Gamification. Web scraping. Behavioral analytics. A recent article inHarvard Business Review (HBR) outlines three methods that may be poised to compete with good old hiring tactics. Does the traditional face-to-face interview even stand a chance against algorithms that turn your prospective employee’s online activity into a quantitative estimate of job potential or fit? These assessment
Big data is, well, big. The term has gotten lots of buzz the past few years. But it’s big in other ways as well. According to McKinsey big data is defined as “datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze.” A 2014 Forbes article has
Many organizations that jumped on the big data bandwagon have struggled to turn their new, boundless collection of data into actionable business information. As consultant Rich Sherman of Athena IT Solutions puts it, today’s businesses are struggling with “the transformation of data into information that is comprehensive, consistent, correct and current.” Enter data governance programs,
Big data is big. Over the past two years alone more than 90% of the world’s data has been created. Each day more than 2.5 quintillion bytes of data are created. For those who are more numerically inclined that is more than 2,500,000,000,000,000,000 bytes per day. Companies are spending big money to determine how they
Analytics is good for business — as long as you can make sense of it. Does your business suffer from a case of data overload? Or do you steer clear of new investments in supply chain analytics because you are afraid they could yield more data than your business can handle? You are in good
The battle for competitiveness in the cloud. In this age of radical transformation for supply chains, top companies are tying together prevailing concepts, like big data and the Internet of Things (IoT), with cloud-based computing. Supply chains are being reimagined as digital networks that track not only physical goods, but also people, data, and money.
From coffee makers to urban design, the Internet of Things (IoT) is affecting change in virtually all aspects of daily life. And even though the IoT is still at the early-adopter stage, in just five years 50 billion devices are projected to be connected to the Internet, generating an estimated $2 trillion to $14 trillion
This article is part of a series of articles written by MBA students and graduates from the University of New Hampshire Peter T. Paul College of Business and Economics. Josh Hutchins received his B.S. in Business Administration from the University of New Hampshire in 2005. He is currently pursuing his MBA at the Peter T. Paul School at the University of
Concurrent with the extraordinary rise of the Internet of Things (IoT), predictive analytics are gaining in popularity. With an increasing number of companies learning to master the precursors to developing predictive models — namely, connecting, monitoring, and analyzing — we can safely assume the art of gleaning business intelligence from foresight will continue to grow rapidly.
A distribution center struggling with a high number of forklift truck impacts found a way to leverage big data to address a nagging, costly warehouse issue. The company had installed a telematics solution on its forklift trucks, but could not determine the cause of the impacts. The time and location of impacts were known, as
“[Companies] don’t know how to manage it, analyze it in ways that enhance their understanding, and then make changes in response to new insights… they don’t magically develop those competencies just because they’ve invested in high-end analytics tools.” –You May Not Need Big Data After All” Harvard Business Review, December 2013 Since the concept of
The Internet of Things (IoT) is ubiquitous. Because of this it can seem abstruse. Puneet Mehta does a great job of putting the concept in layman’s terms: “[A] plethora of “dumb” objects becom[ing] connected, sending signals to each other and alerts to our phones, and creating mounds of “little data” on all of us that
