I was reading about this very interesting research which studied decision makers’ use of data feeds having varying frequencies. As illogical is it may sound, in some environments real-time data could hamper decision making and/or lead to a wrong decision.
At first thought this seems unbelievable; until you realize how much data the human mind can comprehend and process. It really does not take much data to fog up our cerebral processing.
Additionally, with real-time data we can loose the context of the data points. Dips, valleys, peaks, plateaus are all only found with historical views. To predict a dip with most real-time data feeds is more like gambling. As the researchers mention in many cases real-time data turns into noise. In many of our cases the real-time data is more of a technological gimmick or a visually stunning graph. More often than not when we hear a client request real-time data processing for an analytic solution we know that we need to drill-down a bit more and figure out the true needs and requirements. It is nice that know that some researchers finally spent some time determining why so many of our real-time systems are not useful or helpful.
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“In many situations, real-time data comes in on a continuous basis, and then you, as a decision maker, have to decide which data is information and which is pure noise,” says Jayashankar M. Swaminathan, Kay and Van Weatherspoon Distinguished Professor of Operations, Technology and Innovation Management at the University of North Carolina’s Kenan-Flagler Business School. “That’s not an easy task, which is what this study shows.”
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Lurie and Swaminathan found that participants who received reports and placed orders daily had lower profits than their peers who got reports once or twice weekly. To put it another way: Even though all the participants received the same granularity of information — daily sales — those who got the information every day, as opposed to every three or six days, made worse decisions. This was particularly true when there was a high variance in actual demand.
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