Methods such as Statistical Process Control, Lean and Six Sigma have been in use for decades, helping manufacturers maximize the efficiency and reliability of their processes. But when it comes to complex, global supply chains, a lack of data has limited the effectiveness of these tools.
Today, access to new data sources — particularly Internet of Things data — is making it possible for supply chain professionals to adapt many of these same methodologies to improve supply chains.
As companies begin integrating IoT technology into the supply chain, managers are gaining real-time access to huge amounts of data. Always-connected sensors monitor location, temperature, rough handling and other key metrics, and share all that data via the cloud in real time.
This kind of access to data not only enables managers to solve immediate problems, but it also paves the way for supply chain analysis and efficiency on a macro scale. That’s because businesses can gain access to real-time location and condition data for their in-transit goods.
These IoT solutions combine onboard sensors and cloud-based monitoring to give supply chain managers the data necessary to implement these optimization tools. But how do these data-driven tools actually make a difference?
Here are three key benefits of the IoT-powered data-driven supply chain:
- Improve Inventory Management: Analysis of data that shows exactly where shipments are at every point — and how long they take to complete each leg — make it possible to implement targeted increases in safety stock (excess inventory that companies rely on to meet fluctuations in demand or replace inventory that is lost due to unexpected in-transit damages or delays) at critical vulnerability points along the supply chain and remove excess safety stock in other parts of the chain. For example, if location data across hundreds of shipments indicate that inventory tends to arrive late at a certain distribution center on certain days, inventory can be allocated from another facility and/or schedules can be adjusted to account for the predictable delay.
- Reduce Damages: With real-time visibility into when and where damages caused by temperature excursions or rough handling are occurring, managers can design strategic processes to eliminate the root cause of these issues. For example, if data indicate that packages are most likely to experience damages at a particular location or time of day, the supply chain manager can work with the carrier to develop an alternate route that avoids the problem area.
- Minimize Delays: A quantitative analysis of trip durations can shed light on exactly when and where delays are originating, giving managers the insights they need to solve the problem. For example, a shipment arriving late may be a one-time issue, or a recurring problem. If it’s a recurring problem, it may be because of last-leg delays, or excessive processing time between legs of a route, or because the carrier uses a different route on certain days.
Understanding the timing and precise route of every shipment makes it possible to address problems based on data, not guesses.
Ultimately, greater visibility into the data behind a supply chain makes it possible to integrate established methods such as SPC, Lean and Six Sigma into a comprehensive supply chain management strategy to improve operations from end to end.
Tive Inc. provides sensor-driven tracking services to deliver visibility into products as they move through the supply chain.