Grouped Sensor-Driven Asset Intelligence Goes to Work
Boost the Top and Bottom Line for Reusable Packaging Containers
By Sanjay Sharma, CEO of Roambee
As conversations surrounding sustainability are more relevant than ever, the packaging industry is often a key player mentioned. Many companies – especially those in the automotive, food, and chemical industries rely on reusable packaging to safely transport materials, reduce cost, and to contribute to a healthier supply chain.
While reusable packaging is becoming a favorable practice, there are often challenges associated with it – including theft, and poor utilization for users, operators, and renters. The American Bakers Association estimates the baking sector alone in the US spends more than $10 million annually in plastic tray replacement costs due to theft. Additionally, about 10-15% of returnable transport items (RTIs) are lost in transit, are not returned, or become unusable in any other way as per the “The effect of asset visibility on managing returnable transport items” published in the International Journal of Physical Distribution & Logistics Management.
Although these challenges seem overwhelming, especially on such a large scale, there are specific measures to combat a supply chain disaster associated with theft and damage, bridging the gaps within the supply chain. It is through the use of “grouped” sensor-driven asset intelligence that companies can meet unit economics of deriving visibility and insight into their reusable packaging container (RPC) inventory.
In addition, the key value the customer gains is the availability of RPCs when required and aligned with their demand/shipment plans. Coupled with the use of innovative “grouped” sensor-driven asset intelligence, companies will be better equipped to eliminate losses, and transform their asset utilization – directly impacting the bottom and toplines in the regions deployed.
Sensor-driven asset intelligence will not only improve efficiency and customer satisfaction. It can also improve work culture, boost team productivity, and the quality of life for field asset management professionals. By providing customer and geography-based real-time intelligence, sensor-driven assets can also eliminate crisis situations and ad-hoc travel to gather on-ground intelligence about aging assets. Recent studies have also found that early adopters of AI in supply chain management saw a decrease in logistics costs of 15%, an increase in inventory levels of 35%, and a boost in service levels of 65%.
“Grouped” sensor-driven asset intelligence at work
There is always a chance for asset loss or theft when RPCs are unattended at third-party warehouses. The longer an asset is idle in a location without proper supervision, the greater the risk of loss or theft.
Unfortunately, it is impossible to monitor materials at all times within the supply chain. The objective should always be to reduce the amount of time an RPC is unattended at a third-party warehouse as a first line of defense. However, this may be completely out of a company’s control. Another option is to focus on the replacement and protection of future assets. Insuring assets can not only save businesses headaches, but also a great deal of money and energy. However, insurance leads to increased premiums if loss is not curbed.
The most common solution in the market for operational supply chain asset visibility, such as RPCs, is to tag every RPC with an RFID tag, Bluetooth Low Energy (BLE) tag, or a direct-to-cloud GPS tracker. While this is the recommended approach, there are important aspects to consider:
- RFID solutions require intensive infrastructure at customer locations
- GPS direct-to-cloud asset trackers require no infrastructure, but they don’t justify unit economics: Tagging millions of assets worth just $10 to $50 with GPS trackers that cost more than the asset does not justify the return on investment (ROI)
- Even if there was a way to tag every asset with GPS, there can be challenges of cognitive overload in making sense of the exception alerts at scale.
Here is where sensor-driven “grouped” asset intelligence innovation comes into play. First, by placing direct-to-cloud GPS sensors to just a few assets and using purpose-built visibility platforms, companies can extend the sensor battery life to years. Artificial intelligence (AI) and Machine Learning (ML) can then be used to predict the presence or absence of a certain group of assets against service-level agreements (SLAs), generating clear, actionable, aggregated business signals for effective utilization and mitigating security risk.
Some aggregated business signals include:
- Loss/theft of asset groups
- Unauthorized use of asset groups
- Aging of asset groups
- Full/empty status of an RPCs based on location intelligence on the stage of the cycle in a facility
- Cold chain Quality Control (QC) prediction if assets were used in a cold chain environment
- Chain of custody breach of assets and product shipped
- Delivery window scheduling for drop off, pick-up, and customers’ product shipments
- Assets available for product shipping
- Order fulfillment of asset groups
- Revenue recognition of asset groups
With innovative “grouped” sensor-driven intelligence, RPC suppliers can have the information they need to intervene early, rescue RPCs from losses or SLA breaches, better route RPCs, dynamically price RPC rentals, and identify which service centers to target to reduce downtime and increase RPC utilization. Sensor-driven intelligence is transforming the benefits of packaging suppliers, operators and users.
About the Author
Sanjay Sharma is a strategic thought leader with two decades of entrepreneurial experience building technology startups from the ground up. As CEO of Roambee, he is responsible for leading the company’s vision, driving its worldwide business growth, and increasing the company’s value. Sanjay has successfully co-founded and led two successful Silicon Valley B2B technology venture-backed startups with successful exits – KeyTone Technologies, which was acquired by Global Asset Tracking Ltd and Plexus Technologies, which became an ICICI Ventures portfolio company. He has also been a part of the engineering teams at EMC, Schlumberger, and NASA.