It’s clear — and has been for a while — that big data and advanced analytics technologies are transforming a lot of day-to-day operations. In entertainment, it can suggest new movies and content. In health care, it’s helping professionals discover new treatments or care solutions, and in manufacturing, it’s improving outdated practices. It’s not a surprise, then, that big data solutions to better analyze and collect supply chain management data are influencing the modern supply chain, as well.
While logistics and supply chain management fields have been slow to adopt the more innovative forms of the technology, implementation is undoubtedly picking up speed. That’s because a lot of different organizations have realized the full potential of the technology and what it can offer their bottom line. When it comes to the supply chain specifically, supply chain managment data solutions can help improve efficiency by creating a more seamless environment.
Real-Time Data Processing and Sharing
One of the major challenges of logistics is the ability to integrate information and data channels across not just multiple platforms but with all involved parties, as well. Real-time sharing with any partners is vital to ensure operations are running smoothly. The sharing of supply chain management data relates directly to customer demand, various environmental factors, supply levels, and even partner strategies.
Transparency is one of the major contention points of any supply chain. Consider optimizing something like a delivery or transportation route. You have to consider the route source or start, how long it’s going to take to travel to each destination, where the drop-off point will be, when certain events take place and even external factors such as weather and traffic.
It’s also necessary to retain control, not just over processes and operations, but the goods themselves too. Having that transparency about where materials come from and where they’re going can be instrumental during future events. Using supply chain management data to to be able to pull contaminated or defective items, for example, can save a lot of headaches.
The Digital Supply Chain: The Landscape, Trends, Types, and the Application in Supply Chain Management
Managing External Factors With Data
Logistics is also about dealing with situations or circumstances that result from external factors and are outside your ability to control. For instance, socio-cultural changes in a supplier’s country can destroy performance, especially if whatever is happening delays shipments. Alternatively, a major shift in consumer demand can put you in a difficult spot, particularly when you haven’t prepared for it.
Big data solutions can help gather and organize supply chain management data related to all these different factors, and you can use it to acquire insights on how they might influence operations. More importantly, it’s possible to automate these modern solutions to mitigate the amount of time and resources needed to keep them running.
Imagine a system, for example, that builds predictive models using supply chain management data of upcoming social events. It would reveal possible outcomes, allowing you to better manage and plan.
Order Optimization and Inventory Planning
Across the chain, proponents can plan, forecast and optimize their stock to meet changing demand. It’s about more than just keeping the right amount of goods or optimal inventory numbers — it’s more about the logistics automation aspect.
Big data solutions can help power and facilitate inventory automation by ordering new items when needed, shipping out orders, dealing with supply processes and much more. A manufacturer, for instance, might be dealing with a particular material that takes five months to produce. A big data system tapped into all facets of operations that gathers all supply chain management data could discern when is the appropriate time to order more goods, keeping things running optimally without delays. That way the new supplies come in exactly when the old ones run out and there’s no delay in between. Of course, this is just one, simple example of these systems in action.
Increased Customer Satisfaction
Real-time information and supply chain management data streams can also lead to more nuanced improvements regarding how things operate. It impacts efficiency everywhere along the supply chain, obviously, but it also helps improve customer experiences — further boosting satisfaction.
It’s possible to speed up fulfillment and delivery times for orders, handle larger orders that come in intermittently and even plan for them, and to create better, lower-cost opportunities. Companies can even supply this information to customers directly to help them with their inventory management processes.
The Bottom Line
Ultimately, big data streamlines efficiency and responsiveness for nearly all supply chain parties. More importantly, by gathering massive sets of all available supply chain management data, improves compatibility and enhances processes across the board, resulting in some incredibly successful operations.
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