December 10, 1963 – February 27, 2024
As Halloween approaches, interest in spooky ghosties increases as much as the Golden Gate’s wind speed. So we took this opportunity to speak to three paranormal investigators, two skeptics, and a physicist in an attempt to examine the supernatural in terms of what we know best: data.
Retail operates in time and space. So although we frequently hear about the psychology of retail, the physiology of retail is often overlooked—and it matters. Both the buying and selling of goods and services operate in the same complex universe of space-time as we physical humans do.
At the end of each year, Spotify packages and presents data to its users with a marketing campaign called Spotify Wrapped. The data that Spotify gathers from its users are given back to its users in such a way that the users themselves have proven enthusiastic users of that data. This includes not just who your favorite musician or group is, but also indicates what percentile rank you fall into. For instance, you may prove to be not just a top Taylor Swift fan, but rather a “top 1% fan.” This information is sent to users in a graphically attractive package designed to share on social media.
Delight as a marketing and data strategy may seem counterintuitive, given how much hard numbers have been the coin of the realm, but several companies have proven its utility.
Cognitive bias is a bit of a loaded term. It can be a problem for companies striving to become more data-driven, although many cognitive biases are the flip side of an often useful thought process.
A cognitive bias is what Oliver Sibony, author of You’re About to Make a Terrible Mistake!1 and professor at HEC Paris, calls a heuristic gone bad.
When Winter Storm Uri hit Texas in February of 2021, it crashed all the state’s systems. It did grave damage to the state’s unusual power grid, but it also stressed manufacturers, retailers, and customers. It did so in part because American business has for some time relied on what is called just-in-time (JIT) logistics.
What have crises taught us about the utility and the limitations of JIT logistics? What needs to be changed to retain the virtues of the method? How can organizations insure themselves against JIT’s drawbacks? According to logistics experts, the key is to understand what JIT really means.
