Solving the Visibility Puzzle with Data Integration
Irrespective of the industry in which readers of Tech HQ operate, there has been a massive increase in the amount of data collection that every organization engages in daily. With most operational systems now having at least some digital component, ingesting information is a normal part of getting a day’s work done.
Every company is keen to take advantage of those information flows. For supply chain and logistics companies, there are some considerable advantages to be gained. That’s partially because supply chains, by their nature, comprise multiple players that need to work together synchronously. Inside a typical logistics department, nearly every piece of technology is data-focused: vehicle telemetry, supplier portals, spot quote and finance systems, various Excel sheets—every business is different, but the disparity of data sources is a constant challenge.
We were lucky enough to speak to Andrew Hooser, the VP of Customer Solutions at RateLinx, one of the world’s leading logistics technology companies, about the specific data-related opportunities available to the supply chain and logistics sector. We talked first about those different systems that are probably in play in a logistics operator’s toolkit and the challenges shippers face.
Andrew said, “A good example would be you have demand planning and supply planning being done in a system that is independent of a WMS where orders are being fulfilled. So, maybe the WMS gets a spreadsheet once a month from the supply chain team of what’s going to happen in the next month, two months, 24 months, whatever. So that’s what their source of truth is for the next [time period]. Meanwhile, the WMS is not tied together with the TMS. So you have planners manually taking orders from the WMS, going into a separate system to input those orders, and there’s no visibility or tracking.”
So far, the issues facing companies surround the lack of data integration between disparate sources, software, and hardware. Technology solutions solve specific problems throughout a company’s history, but there are no guarantees that each solution talks to any other solution. Therefore, collecting all the available information is the first challenge, followed by verifying data quality. Check out our last piece with RateLinx to learn more about Data IQ. Integrating the data so it maintains context, can be easily accessed, interpreted, and used to make informed, accurate, and timely decisions is a game-changer in logistics.
“Yeah, so data connectivity is simply establishing a pipeline between all of the inputs—the sources—and the data that you’re trying to build. There’s a difference between connectivity and integration. As an analogy, connectivity is finding all the puzzle pieces. Integration is putting them all together to make the picture. I think where organizations struggle is in both areas. One, establishing the connectivity can be difficult because each system, each entity, has its own formats […] So it becomes a data translation exercise, and organizations aren’t really built to do that. At an integration stage, you have to be very intentional about really making sure that the way you’re tying the data together makes sense, especially for the ultimate goal. I see organizations struggle with both. Organizations just aren’t built to do either. They spend a lot of time trying to establish connectivity. And then even if they get connectivity, the integration becomes a struggle. And that’s something we see all the time.”
The nature of data, its translation into compatible formats, and the vast quantities of machine-generated information can produce huge amounts (data lakes) of facts and figures that serve little purpose on their own, Andrew told us. That realization comes from the fact that few companies ever get to that stage.
“What I see is companies will have many disparate systems, [then] they’ll have data lakes, and they will say this part of the data is good, this part is bad. And all the users are kind of tiptoeing around what the data is actually telling them, which means they don’t actually use it to make decisions and [take] actions. They spend most of their time just trying to verify that the data is correct before making a decision, which wastes time, energy, and effort. Everyone talks about having a single source of truth. But very few people, very few organizations get to that level.”
Data integration involves intaking data from multiple systems, translating formats, cleansing the data, and then integrating the data sets to complete the context of all data sets. RateLinx takes a data-first approach with all clients—not something you’ll see with others in this space. They ensure data quality and integration to quickly provide insights and value to shippers. So, what role does RateLinx play in leveraging the new sources of data into operational improvements? Is it all about visibility into operations?
“Any sort of visibility gaps, that’s what we look to fill. That’s done in two ways. One could be tying together a shipper’s own data sources and systems and integrating them. And the second way is (especially on the logistics execution side) we have a TMS, a visibility platform, and a freight audit system. We can tie together all of that logistics data to provide connectivity and help […] execute the strategies for shippers, creating that one source of truth.”
To use Andrew’s analogy, the chain of interlocking puzzle pieces stretches from demand planning and forecasting right through delivery to a dock, loading bay, or customer’s home and down to the invoice level. It’s a broad spread of capabilities that may spur dramatic changes to business systems, processes, and culture. Andrew agreed, but pointed out that even on the way to a complete system and processes refresh, there are plenty of short- and medium-term gains made on the way.
“One: getting visibility to your spend. Pure and simple. You can start to make adjustments to lower cost. You can find opportunities that you might not have seen otherwise, because you can see all [the data] in one place. Second would be customer service. Once you start getting visibility, you can make adjustments to make sure that you’re meeting your customer requirements. And you’re actually giving them the service you promised them.”
In the long term, data has the ability to deliver powerful prescriptive insights. Reliable information pulled from different sources and properly integrated, creates a powerful demand prediction and planning platform for any supply chain company. Decisions aren’t just up to the user looking at the data. Prescriptive insights tell the user what action they should take or even automate recommended actions.
“One of the metrics we focus on is lost savings. For example, we can start to challenge the decisions that are being made, as far as carrier selection, by simply showing the costs behind one of a customer’s decisions [compared] with another. And you start highlighting those and it may be something that the customer just says, ‘No, that’s not what we’re gonna do.’ But oftentimes, eventually they start making better decisions and even cultural changes.”
The difference between RateLinx and a generic IT consultancy or solution architect is its deep involvement with and understanding of the sector. The RateLinx team has decades of experience in the same roles and capacities as their customers. Having an experienced industry-based solution provider keeps the focus on operational gains rather than tech for tech’s sake.
To begin your journey to help your company achieve improvements in processes, data integration, and decision-making, get in touch with RateLinx.
1 December 2022
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