Magpie Sensing, a start-up project under Ebers Smith and Douglas Associated LLC, provides a suite of cold chain monitoring and analysis technologies for the healthcare industry. It is a shippable, wireless temperature and humidity monitor that provides real-time, location-aware tracking of cold chain products during shipment. Magpie Sensing’s solutions rely on rich analytics algorithms that leverage the data gathered from the monitoring devices to improve the efficiency of cold chain processes and predict cold storage problems before they occur. Magpie sensing applies all three types of analytical techniques—descriptive, predictive, and prescriptive analytics—to turn the raw data returned from the monitoring devices into actionable recommendations and warnings. The properties of the cold storage system, which include the set point of the storage system’s thermostat, the typical range of temperature values in the storage system, and the duty cycle of the system’s compressor, are monitored and reported in real time. This information helps trained personnel to ensure that the storage unit is properly configured to store a particular product. All the temperature information is displayed on a Web dashboard that shows a graph of the temperature inside the specific storage unit. Based on information derived from the monitoring devices, Magpie’s predictive analytic algorithms can determine the set point of the storage unit’s thermostat and alert the system’s users if the system is incorrectly configured, depending upon the various types of products stored. This offers a solution to the users of consumer refrigerators where the thermostat is not temperature graded. Magpie’s system also sends alerts about possible temperature violations based on the storage unit’s average temperature and subsequent compressor cycle runs, which may drop the temperature below the freezing point. Magpie’s predictive analytics further report possible human errors, such as failure to shut the storage unit doors or the presence of an incomplete seal, by analyzing the temperature trend and alerting users via Web interface, text message, or audible alert before the temperature bounds are actually violated. In a similar way, a compressor or a power failure can be detected; the estimated time before the storage unit reaches an unsafe temperature also is reported, which prepares the users to look for backup solutions such as using dry ice to restore power.

Questions for the Opening Vignette
1. What information is provided by the descriptive analytics employed at Magpie Sensing?
2. What type of support is provided by the predictive analytics employed at Magpie Sensing?
3. How does prescriptive analytics help in business decision making?
4. In what ways can actionable information be reported in real time to concerned users of the system?
5. In what other situations might real-time monitoring applications be needed?