%201.svg){kind=small}
Easily accessible and reliable cargo visibility data is very important for any business in today’s volatile world. There are often multiple data sources that tell different stories. It is not easy for managers to trust any one data piece, since another data point out there might paint a different picture.
Through this blog post, we will identify the concept of the single source of truth and its correlation with data multiplicity.
The Importance of a Single Source of Truth
Business insider reports that 47% of the top management still manually compile data, and 69% state that keeping information siloed is their biggest financial and operational mistake.
Not having developed the internal capability to assimilate and assess operational data points is the starting point for a downward spiral as the quality of decision-making reduces, since the full data-backed picture is not available. Departments within the business would ultimately spend countless hours deciphering who owns the right data, arguing about who is at fault, while decisions get side-tracked or delayed.
So how does one achieve a single source of truth?
The Concept of Data Multiplicity
However, in reality, and due to the complexities and the dynamic nature of the supply chain industry, organizations are having to depend on multiple vendors, multiple tools, multiple data points in multiple formats, AND multiple hand-offs with multiple risks to achieve their end goal.
The dependency on multiple modes of data or multiple data sources is called data multiplicity. It can be of 2 types:
- Getting different data points about the cargo journey that paint a full picture of the movement of cargo (e.g. container events, port calls, vessel schedules, vessel live locations etc.).
- Getting the same data from multiple sources: helps with building trust in the data point.
In fact, a detailed study on big data states that companies have to move away from the principle that a single source of data is the only solution.
Data multiplicity of both types is critical in the logistics industry as it gives businesses access to multitudes of information that can be assimilated to find a single source of truth. This is where visibility and transparency come into the picture. If there is a discrepancy on the same data point between the 2 sources, the operational user can then take the call on which source to eventually rely on.
Types of Data for Logistics Providers to Achieve Visibility
Container events, vessel schedules and the ship’s live geolocation information: these 3 types of data points will help give 360-degree visibility to logistics providers, giving them data at their fingertips for any deviation that might happen over the course.
The required data can flow through multiple sources across various formats and languages, as detailed in data multiplicity. The more data points that are easily available, the easier operational decision-making can be.
Accessing and comprehending trustworthy data through multiple channels and then communicating it across the organization will enhance the true potential of any organization.
Portcast's Experience In Integrating Dozens of Data Sources
Here at Portcast, we utilize the data multiplicity approach from the very beginning to provide the most accurate data for our customers and take over the challenge of solving discrepancy issues.
Now, we have several years of hands-on experience on that topic, our platform collects information from dozens of sources and is designed to share data from multiple sources, along with recommendations on which data point to trust in case of any discrepancies.
Let us show you some examples of data collisions that may represent the problem of data multiplicity best from the perspective of the shipping industry and container visibility:
- Port congestion indices were developed using information from carrier tracking systems, terminal portals, and the satellite. Using a single index for congestion can create a false representation of the actual scenario at the port. For example, a high number of vessels does not always translate to high congestion. Congestion relies on a port's capacity to handle vessels.
- Location of a container based on carrier data vs geolocation information. For example, based on geolocation data, a ship had reached the port but the carrier did not update the ATA. However, the ATA can be made available from the satellite position of the ship and the port geofencing. Thus, different sources of data allow you to receive the latest updates earlier, which facilitates faster decision-making.
- Schedules and routes from multiple carriers through carrier networks and API integration. Here at Portcast, we monitor the correctness of different carriers’ schedules against live location vessel data to dynamically switch in cases of missing or extra ports. Here is an example of the MOL Trust's journey from Port of Singapore to Port of Le Havre and a comparison of schedules provided by two different carriers where ‘Carrier 2’ missed Port of Suez Canal and added extra ports at the end of the journey:
- Updates from automatic tracking systems to avoid blackout dates or dark days. Multiple sources can reduce the time shippers spend without visibility on their shipments during unwarranted scenarios (like the Suez Canal blockage), by allowing the shippers to switch from one system to another.
How to Enable Data Multiplicity On Your Side
There is a fine balance between having an overload of unnecessary information and having the optimal amount of data multiplicity that can help significantly improve the quality of the single source of truth.
So when there is a question as to data multiplicity or single source of truth in supply chains, the answer can also be “Why not both”.
Our platform uses multiple data sources to find the single source of truth for our customers. It minimizes our client’s efforts spent on integration and research of each data source on top of the development of real-time visibility platform itself.
We work to eliminate the impact of disruptions on global supply chains, help with fast and effective decision-making, and ultimately give a positive impact on the bottom line for the customers who would rather focus on their product instead of worrying about picking one data vendor over the other when they can have the best of both of them.
