The information age is upon us. Sensors are being applied to almost every element of our lives, creating data that can provide insight and intelligence to better support decision-making. Data alone, however, is not enough and the volume of data being produced creates its own challenges. It’s only with the use of advanced analytical software that Big Data can become actionable intelligence.

The retail sector is fast becoming a trailblazer in big data analytics, seemingly finding benefits wherever it places sensors and draws information. Data derived from primary suppliers through to the store floor and beyond is directly impacting the bottom line and creating a competitive advantage for the most pioneering retailers.

In retail, it all starts with an effective supply chain. When guided by a clear understanding of the strategic priorities, market context, and competitive needs of a company, big data offers significant new opportunities to enhance customer responsiveness, reduce inventory, lower costs, and improve agility. In fact, 64% of supply chain executives consider big data analytics a disruptive and important technology, setting the foundation for long-term change management in their organizations, according to SCM World.

Data-driven decisions eliminate guessing, leading to measurable results. (Results from two fashion retailers. Source: ChainLink Research)

Delivery Management

Delivery management is a fundamental part of the supply chain and big data analytics are enhancing real-time delivery management by analyzing weather, traffic, and truck location feeds to determine the exact time of delivery. Technology, such as RFID, is being used to provide environmental information for high-value goods in transit, RFID can even track the exact location of items in case they are separated from the delivery and even let the retailer know if packages have been opened.

Order Picking

Order picking is a labor and time intensive process, or at least it was. Big data analytics along with RFID technology is providing a faster and better order picking process for big and small retailers alike. By incorporating information like orders, product inventory, warehouse layout, and historical picking times, big data analytics is optimizing and simplifying the warehouse according to the needs of the retailer.

Vendor Management

Complex networks of vendors can foster a confusing and inefficient supply chain. Big data analytics allow for real-time vendor management through well-defined key performance indicators (KPIs), be they packaging vendors, transportation, logistics or drop ship vendors. KPIs assess delivery record, profitability, customer feedback and whatever elements the retailer feels relevant to optimizing, adapting or cancelling vendor relationships.

Product Sourcing

Accurate demand and inventory information combined properly puts an end to frequent revenue losses due to out-of-stock situations. Back-ordered items also become a thing of the past with the implementation of big data analytics for product sourcing. Big data enabled product sourcing analyzes purchase history, marketing, lead times, and other factors such as promotions and weather, to create accurate demand forecasts. Tying this into supply chain data, retailers can ensure they always have the products their customers demand.

Segmented Supply Chain

Through big data analytics customer demands can also feed directly into the supply chain to provide a greater level of personalization. Collecting post-sale data from social media and customer feedback channels allows retailers to understand how their products are being used. Statistically analyzing such data can then influence product design and bring about personalization of aesthetics and functionality. In modern consumer culture personalization is key to developing sales and customer loyalty.

Throughout the supply chain big data analytics is creating a competitive advantage for retailers. An Accenture study found that 97% of supply chain executives report having an understanding of how big data analytics can benefit their supply chain, yet only 17% report having already implemented analytics in one or more supply chain functions. The same study concludes that embedding big data analytics in operations leads to a 2.6x improvement in supply chain efficiency of 10% or greater.

The information age is upon us and those who embrace it will be at the forefront of their industry.

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