How Does Big Data Influence Supply Chains?
Martin Pahulje - June 29, 2021
In the supply chain industry, it is vital to stay up-to-date on technology and industry trends to stay efficient and competitive. A recent and growing development is big data, which offers the solution to generate increased efficiency to the retail supply chain. As organizations continue to implement more and more technology, they are gaining access to massive volumes of data, larger than have ever been handled before. If an organization cannot filter and analyze this data for incorporation into its supply chain strategy, it is not being fully utilized. Technologies such as sensors and AI-enabled systems can significantly strengthen an organization’s supply chain but only if paired with the right solutions to interpret the data outputted. This is where big data comes in.
Today, customers have higher expectations than ever, and it is critical that organizations keep up. To do this, organizations must have accurate forecasting, streamlined production, and absolute resilience – all of which can be obtained through big data. Big data is drastically influencing supply chains for the better through real-time analytics capabilities. This solution complements the end-to-end visibility of the supply chain and enables your organization to work proactively, avoiding revenue loss while optimizing operations. We will discuss the seven ways that big data analytics will revolutionize your supply chain.
Perhaps the most significant influence big data analytics have on supply chain management is in customer service. Because big data enables the acceleration of supplies in conjunction with customer orders, organizations are able to deliver faster service at less expense. Even the most experienced department supervisor will struggle to keep up with all sources of supplies, much less determine which supplies have the best prices on top of that. Big data management finds and reports this information in an intuitive layout. This way, supervisors are provided the necessary information to make smarter decisions, at no additional work to themselves. Because big data is so user-friendly, managing supply and demand has never been more straightforward.
Shipping and Delivery
Another excellent benefit of big data analytics is its real-time tracking capabilities. Big data enables the tracking of orders and shipments throughout the supply chain network. This allows managers to know the exact location of packages, whether incoming materials or outgoing orders, which is crucial to scheduling and service. Most shipping companies allow customers to track their package up to the exact location and its exact predicted delivery time. Because of this, it is now expected that most if not all businesses can provide this as well. With big data-enabled technology, this is possible.
Accurate forecasting is crucial for an efficient supply chain. If your organization is over or underproducing, or even producing at the wrong time, you are actively losing revenue. Having access to real-time data on sales trends and keeping up with technology developments and equipment upgrades can significantly help organizations determine future demand of products before receiving actual orders. This allows organizations to work proactively, filling orders before they are placed to maximize efficiency and equipment usage. In addition, by increasing or decreasing the production of a particular item, you can increase the speed of filling orders and ensure that demand is always met, and thus revenue is earned to its most total capacity.
Hand-in-hand with forecasting is product sourcing. If your organization is continuously turning away potential customers due to products being out of stock, big data analytics can resolve this. Big data solutions can offer a real-time view of product demand, product sales, and the sourcing process, which help you accurately match inventory with demand. Additionally, once big data solutions are implemented, retailers can stop marking products as "back-ordered," as they will always know the precise lead times for sourcing them.
Before a product reaches its final destination with the customer, it moves along the supply chain network through a line of suppliers specialized in transportation, logistics, and packaging. With so many intermediaries, there is ample opportunity for errors to occur. These errors may appear as delays, incorrect deliveries, and other interruptions, all of which can significantly impact the supply chain as a whole. Fortunately, big data analytics empower real-time management by assessing vendor performance against a set of key performance indicators (KPIs). These KPIs can include vendor profitability, on-time service, and customer reviews and complaints, all of which ensure that your organization has a clear picture of who you are working with. With this information, you can set policies to create alerts if KPIs do not stay within your defined range to guarantee quality assurance and minimize interruptions.
The shopping experience for customers has drastically changed in the past few years. Customer demand is growing, and customers expect exactly what they want when they want it. Today, organizations hold the responsibility of meeting these demands and delivering an elevated level of service. Personalization is key to satisfying customers and differentiating your product from competitors. But there is a balancing act to be made – you need to offer unique and personalized products without offering irrelevant offerings that can irritate customers. So, how do you manage these conflicting customer preferences?
Using big data, retailers can evaluate customer interactions throughout all channels – social, media, and web – to determine how customers use the product they have already or intend to purchase. With this information, retailers can then segment their supply chain to offer customers configurable products where they can select features such as color or size. This ensures that products are relevant to consumers while still allowing some personalization to entice buyers.
The final influence that big data has on supply chains is pricing management. The knowledge of available supplies and their respective costs is critical to determining the price of your final product. Labor and shipping costs may be fairly consistent, but the cost of supplies often fluctuates with changing market resources and supply chain flow. As a result, it can be difficult to pinpoint, and if chosen incorrectly, it could result in a significant revenue loss. In using big data, organizations can rely on sensible average pricing for supplies, in addition to their value on the wider market. This allows organizations to keep pricing at levels fair to your company's profit expectations and customer needs - it's a win-win.
Big data is playing an instrumental role in supply chain management. With real-time analytics capabilities, big data is able to resolve several pain points at strategic, operations, and tactical levels. Ranging from procurement to delivery, big data is making significant impacts on all supply chain activities. This solution allows for organizations to improve customer service, optimize forecasting and production, and maximize revenue. The analytics reports provided by big data solutions enable decision-makers to achieve operational efficiency and monitor performance to improve productivity. In addition, organizations will also reduce costs and improve service levels. Overall, by implementing big data analytics in your organization's supply chain, you will improve your business through faster and better decisions, allowing you to exceed customer expectations and perform more efficiently than ever.
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