Multi-enterprise Supply Chain Networks

The Multi-enterprise Supply Chain Networks market research delivers current market analysis plus a five year market and technology forecast. 

Multi-enterprise Supply Chain Networks Market Finds its Groove in the Wake of the Pandemic

ARC’s research shows that the market for Multi-enterprise Supply Chain Networks (MSCN) is growing rapidly as the solutions almost always result in increased ROI. MSCN is a new name for networked applications that were already in existence. Some of the platform application providers grew incrementally out of marketplace sourcing solutions, some out of public cloud applications, and some of the risk solutions are much newer types of applications. 

Multi-enterprise Supply Chain Networks Strategic Issues

In addition to providing a five-year market forecast, the Multi-enterprise Supply Chain Networks market research provides detailed quantitative current market data and addresses key strategic issues as follows.

Support Supply Chain Digital Transformations

In terms of supply chain digital transformations, the most advanced transformations will depend upon solving the end-to-end multi-echelon, multi-enterprise problems. With visibility to where problems are, companies can 'orchestrate' a solution, or at least mitigate, a problem. Several MSCN suppliers can use visibility to orchestrate better logistics solutions to a problem. Some vendors can use network data to optimize a better transportation solution.

Even better is a solution that could trade off manufacturing, distribution, and transportation costs to better solve an exception and enable optimized execution. Optimized execution is the key process that has been missing in SCM-deployed solution architectures.

For optimized execution, the network must run on a common data model, with a single version of the truth, in real-time, with the ability to represent multi-party and multi-tier transactions across trading partners. Furthermore, advanced risk detection is critical to optimized execution.

Advanced risk solutions continuously monitor real-time risks across hundreds of thousands of online and social media sources and then mapping those risks to the extended supply chain of a company. Risk events can also be based on real-time alerts that a shipment will arrive late to a customer.

Finally, concurrent planning would be critical for a robust optimized execution solution. Concurrent planning is the process of making and managing unified plans across multiple time horizons, business processes, and organizational boundaries at the same time. No supplier has all these capabilities. 

But a supplier that could provide all these elements could allow users to build advanced supply chain control towers at a fraction of the cost and in a much quicker time frame. Currently, building advanced control towers involves complex data mapping, master data management issues, and the need to integrate different applications into a customized data mart.

Recognize the Distinct Advantages of the Multi-enterprise Supply Chain Networks Architecture

Growth in this market is (also) driven by some unique characteristics of multi-enterprise supply chain networks solutions. These solutions have public cloud synergies that go beyond just being an architecture, which is quicker to implement and easier to upgrade. These benefits also go beyond making it easier to do business with companies already on the network. The benefits can include:

• Communication management: as new parties enter the network the existing integration can make connecting to other parties on the network much easier and quicker. 
• Partner management: when sellers of supply chain services (warehousing, transportation, or contract manufacturing) or direct materials, are part of an MSCN solution, the partner information can be stored on the hub for use by other potential buyers of their services This can include contact information, sustainability, financial risk data, industry certificates, or product data. Because the data is provided to the hub, it can be leveraged by other buyers without the seller having to re-enter the data.
• Third-party data: when companies integrate to the hub they can easily access supply chain third-party data stored in the hub. This can include downstream demand and inventory data, upstream capacity data, government and industry data sets that can improve demand planning, financial risk data, sustainability data, etc.
• Network analytics: this refers to analytics that can leverage the data from the community and drive better insights while protecting the confidentiality of any participant. The newest generation of risk management solutions, which ingest massive amounts of data and use that to provide real-time risks, are another form of network analytics.
• Network master data: centralized naming conventions that ease supply chain collaboration. Examples from the standards body GS1 include global trade item numbers (GTINs), global location numbers (GLNs), and serial shipping container codes (SSCS).
• Collaborative system of record: because data is stored centrally in the hub and then shared with partners, the hub can serve as the system of record for cross-party transactions.