Big data, while vast, has its limitations. As time goes on, executives might consider putting a longer time scale on their analysis when making decisions.
The era of big data, the term used to describe data sets so large and complex that it is difficult to comprehend, is alive and well. Marketers use data to glean insights into consumers, while political pollsters use large data sets to categorize and target voters.
In business, the big data craze is equally strong. In human resources, executives leverage human capital analytics to measure and make workforce decisions.
But big data also has its limitations. According to Samuel Arbesman, senior scholar at the Ewing Marion Kauffman Foundation, an education and entrepreneurship research foundation, there’s another class of data worth paying attention to: long data.
Arbesman, an applied mathematician and network scientist, says that the long data concept will play a major role in the future analysis of human existence and other subjects with deep histories.
And as businesses continuous to collect vast troves of data, long data is likely to become a valued tool to study trends that affect every organization’s workforce, products and services.
Talent Management spoke with Arbesman on the concept. Following are some edited excerpts:What is long data, and how is it different from big data?
Big data, as we’re all familiar with, is just vast amounts of information — whether or not it’s data from cars, from your cellphone or from medical devices. And the idea is by using this large amount of data you can extract anything you want. It’s been very, very powerful. The problem, though, with big data is that often even though it’s very rich and might cut across a wide cross-section of humanity and various situations, it doesn’t have a long time scale.
So for example, let’s say you’re trying to understand how people move around or how people interact with each other. And so you’re using cellphone data, you’re using big data from mobile phones. You often only have maybe data over the course of days, weeks or months, or if you’re lucky maybe a year or two. The problem is, though, that that’s essentially a snapshot of humanity; you don’t actually see people, interact or do what they do over swaths of time. And so when I think about long data, I think about trying to see sort of these long patterns over vast reaches of time relative to human civilization.