Achieving end-to-end supply chain visibility with your data architecture

Small problems or large, having as much accurate, up-to-date information as possible on hand almost always correlates with making better decisions. This rings especially true in the management of supply chains. Anything ranging from “global pandemic” to “beached supertanker in a global trade bottleneck” requires decisive action in order to minimize the consequences of unpredictable events.

Most organizations have recognized the importance of digitizing their reporting and tracking data in order to streamline operations. An enterprise may have insight into their suppliers, into their inventory, and across their fulfillment network. But the ability to discern larger trends and a big picture is limited if this information is being collected in independent silos. What is happening instead is that since 2015, gaps are growing in every facet of supply chain visibility. 

What is needed is a mindset change.

An end-to-end approach to supply chain visibility unifies all this information, giving a complete picture of the entire supply chain at a given moment, unlocking deeper insights both about the way you, your customers, and your partners conduct business. End-to-end visibility allows you to track individual items throughout your supply chain, from the raw materials all the way to finished, manufactured products on their way to their final destinations. 

Companies that implement scenario planning are twice as likely to avoid supply chain disruptions as companies that do not. The key to proper scenario planning — which includes knowing when to execute what plan — is rooted in having as much visibility as possible.

What does real supply chain visibility look like?

Any proper end-to-end visibility solution needs to solve a number of common bookkeeping pitfalls.

• Traceability – The ability to quickly identify a product or batch and then trace the product or batch up or down the supply chain quickly, accurately, and cost-effectively especially when managing defects or recalls.
• Single source of truth – Knowing for a fact that the information and signals you have in front of you are accurate and up-to-date means that humans don’t need to spend precious time verifying information, resolving discrepancies, or accounting for plain old incorrect data.
• Sub-tier visibility – Gives you further insight further up the chain; every mistake in a supply chain is cheaper and has an exponentially lower blast radius the earlier and further up it’s caught.

Obstacles to achieving end-to-end visibility

The most common challenges in achieving end-to-end visibility are engineering and the operational structure of your business process. 

• Sharing of data – Often via spreadsheets shared over email; impacts the timeliness of data as well as the risk for discrepancies.
• Scalability – Some organizations develop and maintain IT interfaces like agreed-upon API schemas with a close partner or two in order to digitize the data sharing process; however, when expanding to dozens of sub-tier partners and customers, that becomes a managerial nightmare.
• Partner technology – You can pick your partners, you can pick your tech stack, but you can’t pick your partner’s tech stack. 

Any digital data sharing solution you choose to implement should make interoperability with partner systems as simple and seamless as possible. It should also be future-proofed to account for all your existing partners — plus everyone else you choose to onboard in the future. Implementation of a simple, seamless solution isn’t impossible, and it needn’t solve for every future partner or scenario from the get-go. Rather, a proper solution that meaningfully improves end-to-end visibility should address the common pitfalls described above.

How to achieve end-to-end visibility with your data architecture

There are three major steps involved in achieving better end-to-end visibility, and they all should be repeated regularly to ensure you remain agile and adaptive to the issues of the day.

1. Gather supply chain data

The first step is to collect the data that exists at this moment and understand what the current data collection processes report. In 2023, three decades out from the advent of modern ERP software, most enterprises collect information and report some of it to their partners. The more information you’re able to collect from your processing and your partners, the more you can find deeper patterns in that data. 

For example, let’s consider tracking the location of cargo shipments: a trans-Pacific trip takes 15–30 days, not including processing time at the port. Knowing exactly where the cargo is allows you to manage your inventory much more efficiently and prevent over-or-under-stocking of your products across your distribution network by adapting to changes as they happen.

2. Plan for improvement

If you are embarking on improving end-to-end visibility for the first time, a few “problem areas” are common, such as data siloing. Each partner or internal business unit may use a different reporting method with different technology and services leading to disorganized, heterogeneous data. Mitigating this problem is a company-wide decision, and mitigation often involves implementing policies such as standardizing tool use, deeper and more collaborative partner data sharing agreements, and creating a central data ecosystem such as a data lake. 

Standardizing tool use and participating in more collaboration with partners can yield powerful results. BMW adopted Vendia Share to trace defects in their supply chain and reduced cost of recalls by 88%.

Read the case study

3. Build a robust data sharing architecture

When working to achieve end-to-end supply chain visibility, maintaining a robust data sharing architecture cannot be avoided. Your customers need to know when they will get their products, and you need to know the status of the inputs required to make those products and get them to customers. Because data sharing is an integral part of end-to-end visibility, some of the same challenges show up in both places. 

• Heterogeneous data leads to data siloing, as discussed above. 
• Brittle connections arise from organizations agreeing to use a certain data sharing mechanism (such as a private data egress API) that was architected once at the time of contract signing; each organization has their own IT goals to pursue, and the technical alignment that existed in that snapshot of time will inevitably drift. 
• Data reconciliation has been a thorn in the side of sharing information since bronze metalworkers first started buying copper from local miners thousands of years ago. 

Ensuring both parties are reading the same books and agree on the process for reconciling discrepancies is integral to making informed decisions.

Slalom chose Vendia to deliver a data sharing solution in the Travel and Hospitality space. The solution provided a universal data model with automatically-updating APIs that took less than a week to deploy and ensured instant data reconciliation with high throughput.

Read the case study

How Vendia Share can help you achieve end-to-end visibility and see into your sub-tiers

Vendia Share provides a flexible, scalable, tech-agnostic data sharing solution with a focus on trust, control, and security. Vendia Share provides features and functionality that bring data sharing into the 21st century.

•  Our universal data model ensures all data is homogenous without exposing too much of your data to partners who do not have a need to know with access controls and the ability to seamlessly evolve as your business needs or partner roles changee. 
• Automatically deployed smart APIs are custom endpoints derived from your data model that can have their access controlled by the Vendia Share network owner. 
• Our consensus algorithm provides high-throughput processing while ensuring common pitfalls like race conditions are avoided, so you and all your partners can trust that your data is accurate and up-to-date.

What's next

Supply chain visibility is a common goal that each industry has a winding road to achieve based on their unique characteristics. While the takeaways outlined in this blog generally hold in most cases, each industry will tackle them in different ways. Here at Vendia, our strength as a modular, flexible solution means that we can help out in a lot of different places in a lot of different ways; we outline 3 such cases in the semiconductor industry here.

Upon gathering all of your organization’s supply chain data, you may find that poor data sharing is impacting your ability to make the most informed decisions possible and that a tool like Vendia could serve as the foundation for a robust data sharing architecture. We’re always happy to talk to see if there’s a match between your challenges and our solution.