Guy Courtin, Infor GT Nexus Commerce Network
When the internet started to become the backbone of business software deployments 20 years ago, the supply chain seemed poised to benefit more than most. A ubiquitous network that was being adopted by every person and business on the planet had the potential to solve the challenges of information sharing, collaboration and visibility.
Business software systems quickly adopted the cloud as a deployment method. Accessing software as a service, using a web browser, gave buyers more power, and it lowered the barriers to entry for smaller companies. Countless software companies emerged that were focused on delivering pure, cloud-native solutions, and the big software firms eventually followed suit.
But regardless of the way technology gets deployed, it still depends on data. In functional areas where the data comes from sources largely within a company’s sphere of control, cloud rapidly displaced software as the preferred deployment method. But in supply chain, there’s a network dimension to any technology effort that must first be addressed. That’s because more than 80 percent of the data needed to effectively run a supply chain comes from external partners, which are different companies scattered around the world.
Networks are Not Created Equal
Information networks are not a new thing. There are countless companies that provide networks and associated capabilities. Many of these services are focused heavily on supply chain, providing connections between thousands of companies. Lots of supply chain data flows through these networks, yet companies still struggle to coordinate and translate that data so different systems understand it—and so the vast partner communities all operate with a common information language.
One of the main reasons that companies have struggled with their network strategies was that all of the data normalization took place at various nodes at the edge of the network. When social media platforms hit the scene, their success was based on shifting the data records from the edge nodes to the center of the network. Suddenly, a single profile page could be updated constantly and serve as the master record of one’s social status. That master page would then be accessed by other network members. Users only had to worry about their own profile, yet every member of the network had full visibility and connectedness to as many friends with whom they wanted to connect.
Now, imagine the implications for supply chain managers using a LinkedIn-like information model. Instead of shuttling petabytes of data files around a network of potentially thousands of partners and their systems, all the data is posted to the center of the network for all to see and use. If the status of an order or shipment changes, the “object profile” is updated, and anyone who has permission to see that change gets the update. In a world as complex as global supply chain management, this is the only way to get partners in sync and applications functioning at scale.
Critical Mass is Key
The vision of a business network that mirrors the way social networks are designed is not a new thing. The minute Facebook surpassed 500 million users, the business-to-business software companies raced to find a way to develop a similar network design to support their respective solutions. And in many cases, there were some very viable networks that were introduced. However, a “build it and they will come” approach does not always result in actual network adoption and growth.
Even the best designed, most functionally rich network on the planet is nothing without a critical mass of stakeholders and participants. What would Facebook, or LinkedIn, or Snapchat be if you couldn’t find friends and colleagues? It’s not enough to open a network and expect the masses to come and set up shop, especially when it comes to supply chain partners who are likely being asked (or pressured) by their customers to join networks of all sizes and shapes.
Networks take time to achieve critical mass in business-to-business environments. There are so many offerings, focused on such a broad range of functional areas, it’s easy to see how IT leaders would be confused about how to best address their thirst for data. Do they build their own networks, or pay to join an existing third-party network?
Networks that combine the right architectural model with a robust community present a fast path to operational status. It’s likely that companies will find many of their partners already connected and supporting their own customers. And, importantly, an existing, humming supply chain network will have a data quality program already in place, designed to address the difficult task of translating and normalizing data – something that’s only going to get harder as more IoT devices come online.
Digital Transformation Enablement
Supply chain networks that are focused on connecting suppliers, logistics providers, financial services, factories, warehouses, agents and even different divisions within the same company, are a foundational requirement if any company is going to embark on a digital transformation initiative. This network also needs to connect various enterprise systems, such as enterprise resource planning (ERP) systems, which can date back years or decades.
At the core of anything digital is data, but “ones” and “zeros” don’t equal insight. Most supply chain innovations will still require a network strategy. Even blockchain, the white-hot innovation theme of 2018, will require a network to actually work because the public ledgers we often hear about are too slow and power-hungry to run at scale.
Digital supply chain transformation is becoming a mission critical path for most companies. Amazon is forcing everyone to rethink the way it makes and delivers products. “Ones” and “zeros” will help, but for true transformation to actually begin, data must be converted into insight. A network won’t provide all the answers, but the right kind of network will make the difference between more of the same, versus actually doing something differently and better.
