One of the lasting changes from the COVID-19 pandemic is rethinking how companies address supply chain risk. Underpinned by technologies, risk analytics have become embedded in supply chain decision-making, offering a competitive advantage of a more agile and resilient supply chain than their competition.
Supply chain management and transport teams are now demanding information beyond ‘where is my shipment’ to ‘when will it arrive at the next stop?’ and ‘are there any risks of a delay?’ As such, the ability to predict shipment ETAs has become increasingly valuable.
However, their accuracy and reliability depend heavily on the quality of the data captured and the sophistication of the technology and computational methodology used.
In this article, we will explore why data quality is essential for RTTV platform performance, both in calculating predictive ETAs and carrying out comprehensive analyses on flows to generate and leverage it for comprehensive analyses on flows and generate valuable insights into a supply chain’s operations and processes.
The challenges posed by lack of data
When shippers experience delays in getting shipments out for delivery or use resource-intensive communication to reach teams and customers, it degrades the experience and decreases efficiency. If issues occur on the production line or stock runs out, it causes operational and planning headaches for supply chain managers. This can have a knock-on effect if delays occur due to docking bay mismanagement and congestion at ports. All of these are issues that, in the current climate, shippers would ideally love to avoid.
The need for quality data
The ability to track an item in the supply chain as it moves in real-time is becoming increasingly accessible with the availability of faster and more reliable connectivity, cost-effective IoT devices, and more compatible systems and software platforms.
For organizations, it makes sense that visibility of operations can be achieved by having access to better operational data, supporting decision-making with analytics, and improving operational capabilities.
When data is collected manually from various sources, it is often incomplete and untrue. Therefore, collecting data for all shipments at every stage of the supply chain can be difficult. Capturing the quality data needed to take action is even more complicated. However, while this situation is not new, customers’ expectations regarding visibility are growing.
That is why accurate, reliable, and automated data monitoring can save a considerable amount of time in manual processes—enabling shippers to generate more insights and be more reactive, which is a significant competitive advantage in today's global industry.
The components of data quality
Quality data must come from quality sources to ensure accurate and reliable outputs, like ETA predictions or other network and operational performance insights. This quality measures the condition of data based on factors such as accuracy, completeness, consistency, reliability, latency, and many other factors.
The quality of the data captured influences several factors, including GPS signal, the nature of the location tracking technologies used, and frequency of data collection. However, one of the fundamental influences of overall data quality is consistent data flow into the platform because inconsistent data means gaps in overall visibility.
Conclusion
By connecting data from previously siloed sources across all modes - sea, air, FTL & LTL, rail, etc.- and bringing it together using APIs, using a real-time visibility platform provides end-to-end visibility across your entire supply chain.
Shippeo monitors inbound data to ensure it’s of high quality. The platform applies data transformation techniques to raw data to provide high-quality data outputs.
Achieving end-to-end transportation visibility is a complex puzzle. But Shippeo helps to piece together your entire supply chain ecosystem thanks to a unique platform enriched with reliable and accurate data.
Learn how Shippeo automatically captures real-time transport network data and transforms it into predictive ETAs with market-leading accuracy and reliability.
Curious to find out more about real-time visibility and data? Check out our other blogs:
6 reasons why real-time visibility is important for supply chain execution
From ‘blurry’ to ‘focused’: Real-time visibility project success relies on high-quality tracking data
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