strategy. Also, there is the issue of making data visible only to the tools and workforce that have clearance. It stands then, that security is not optional, regardless of what stage of your OI plan implementation you find yourself in.
We mentioned that operational intelligence is a journey, which means it has to be maintained just as intently as it was obtained. You could also employ a system to maintain your OI plan. Create notifications for when metrics are falling under optimal levels. These, along with AI that triggers corrective processes (think environment maintenance) are a good start to achieving OI.
IT Operational Intelligence and DevOps
On a strictly engineering front, IT OI now uses a new approach for system deployment (DevOps). Taking on a DevOps and continuous deployment stance, the various tools you chose to achieve your desired state of OI should work hand in hand. We’re talking seamless compatibility of all business applications, and it could get costly (time and money wise) very quickly.
Building and maintaining one such tool to act as a container for all applications to seep data onto is plausible and often worth it. However, the complexity of such an environment is controlled by how creative your development team is. Then there’s the usual crossroad: buy or create the container.
Even if time is on your side, you should still consider the cost of heavy API development sessions needed to bridge the gaps created when you adopt and need to integrate systems from different vendors. Either way, if there is a pill you can swallow (a la Matrix) to attain IT operational intelligence, be sure you know where you’ll wake up before you gulp it down.
This post was written by Taurai Mutimutema. Taurai is a systems analyst with a knack for writing, which was probably sparked by the need to document technical processes during code and implementation sessions. He enjoys learning new technology and talks about tech even more than he writes.
16September, 2021 by Carlos SchultsLet me start with a question: as a leader in tech, are you satisfied with the budget you have? If I had to guess, I'd say the answer is no. Because of that, calculating the return on investment of the many activities in software...
14AUGUST, 2021 by Ukpai UgochiIt is the goal of every software engineer and software development firm to continuously ship products to end users. This can only be achieved through software deployment. In this post, we'll explore deployment and deployment planning,...
09SEPTEMBER, 2021 by Eric GoebelbeckerLet’s talk about container essentials. Over the past few years, containers have transitioned from the hottest new trend to essential IT architecture. But are they are good fit for you? Are you wondering whether or not you’re using...
05AUGUST, 2021 by Alexander FridmanIn the beginning there was nothing. Then there was the monolith, though we used to simply call monoliths "software." Today we have two rival architectural types: monoliths and microservices. This post will explain what monoliths and...
15JULY, 2021 by Justin ReynoldsCompanies go to great lengths to protect their physical environments, using deterrents like locks, fences, and cameras to ward off intruders. Yet this same logic doesn’t always translate to digital security. Corporate networks — which...
06JULY, 2021 by Justin ReynoldsCompanies today face increasing challenges around reducing the time and cost of software development. Many are thus using DevOps methodologies, which combine software development and IT operations to achieve continuous delivery and...