Supply chains have become so complex and entangled that the traditional way of navigating everything, from suppliers, to inventory, to transportation and analysis, has been turned upside down.
As with all messes, there is a significant business opportunity for any business that can handle cleanup in a new, more streamlined way. In a post-2020 world, this need is greater than ever, but it will take more than a traditional supply chain management system. It will need more data from more sources, all provided and synthesized as close to real time as possible.
Few companies can bring together so many disparate data sources with the tools of the backend platform. Google is one of them.
The catch is, you have to use the cloud and it has to be Google’s. Again, supply chain management systems have always been proprietary and impenetrable.
Where else can the companies most susceptible to supply chain disruptions go as each day seems to bring a new bottleneck? Weather or container and port backups, delayed flights and trucks, supplier outages or disruptions – these are all macro issues that are difficult to integrate into existing supply chain management systems in near real time. .
It may be that only hyperscalers can deliver the kind of nuanced supply chain impacts that businesses need. They’ve got the hooks in a massive data partner ecosystem, their own data in spades, the compute to bring and all the levers in the world to get the big ERP and supply chain software manufacturers to team up.
In other words, why let these ISVs have all the power when getting the bigger view (and all the infrastructure) takes so much more than a single database? AWS has been offering complex supply chain offerings for years, and Microsoft has worked with SAP to make its own approach to supply chain and logistics a science. But when it comes to really big data – the kind that matters in the post-2020 case – Google might have the most compelling tools at their fingertips.
Software startups beware: there might not be an opportunity to ‘disrupt’ the software space in the supply chain, but it is very useful to score a niche as a supplier of ‘components. data ”targeted. 2021 could be the best year possible all the way down to the ground floor with a very nuanced risk-driven assessment tool or service to power the giant engines of supply chain understanding, and the worst for anyone. hopes to launch a “mega-platform” despite the obvious need. In this particular case, there’s really no competition with the cloud, especially once that element of integration is resolved. Assuming, of course, that supply chain victims are in the mood for a big tech change in the middle of the worst year imaginable.
Google Cloud is doing everything it can to make this offering look non-traditional, while capitalizing on the AI buzz and more under-the-radar concepts like digital twins.
Google Cloud Platform’s approach to supply chain technology goes beyond a database-driven platform on the surface and in the field of something we’ve heard in the field. supercomputing: digital twins. Instead of a traditional way of analyzing and forecasting, digital twins are a virtual expense of a company’s entire supply chain, which can be manipulated to make more accurate predictions. At the end of the day, it’s just databases, but it’s the sources, ingestion, and simulation that can make the difference, along with more real-time emphasis.
The company’s recently announced Supply Chain Twin can aggregate and synthesize data from publicly available risk and weather data as well as its own proprietary data wells. Google can integrate with existing ERP systems and integrate data from suppliers and transport companies. Users can receive alerts when something might change and can use Google Cloud’s built-in machine learning to get suggested responses to a number of possible impacts.
Supply Chain Twin provides ready-to-deploy connectors and transformation pipelines based on Cloud Data Fusion to move data from ERP systems like SAP to the BigQuery data platform. It uses public datasets from Google Cloud and Analytics Hub to enable secure access to organized datasets from multiple data providers without complex integration. This semantic layer spanning private, community and public data segments enables data to be directly and scalably mined for a variety of uses, including data science.
The offer is still in preview mode, but companies like European automotive giant Renault were the first to adopt it. “At Renault, we innovate the way we manage efficient supply chains. Improving the visibility of inventory levels in our network is a key initiative ”, declared Jean-François Salles, Vice-President Global Supply Chain of Groupe Renault. “By aggregating inventory data from our suppliers and leveraging the strength of Google Cloud in organizing and orchestrating data, with solutions like Supply Chain Twin, we hope to gain a holistic view. to work with Google tools to simultaneously manage inventory, improve forecasting and possibly optimize our execution.
Hans Thalbauer, who heads the Supply Chain and Logistics division of Google Cloud, explains that the problems with existing systems are due to siled and incomplete data. He highlights this lack of visibility and says that the digital twin’s approach to supply chain management allows users to gain “deeper insights into their operations, helping them optimize chain functions.” procurement, procurement and planning to distribution and logistics ”.
Synchronizing all of this with existing systems and platforms will be the biggest challenge. While companies may know that their current approach to the supply chain is no longer robust enough, stepping into something new in times of crisis may not seem like the natural thing to do. Google Cloud is working with Deloitte and Accenture, among others, on the integration side to merge the relevant datasets.
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