The power of data in retail supply chain management. By Amanda Sinkewitz
Consumers are a key figure in supply chain management and their needs and opinions will affect the suppliers’ decisions. Thankfully, technological tools can make a big difference in this arena.
In this article, I discuss the power of data in retail supply chain management and how retailers and suppliers can improve operations by successfully implementing it into their business strategy
Enhance the shipping process
Tracking delivery of shipped goods has improved over the years. However, with the use of big data, it can be developed further by enabling real-time delivery management that analyzes weather, traffic and vehicle location feeds that determine the exact time of delivery.
This capability helps retailers keep track of their shipments from the vendor to their warehouse or store and even updates customer deliveries. Best of all, it can be implemented – whether internally or by using a third-party – without requiring significant changes to the existing supply chain setup.
A similar use of big data can improve order picking, resulting in better order fulfillment. Historically, order picking is a labor-intensive process but with big data even smaller retailers can improve their picking process, resulting in better order fulfillment.
Big data solutions allow data from different sources, like orders, product inventory, warehouse layout and historical picking times to be analyzed, based on the rules defined by the retailer, to improve the overall picking process.
Best of all, as these solutions can optimize the picking process in simulation mode, by tweaking various parameters and settings before rolling out the final process to the warehouse and store, this results in minimal impacts to operations.
Enhancing vendor management
Most retailers work with multiple vendors, which can foster a confusing and inefficient supply chain. Through using big data, it allows for real-time vendor management by reviewing vendor performance against a set of key performance indicators. These KPIs can include vendor profitability, on-time service and customer feedback.
These KPIs are tracked in real-time by integrating with vendor systems, meaning rules can be created to generate alerts if the indicators do not stay within the defined range.
By using this real-time analytics solution, retailers are able to ensure the quality of service and the profitability of their business stay at the desired levels without requiring any additional efforts.
A recent study revealed 80 percent of consumers want personalization from retailers and that customers now expect it throughout the customer journey.
Through the use of big data, retailers can analyze customer interactions across a variety of different channels – such as purchasing history, web browsing data, loyalty programs, in-store beacons and even social media – to determine how prospects and customers are using the products they bought or will buy.
Many companies may not be aware of the need to segment their customers and currently have a ‘one size fits all’ strategy, but this doesn’t work in today’s environment.
The concept of supply chain segmentation involves the alignment of customer channel demands and supply response capabilities, that are optimized to maximize profitability and customer value across multiple market segments.
This allows retailers to provide their products across a diverse target market and in turn increase sales and profitability.
Increase the ability to forecast
Accurate sales forecasting is critical for retail companies to produce the required quantity at the right time. Nowadays, companies have access to huge and complex amounts of data from various sources, including suppliers and customers. But data collection and analysis can be time-consuming and more often than not, can result in out-of-date data.
Companies look at various performance indicators from previous products to help build future forecasting reports such as purchase history, location data, seasonal and time periods.
However, retailers can employ third-party analytical tools to integrate data from a range of systems, combined with pre-determined performance indicators such as purchase history, geographical data, seasonal, pricing and time periods, it helps businesses uncover up-to-date, actionable insights to significantly enhance the ability to forecast demand.
Supply and demand
Popular culture in recent years has had a huge impact on consumer buying behavior. Only recently, following the premiere of Netflix hit ‘The Queen’s Gambit’, sales of chess sets grew 125 percent.
While trends come and go at a rapid pace, it’s important retailers can keep up with consumer demand so they don’t miss out on sales opportunities.
Over 30 percent of shoppers will switch to a competitor the first time a product is unavailable on their preferred site. Failing to have the stock to fulfill this demand, will, at best, put you at risk of missed sales opportunity.
By using location-based data, suppliers can recommend retailers to adjust product allocation based on current sales and inventory trends. This minimizes missed sales opportunities and, in some cases, can recommend when stock should be replenished, so that you have enough to fulfill demand.
Amanda Sinkewitz is Sr Retail Intelligence Manager at SPS Commerce. SPS Commerce is the world’s leading retail network, connecting trading partners around the globe to optimize supply chain operations for all retail partners.
It supports data-driven partnerships with innovative cloud technology, customer-obsessed service, and accessible experts so its customers can focus on what they do best.