In today’s economy, consumers have higher expectations than ever before, and retailers are under growing pressure to amalgamate purchasing channels in order to provide a more streamlined shopping experience for their customers. Big data could be just the solution to help generate increased efficiency to the retail supply chain at a time when it is much needed.
Technologies such as sensors and GPS solutions are amassing large amounts of data, but unless your organization is filtering and analyzing this data and incorporating it into its supply chain strategy, this technology is not being utilized to its full potential. Technologies like these, along with analysis and continuous feedback within the supply chain between sales, product teams, suppliers and warehouses – strengthens your organization’s supply chain and helps avoid revenue and margin loss.
The key to Big Data is real-time analytics. This complements the end-to-end visibility of the supply chain and enables your organization to act fast enough to avoid revenue and profit loss that can take place at several points in the supply chain. Below are 7 ways your organization’s supply chain can take advantage of Big Data analytics.
1. Customer Service
The key benefit of big data analytics regarding supply chain management is customer service. By accelerating the source of supplies in conjunction with customer orders, faster service is delivered with less expense. Even the best department supervisor is unable to keep up with all sources of supplies, much less which supplies presently have the best prices. Big data management affords that information in an intuitive layout.
2. Shipping and Delivery
Another benefit of big data analytics is real time tracking of orders and shipments. Knowing the exact location of packages, whether incoming supplies or outgoing orders, is crucial to scheduling and in turn, service. Since today’s technology lets consumers know the precise location of a package, customers expect a business to be able to provide that information when prompted.
If your business is overproducing, or producing at the wrong time (when consumer demand is not there) chances are you are are losing revenue. Data on sales trends, along with technology advances and equipment upgrades can assist an organization to determine the future usage of any product well in advance of receiving the actual orders. This permits an organization to work on a proactive basis to fill those orders. By increasing or slowing down production of particular items one can increase the speed of filling orders.
4. Optimizing vendor management
Before a product makes it to the customer, it moves along a line of suppliers that specialize in transportation, third-party logistics, packaging, etc. With so many stops along the way, there is ample opportunity for errors to occur such as delays, wrong deliveries, and other interruptions. Big data analytics solutions empower real-time management by assessing vendor performance against a set of key performance indicators (KPIs). These KPIs include vendor profitability, on-time service and customer reviews and complaints. Policies can be produced to create alerts if the KPIs do not stay within the defined range.
5. Automating product sourcing
If your organization is turning away potential customers due to products being out of stock, data analytics can help. Big data solutions offer a real-time view of the product demand, product sales and sourcing process. Moreover, once the big data solutions are implemented, retailers can stop marking certain products as ‘backordered’ as they always know the precise lead times for sourcing them.
6. Personalizing service
In the time of the catalog, retailers would send out one mailing and expect customers to go through it and pick out the items they desired. In today’s economy, however, consumers demand far more – and the responsibility is on organizations to deliver this elevated level of service. Personalization is key, and irrelevant product offerings can result in irritated customers. But how are retailers expected to keep everyone’s preferences in order?
With big data, retailers can evaluate customer interactions amongst all channels – social, mobile and web – to establish how the customer is utilizing the products they purchased or will purchase. For example, retailers can segment their supply chain to offer some shoppers configurable products, where they can select features like color or size.
7. Pricing Management
The knowledge of available supplies and their costs is the key to determining price for your final product. While labor and shipping costs may be fairly consistent, the cost of supplies often fluctuate with market resources and supply chain flow. By using big data analytics you can often rely on sensible average pricing for your supplies, as well as their value on the wider market. This allows you to keep pricing at levels that are fair both to your company’s profit expectations and your customers’ needs.
Concerns that may arise with the incorporation of big data in a supply chain environment
The drawbacks of integrating big data in your organization’s supply chain process can seem daunting. It often requires enhancing the capabilities of current business systems as well as procuring and implementing new software tools. There are ways to avoid these concerns.
For example, it may be easier to implement the solution one department at a time rather than implementing the system enterprise-wide. The initial implementations will provide quick-wins for the organization while the learnings will benefit subsequent implementations.
Litcom can help you explore big data opportunities. We provide strategy, technology, analytical and implementation support to assist your organization put big data to work today. Our team can help your organization assess, anticipate and manage changes in processes necessary to implement sustainable big data solutions. For more information, please contact Litcom at: email@example.com.