Incorporating the Internet of Things as Part of a Digital Supply Chain Strategy

Sean T. Riley, Global Manufacturing & Supply Chain Solutions Director, SOFTWARE AG USA
Sean T. Riley, Global Manufacturing & Supply Chain Solutions Director, SOFTWARE AG USA

Sean T. Riley, Global Manufacturing & Supply Chain Solutions Director, SOFTWARE AG USA

The Internet of Things (IoT) is receiving a significant amount of attention and for good reason; it has the ability to enable extreme innovation for manufacturers’ supply chains. This doesn’t mean that IoT is going to revolutionize the supply chain industry on its own, but it does provide supply chain practitioners with the ability to understand specific actions in a supply chain with precision never before realized. When that is coupled with the ability to continuously analyze that data with streaming analytics, a new platform for innovation rises. This is why IoT is going to become an urgent priority for IT executives.

"In the supply chain industry, IoT data is produced by embedding sensors into transportation assets, shipping containers, production equipment, dedicated monitoring devices and material handling"

In the supply chain industry, IoT data is produced by embedding sensors into transportation assets, shipping containers, production equipment, dedicated monitoring devices, material handling equipment and products, better known as raw materials or finished goods inventory. These sensors can collect a myriad of measurements including temperature, humidity and vibration data from monitoring devices, Telematics data from transportation assets, performance data from production equipment, inventory usage rates, positioning and precise GPS data of both equipment operators in a facility and transportation or inventory assets around the world.

While this type of data has been available for years, the ability to have the data automatically transmitted, accessed by multiple partners and analyzed in real time has not. Additionally, this type of data is quite different than barcodes and radio frequency identification (RFID). Both bar codes and RFID are complacent and require interaction with a scanner to transmit data. The scanner itself records or transmits the data, which means the data contained can only be accessed at certain points of a process, whenever a scanner is contacted. With IoT, data is auto-generated on a set time frame by the embedded device itself. It does not require a separate device to collect or transmit data at certain points. This is what makes this data so uniquely important. Independently, IoT data doesn’t drive a significant advantage but when utilized in context with other pieces of data and continuously analyzed to drive immediate action it becomes an integral part of the digital supply chain.

The digital supply chain combines IoT data with application process execution software (ERP, WMS, TMS), partner messages (responses and updates) and event data (weather, traffic, political/ labor strife) where the “fast moving data” is then continuously analyzed with the “slow data” to produce scalable, automated efficiencies.

For example, a ship holding 10,000 containers is headed to port. To relieve congestion, reduce idle time and decrease fuel costs, a ship can be told to decrease its speed so that it synchronizes its arrival with the ability to unload the containers and ship them inland. Through continuous analysis of GPS data combined with application data, trucks arriving to deliver the containers to their destination can also arrive exactly on time and synchronized in a specific order to match the containers as they are being unloaded, cleared through customs and sent on their way. If a container is arriving late, distribution center schedules are updated, transportation assets are redirected, customer or production deliveries are modified and the impact is mitigated. This is all completed based on a series of alerts and dynamic exception processes that serve as guides with the most routine portions of the exception processes automated.

Traditionally, supply chain practitioners have not considered the exact synchronization of assets as high priority since the amount of efforts and time required to complete this manually far outweighed the benefits. Secondly, the data needed to manage this excursion was not available. Messages and files sent between partners did not occur at the right frequency to make this type of synchronization possible. Most importantly, the time lapse between the time a message is sent and when the asset is received allowed for unplanned exceptions to occur.

While this is a single example, this same type of principle can be applied to purchase order (PO) fulfillment. Rather than relying upon acknowledgement of a PO, updated inventory and advance ship notices (ASN), IoT allows a digital supply chain practitioner to receive those messages and monitor the supplier’s readiness level from inventory orders to available inventory to production yield in real time. Lastly, the supplier would send an ASN but the actual container and shipping assets with embedded sensors will provide the basis for understanding when that container is going to actually arrive, the current temperature it is maintaining and the amount of vibration sustained from transport and handling that could impact product quality. Continuous analysis of this data allows for not only exact synchronization and scheduling but also the ability to stop product quality issues before they are received for inspection which results in a more efficient, streamlined supply chain.

For the IT executive, this means that there is going to be more data generated than imagined. This brings forward two immediate concerns: data security and continuous analysis. Data security can be managed by leveraging existing integration tools and combining them with new data collection vendors. The massive amounts of streaming data require a continuous analytic engine that is robust enough to analyze this amount of data to drive action. Lastly, this same continuous analytic engine should also be used to monitor the responses to these exceptions. Response monitoring and efficient, accurate management will become as critical as exception identification in the digital supply chain as that is what converts identification to customer or enterprise value.

The Internet of Things will be a critical enabler to the digital supply chain which will initiate a new approach of conducting business for manufacturers because of its ability to reduce costs, improve customer service and enable scalable revenue growth -- and the supply chain is only one area that will be significantly impacted. IT executives should start focusing now on how this development will impact their own infrastructure and future planning processes.

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