snext - Creating Management Tools for the Supply Chain of Tomorrow

Digital transformation for logistics and supply chain management is not for the faint of heart — particularly in retail, where there are webs of diverse systems and mountains of raw, unconnected data. But there is a way to create a comprehensive, seamless view of an extended retail enterprise. InterSystems partner snext, headquartered in Paris, was founded on a futuristic vision of supply chain operations that maximizes customer experience and profitability while conserving resources.

“Today, it is possible to give suppliers and logistics and other stock managers the tools to measure and simulate the impact of their decisions on quality of service and on operating margin,” says snext General Manager Richard Viot Coster.

Using InterSystems data platform, snext is commercializing software-as-a-service (SaaS) applications enabled by artificial intelligence (AI) and machine learning (ML) for product categorization, inventory control, and demand monitoring. The three solutions represent critical areas that are largely ignored by current enterprise resource planning and advanced planning and scheduling systems.

As the foundational platform for snext’s applications, InterSystems integrates, transforms, and harmonizes customer data from multiple sources. The data can thus be visualized and analyzed consistently.

According to Viot Coster, snext’s family of SaaS modules facilitates digital transformation by allowing users to retain their existing systems. The solutions also meet a major challenge: creating a flow of information among largely fragmented systems.

“They are complementary to customers’ existing applications and data stores, and data is integrated through standard application programming interfaces,” he says.

The SaaS solutions are based on a solid understanding of supply chain processes and technology. They are built on an open architecture that a customer’s developers can leverage to create their own applications by tapping into information and data from snext modules.

“The reasoning is that digital transformation is not so much a revolution replacing what is already being used, but rather a realization of the full potential of the data and information already present in an organization,” Viot Coster explains. “And that is critical for facilitating digital transformation.”

InterSystems data platform was chosen by snext based on its cloud-based availability, its ability to integrate with other systems, its ease of development, and its scalability and efficiency.

“The fast development of new solutions is critical for our business success. InterSystems data platform empowers us to work much faster and ensures the scalability and security that is indispensable to our customers,” says Viot Coster.

According to snext cofounder Blaise Zarka, “Because snext modules are based on InterSystems technology, they consume five to 10 times fewer cloud resources than they would operating on other data platforms.

“It also gives us the capability to create new services,” he adds. “With InterSystems technology, it is easy to create end-to-end processes, which gives us a competitive advantage.”

Richard Viot Coster believes that the system architecture and technology platform are critical to reducing development costs and integrating the SaaS solutions with existing systems. And thanks to the open architecture of InterSystems data platform and its ability to integrate fragmented systems, snext users can easily create processes and applications spanning an end-to-end supply chain. In addition, shared cloud services enable users to focus on doing their jobs rather than troubleshooting technical problems.

Finally, the scalability of InterSystems technology means snext can easily respond to the growing number of customers for its services.

The next steps in the product roadmap include developing AI and ML models from the historical data in the systems, and embedding the models into the connected processes. snext is confident that it can support this effort with its in-house expertise. The data stored in InterSystems data platform can be used to develop AI and ML models, and the resulting models can be embedded directly into the SaaS offerings, all without moving the data to another environment. Target use cases include real-time operations monitoring, more accurate demand forecasting, and disruptive inventory optimization.

AI, Viot Coster says, is “particularly well adapted to extracting pertinent information from a mass of raw data. For example, despite its benefits to any supply chain, detailed demand monitoring is a great fit for any use of AI but is seldom used.”

Here, AI can be used to analyze large amount of data, so “any anomalies in demand behavior on a multitude of items across an entire distribution network can be immediately detected and reported for maximum responsiveness,” he explains.

In this use case, AI will not automatically reorder stock; a human, informed by AI, makes the ordering decision. As Richard Viot Coster puts it, “AI complements traditional demand-planning tools and can effectively relieve users from tedious manual tasks.”

He notes that AI cannot be the end in itself. It will live up to its promise only when its use is based on meeting specific business goals, and when it is supported by an architecture and a platform capable of integrating data from existing systems and providing business solutions that deliver value. InterSystems data platform, coupled with snext’s deep supply chain experience and expertise, is enabling snext to indeed live up to the promise.