IoT Analytics and Cold Chain Management – A Powerful Use Case

IoT Analytics and Cold Chain Management

INTRODUCTION

Among the many use cases we have come across this year in our close collaboration with customers on IoT Analytics is Cold Chain Management.  Maintaining unbroken temperature control over food and pharmaceuticals is mission-critical in the food service and life sciences industries.  IoT Analytics can monitor and manage these cold chains to ensure problems are avoided or mitigated.  For example, a restaurant chain can get alerted to real problems like a food shipment sitting on a loading dock in the heat.  Pharmaceutical companies can ensure that drugs are maintained at the proper temperature at every step during the process as they are shipped from the factory to medical offices.  There are many more specific use cases that are quite familiar to supply chain professionals in these industries.

COLD CHAIN MANAGEMENT TRENDS RAISING THE STAKES

Cold Chain Management has become even more complex in recent years as a result of a series of underlying business trends.  The two most prominent are:

  • The rapid increase in customer expectations as globalization has increased choices
  • Complex supply chains that involve multi-sourcing and a much wider array of players

Both of these trends increase risk substantially for the providers of pharmaceutical and food products, and means that new solutions for cold chain management must be brought to bear to meet the many challenges caused by these secular trends.

COLD CHAIN MANAGEMENT – A MODEL TO INCREASE VALUE WITH IoT ANALYTICS

Leveraging IoT and Analytics to address these challenges is not a simple process.  Careful thought and planning are required to capture business value successfully.  Our experience with customers has taught us that a straightforward three step model is usually a good approach.

Step One

The first step with IoT Analytics and Cold Chain Management is to get the basic infrastructure in place in order to be aware of the status and issues along a cold chain.  Sensors are installed in all key transportation juncture points, and data is collected.  This first step enables analytics on historical information and auditing of problems and issues.  These initial steps are useful, but the overall utility is limited because the data is consumed and analyzed only after the fact, which minimizes the opportunities to prevent problems in the first place – which is much more valuable

Step Two

IoT sensors and devices are a good start, but the data collected in Step One needs visibility, context, and possible action to be truly valuable.  In the second stage of evolution of cold chain management with IoT, operators and managers need to have the ability to understand problems in real-time and take action to minimize damage.  One of the clearest examples of this is when shipping containers experience temperature fluctuations over time that lead to spoiling of the goods inside.  In this example managers can stop the shipment in its tracks, and turn it back to its source for remediation. In these cases, the end customer is never exposed to spoiled goods. As a result, all parties have more lead time to deal with the potential shortages or stock out that typically result from these types of spoilage.

Step Three

In the third and most advanced stage of the application of IoT Analytics to Cold Chain Management, managers will be able to not only detect problems in real-time as in stage two, but actually be forewarned about possible problems in advance before the problem becomes acute and causes waste. The key is preventative action.  At this stage, the real-time analytics systems – and associated sensor hardware – have evolved to the point of providing highly acute information in real-time. These types of advanced IoT Analytics systems can provide warnings so that preventative action can be taken to fix a cold storage or transportation unit even while it is in transit.  In these use cases, the ambitious goal is to completely avoid spoilage vs. being made aware of it after the fact, ensuring smooth and consistent operations.

Vitria VIA IoT Analytics Platform for Cold Chain Management

As outlined above, meeting the market demands and requirements of modern cold chain management is not easy.  Market competition and the system level demands required to meet them are a steep hill to climb.  Vitria has worked closely with a number of prospects and customers and is continuing to learn and improve our focus on handling all the critical use cases for cold chain management.  We have been pleased to learn from the market that our quickly maturing VIA IoT Analytics Platform is capable of addressing some of their most difficult problems.

VIA is a comprehensive IoT Analytics Platform that includes a unified set of capabilities for cold chain management:

  • Real-Time monitoring, management, and implementation of preemptive actions to maintain the integrity of cold chains.
  • Continuous monitoring of sensors located throughout the supply chain and alerting of any condition defined as critical or needing attention
  • Predictive & prescriptive analytics in the platform leverage historical and real-time data to recommend actions to prevent temperature anomalies or control problems from causing spoilage or waste.

Summary – Cold Chain Customer Benefits

Vitria VIA delivers the following key benefits for cold chain managers:

  • Enhanced safety and reduced risks and liability for producers who must maintain strict quality control
  • Increased customer satisfaction as potential quality problems are prevented entirely
  • Major reductions in operational costs associated with shipment returns and re-shipments

To learn more about how VIA can help you address your Cold Chain Management Challenges, visit our platform page or contact us.

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