What data quality means
Data that is high quality creates trust. Anything less creates distrust — which leads to second-guessing, manual re-checking, and an inability to rely on automated monitoring. With trusted data, you escape the cycle of distrust and manual effort and can finally unlock the full benefits of automation.
For us, the kind of data quality that operations teams can trust is made up of four dimensions:
- Completeness: All points are consistently present
- Timeliness: It is reported as close as possible to when the real world event occurs
- Accuracy: It is correct
- Standardization: It adheres to a consistent format
At OpenTrack, we dedicate significant effort and resources to ensure high-quality data across all dimensions. Our approach involves:
Completeness
Some carriers don’t consistently report departure or arrival milestones. Some don’t report the terminal at port of discharge. By tapping into multiple data sources, we’re able fill in these gaps and deliver a consistent, complete experience, no matter which carriers you book with.
Timeliness
Good data is one thing, but it’s only useful if you get it in real time. By prioritizing push integrations and tapping into multiple different kinds of data sources, we’re able to capture events close to when they actually occur.
Accuracy
Accessing a multitude of high quality data sources helps with completeness and timeliness, but it presents a challenge: what to do when data sources report conflicting accounts of the same event?
For example, imagine a steamship line and a terminal are reporting different ETAs, or reporting that the same container out-gated at different times.
By leveraging statistical models, human intelligence and machine learning, we’ve trained the system to select the most accurate data or make the best prediction when none of the providers are deemed to be credible. Our system detects an exception and determines the right resolution based on years of building in the intuitions of seasoned freight operators.
Standardization
Inconsistent data hinders efficient operations. To build workflows and applications on top of tracking data, it needs to adhere to a predictable format. Ideally one that makes use of international standards for location, event, and time notations. That’s why OpenTrack adheres to the Digital Container Shipping Association (DCSA) format and data is reported consistently in a standard format no matter if we’re tracking on ocean, rail, or over the road.
These processes quickly demonstrated to customers that we were actively looking out for their interests. Customers soon recognized our consistent ability to stay ahead of potential issues, which significantly boosted their confidence in our services.
Ocean shipping isn't an exact science, and every company faces operational challenges. Our secret to success was identifying these challenges before our customers did. I found it incredibly embarrassing when a customer called about a problem I wasn't aware of. Thanks to OpenTrack, my department nearly eliminated such occurrences for me and my team.
Overcoming challenges and driving change
Implementing these changes wasn't easy. The account-based model often makes it difficult to establish consistent processes across accounts. We found success by adopting more of an assembly line approach: person A handles dispatch, person B manages customs holds, person C oversees payments, and so on.
We also had to overcome the "If it ain't broke, don't fix it" mindset. This required a paradigm shift pushed from the top. Fundamentally, you have to care that you're doing a good job. It's crucial to foster a culture where people take pride in their work.
Technology played a key role in our success. Tools like OpenTrack allowed us to work smarter, not harder.
How OpenTrack ensures superior data quality
OpenTrack ensures superior data quality through a unique approach:
- Multiple data sources: We tap into various data streams to fill gaps and provide complete visibility when a single source doesn’t.
- Push integrations: Our system prioritizes real-time data capture for timely updates.
- Advanced exception detection and resolution: Our sophisticated algorithms, developed through years of collaboration with seasoned freight operators, identify and resolve thousands of data discrepancies daily. This custom-built logic not only resolves conflicts between data sources but also provides automated monitoring for your entire supply chain.
- Human expertise in the loop: An experienced data operations team personally handles rare, complex edge cases around the clock, so you don’t have to.
- Continuous monitoring: We maintain full surveillance across all data quality dimensions in the table above, and react quickly to make sure your data is always available.
- Continuous improvement: We review, prioritize, and implement improvements every single week. Our automated monitoring is paired with robust systems to mobilize our engineering teams to quickly implement improvements.
- DCSA standard adherence: We maintain consistent data formats across all transport modes and data points, making our data simple to work with.
This combines to produce the highest data quality in the industry, powering automated exception detection tools used on the front lines by the most trusted names in freight.
