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34 Part I • Decision Making and Analytics: An Overview

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 dash-
board that shows a graph of the temperature inside the specific storage unit.
Based on information derived from the monitoring devices, Magpie’s predictive ana-
lytic 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 pos-
sible temperature violations based on the storage unit’s average temperature and subse-
quent 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 tempera-
ture 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 tem-
perature also is reported, which prepares the users to look for backup solutions such as
using dry ice to restore power.
In addition to predictive analytics, Magpie Sensing’s analytics systems can provide
prescriptive recommendations for improving the cold storage processes and business
decision making. Prescriptive analytics help users dial in the optimal temperature setting,
which helps to achieve the right balance between freezing and spoilage risk; this, in turn,
provides a cushion-time to react to the situation before the products spoil. Its prescriptive
analytics also gather useful meta-information on cold storage units, including the times of
day that are busiest and periods where the system’s doors are opened, which can be used
to provide additional design plans and institutional policies that ensure that the system is
being properly maintained and not overused.
Furthermore, prescriptive analytics can be used to guide equipment purchase deci-
sions by constantly analyzing the performance of current storage units. Based on the
storage system’s efficiency, decisions on distributing the products across available storage
units can be made based on the product’s sensitivity.
Using Magpie Sensing’s cold chain analytics, additional manufacturing time and
expenditure can be eliminated by ensuring that product safety can be secured throughout
the supply chain and effective products can be administered to the patients. Compliance
with state and federal safety regulations can be better achieved through automatic data
gathering and reporting about the products involved in the cold chain.

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?
What We can Learn frOm this vignette

This vignette illustrates how data from a business process can be used to generate insights
at various levels. First, the graphical analysis of the data (termed reporting analytics) allows

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