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AIoT for Inventory Management and Planning

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Leveraging AIoT for Inventory Management Transformation

There is no doubt that the AI-enabled Internet of Things (IoT) has the capability to transform the way supply chains run significantly. This is why we will cover this aspect, among others, in our November research report, Inventory Planning and Optimization State of The Market. While we predominantly think of the usage of AIoT in digital twins in a supply chain context, AIoT can potentially significantly impact inventory planning processes within supply chains. This article briefly touches upon three areas where AIoT adds value to the inventory management and planning process. A key point that I believe I should highlight is that while many SCM professionals have the notion that these applications are futuristic, in reality, many organizations are already leveraging the power of IoT in their supply chain planning.  You can find examples from the SAP technology world in the appendix section of this article. With the background developed from the context above, let us explore three applications of IoT in the area of Inventory Management:

Shelf Inventory Management

Leveraging sensors on shelves to identify the level of on-the-shelf inventory in-store can be used to create a process where the products can be ordered automatically. Taking it further, stocks level on retail shelves, stockrooms, distribution centers, and other storage facilities can be linked and viewed theoretically on a real-time basis. With this infrastructure in place, you can also optimize your returns by re-routing returns to stores where there is demand rather than re-routing to the warehouse. But think about the opportunities to develop game-changing replenishment planning algorithms.

Pipeline Inventory tracking

Logistics containers leveraging IoT technology are already being leveraged by shipping companies. There are many different levels of sophistication of sensors used in the tracking of containers. Some log data for download at a later point, while others can use GPS technology to provide real-time tracking, alerts when the door has been opened, or environmental parameters have been exceeded (ex: temperature).

From an Inventory Management perspective, integrating these sensors with a cohesive Inventory management system and gaining visibility into the consignment within the container will provide real-time visibility into pipeline inventory, which is often used in the inventory position calculation. Also, this tracking will also flag any issues with the transportation lead time, which is one of the inputs in safety stock calculation. Many supply chain visibility platforms provide this level of visibility on their platforms.

Inventory Optimization

IoT technology, as mentioned above, can help track key parameters that are frequently used in Inventory calculations like demand, lead time, on-hand inventory, pipeline inventory etc. Integrating data generated by these sensors with an Inventory monitoring and optimization tool in the cloud and then allowing the tool and an intelligent algorithm to place orders will help significantly minimize stockouts and Inventory costs. With sufficient infrastructure, you can develop an automated pipeline to an inventory optimization tool that runs automatically at periodic intervals to generate tactical inventory plans.

What does this mean for SAPinsiders?

Before you make that leap into the IoT world, consider if you can prudently leverage your existing digital tracking capabilities. Getting value out of digital technologies is more about people and processes and less about the technology itself. It is imperative that you have the organizational capability to harness value from digital tracking, whether it is RFID or IoT.

The next key step is to put a robust infrastructure in place to collect and manage data from edge devices. Though the real differentiator, analytics will be relatively easier to implement if you have a centralized and integral dataset. Data that can not be put to use is of no value at all.

Leverage edge computing and TinyML to inject “smart” capabilities in your edge devices. This will allow you to build much smarter capabilities. Remember that many of the tracking aspects are already being covered by RFID technology. In my perspective, the real value is in leveraging these edge devices for some “instant analytics” and pairing that with centralized analytics algorithms.


 

Likes of Accenture and Deloitte have been partnering with SAP to help their customers use the power of IoT to transform their planning processes. Below are links to a few examples illustrating how SAP solutions leveraging the power of IoT transformed inventory planning processes:

https://www.accenture.com/_acnmedia/pdf-91/accenture-lsfl-iot-point-of-sale.pdf

https://www.accenture.com/_acnmedia/pdf-89/accenture-augmented-warehouse-video-transcript.pdf

https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Technology/gx-iot-predictive-analytics-2017.pdf

https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Technology/gx-tech-connected-goods-accelerator.pdf

 

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