Big data is a frequent topic of conversation among C-suite executives but many have difficulty pointing to specific benefits much less ROI derived from the technology.

Old school dashboards can be challenging to interpret, as they’re not tied to business outcomes and don’t clearly showcase potential actions. CIOs and other business leaders need data presentation techniques that meet modern expectations for usable and understandable dashboards, not just numbers that still need interpretation. This means AI-driven capabilities are crucial, with dashboards that can answer important questions, including:

  • What's been happening?
  • Is this likely to be a trend?
  • What's causing it?
  • Is there some action to be taken to change this?
  • And once we've taken that action, did it make a difference?

Making the right connections

Business executives want to look at data from their own domains, with those at the top looking for overall enterprise performance. IT is often tasked with gathering and corralling the data and connecting the analytical services that enable those views, and the dashboards that result can help line of business (LOB) executives glean actionable insights.

When AI is added to the process, dashboards can demonstrate cause and effect relationships, improve projections, and even automate some decision-making processes. But justifying the IT investment to create these tools depends on linking outcomes to the insights and actions taken. It's up to the CIO to identify the links between IT spend and business ROI for that spend. CIOs need their own dashboards that deliver operational insights.

CIO dashboards are usually last to receive the attention they need

The CIO is charged with managing the totality of the enterprise’ data, and understanding how different connections are or should be made can be monumental. Often that leaves little bandwidth for development of IT-specific analytical tools that could help the CIO fulfill their own objectives, and dashboards for CIOs are usually the last to receive the attention they need to make them truly useful.

But the resources available to IT leaders extend beyond the business data important to LOB leaders. This includes facts that can be useful in analyzing the performance of IT assets and planning future initiatives.

While there is plenty of data across multiple domains, the issue is about identifying which data sets are the right ones.

IT leaders often don’t have the granular cost data specific to IT needed to make decisions and help the business pull levers. This data is critical to understanding IT spend, and rolling that into business value that is understood by the business. IT leaders who are able to demonstrate direct correlations between the systems they are responsible for and business initiatives can make solid cases about prioritization of resources and have more control over how budgets are allocated.

Finding the right data combination

Business process data, including financial and transactions, are analyzed most often for business purposes while many other datasets are frequently left untouched. They include clickstream data, IoT data, and possibly more important for IT—application and server log data. These types of data can prove rich sources for intelligent analytics and deep insights because they are derived from computing activities.

When combined with business transactions and enhanced by analytics, CIOs can use this data to deliver insights based on where computing resources are being used and in what business activities. But unless something draws attention to issues, they are likely to be missed. That’s where alerts come in.

AI can help surface issues by delivering three kinds of alerts. Each can be helpful in particular instances and deliver insights based on conditions. The CIO's opportunity is to connect these alerts to data sets and conditions that bridge the IT and business operations and demonstrate how changes are linked to IT efforts.

  • Absolute value alerts are triggered when predefined values are crossed. These are common and easily implemented when the target values have been identified. AI can be used to discover which values should be monitored for change, then those alerts fed back to other AI processes.
  • Relative value alerts are typically based on time series valuations such as when transaction levels are different from previous levels by a predefined percentage. AI can be looped into this process to manage the percentage that triggers an alert.
  • Neural network alerts use advanced AI techniques that attempt to mirror human brain processes and can provide insights based on both absolute and relative value triggers. In addition to simple alerts based on triggers, AI can deliver a confidence value that indicates a level of certainty that the CIO can use in their own analytical processes.

AI can bolster CIO efforts to deliver insights and predictions that let them adjust organization resources to accommodate business processes and concentrate their efforts on the highest value projects.

CIOs have advantages in that they can use detailed process data to augment and enhance business data. Their challenge is to determine which data can best serve the company’s needs and then to find ways to make use of those assets to drive business processes. Managing data overload with AI-driven analysis helps everyone understand how IT spending affects business efforts.

Using the right data in the right combinations, delivered in clear and actionable ways, can give IT executives an edge that helps them accelerate their enterprise business.

 

Scott Koegler has more than 20 years experience as a technology journalist and has written for publications including Network Computing, Forbes, Internet Evolution, and many others. He also practiced IT as a CIO for 15 years.