Through what are destined to become "basic" algorithms, computer software can tell more than we once thought about us and what once sounded like science fiction is now a reality that we are increasingly comfortable with. Mary Shacklett, whose utilized data collection to forecast consumer behavior for a supply chain risk avoidance project, expands on the Orwellian at Yahoo, giving us a clearer insight into the pros and cons of big data. Explaining the project she worked on, Shacklett writes that the ways that big data mines for information and creates narratives through her own experience on the supply chain project. "One solution evaluated was a third-party analytics tool that collected GPS, weather, economic, financial, and political data from around the world, and then combined it with detail related to specific suppliers, such as their individual financial health and capability, as well as their criticality with respect to the urgency of components they provided to enterprise supply chains." There are always pitfalls, of course, and while the story of the Mars Climate Orbiter's problems is one high-profile example, a more resounding risk may be governments and companies haphazardly collecting data from inaccurate samples. While often successful for charitable efforts to help with disaster relief, this mode of data collection may not be uniform, or even understood, enough for flawless (or even flaw-lite) decision making. "Analytics is like a comprehensive menu," says Mark Stevenson, Data Analytics Recruitment Specialist at the tech-focused Salt. "Heed the data but use your gut."