Real-time data and analytics are key to making better decisions, but their true potential is rarely reached. Are you making the most of real-time?
“Real time” is a phrase that gets used quite a bit these days. But what is it exactly, and how can companies truly take advantage of it?
In many cases in retail, for example, sell-out promotions could have been even more successful if there was a greater awareness of where additional stock may be within the system– a capability known as real-time inventory control (case studies here).
“If only your company had known the whereabouts of all its products in real time and married that with live purchasing information then maybe sales teams could have made the adjustments to re-route sales,” Fleming explains, calling it “a case of ‘not having true real time insights costing you business.”
This is one example of the “time gap” that exists across today’s enterprises, no matter how well wired they are, Fleming continues. With the rise of the Internet of Things and the multitude of sensors and devices coming online, that time gap will only increase.
Real-time data and decisions
The rise of IoT and big data analytics will exacerbate this time gap, Fleming predicts. Structuring real-time analytics for IoT “will require a new way of handling the exponential increase in data,” from gathering to processing to storage. IoT calls for a rethinking of the decision-making process,” he states. However, many of today’s solutions don’t deliver true real-time views.
“The user may be able to interact with the data in real time but if the data is old, then the insights are not a true reflection of events,” Fleming states. “It’s great to get actionable insights from your data but any action often needs to take place almost immediately.”
Things also have to be put in their proper perspective. Does it mean simply delivering information faster, or within a specified timeframe? “It used to be that when a customer or prospect asked you for real-time, what they really wanted was something faster than their apps and systems were performing at the time – so maybe this meant on the same day, instead of overnight, or maybe within an hour, instead of hours later.”
Gartner’s Roy Schulte, who has been studying and providing guidance on the real-time space for a number of years, recently provided his insights at Forbes. He notes that real-time analytics can play a key role in realizing real-time capabilities. “High performance analytics helps companies make better real-time operational decisions,” Schulte says. “But they can also be used to improve the quality of tactical and strategic decisions.”
Schulte offers the following advice for incorporating real-time analytics into decisions:
Move repeatable operational decisions to real-time: “Most real-time operational decisions are repeatable,” says Schulte. “For example, a scoring model used to approve credit card transactions may be developed once on historical data, and then used for evaluating real-time credit card transactions for days or weeks.”
However, this requires some legwork, he cautions, as operational decisions “that go from slow to near-real-time may require new software tools, new kinds of data, new business process designs, and other changes to the business.” Real-time analytics requires responding “to conditions as they are at the moment, not to process yesterday’s data or data from last month.”
Track and measure results: “It’s important to track the results to make sure the models are still working correctly and to modify rules and analytics frequently to get the best results as business conditions change,” Schulte says.
Keep humans in the loop: Machines and applications are fallible. “System logic should be used to check other systems, and people periodically should monitor systems,” Schulte advises, adding that a “stop” button should be part of the system, “so people can halt a rogue system quickly when a problem is detected, as well as “circuit breakers” to prevent system overloads.
Use continuous intelligence: “Continuous intelligence monitoring systems run all day, listening to events as they occur, until they detect a threat or opportunity that requires a response by a person or system,” Schulte explains. “Continuous intelligence provides a common operating picture across the enterprise. Each person involved in a situation may have a personalized view specific to their role within the organization, but providing the real-time analytics across the organization ensures that all involved have the same understanding of a situation.”