How Big Data Analytics Can Improve Supply Chain Efficiency
“Big data” is the term used to describe data sets that defy traditional methods of analysis due to their complexity, and often, the way they represent human behaviours. Although the crunching of these types of numbers can be daunting, big data analytics has a key role in modern supply chains. Big data is just one part of the rapid rise of technology in supply chain services, and when used properly, it can help inform future demands and optimize current supply chain practices for better efficiency. Here are just some of the ways that big data analytics can shape your supply chain solutions.
Create a Unique Brand Experience
One of the most significant impacts of big data on supply chains is how it can offer information on the customer experience. Call centre logs, loyalty programs, customer surveys, web logs, mobile data, and more can all come together through analytics to create a 360-degree image of your customer’s needs and expectations. By taking these findings and using them to shape your processes and activities, you can deliver a stronger brand experience to your customers. This could be as simple as offering different shipping options and prices or as complex as redesigning delivery routes to more closely align with where the majority of orders are coming from.
The use of data analysis in supply chain management is particularly well-suited for enhancing the traceability of your products. One of the most time and money-intensive activities a company can perform is trying to integrate and process disparate databases in order to track down products that have to be recalled or retrofitted. This is an intensely data-driven activity by definition and it is therefore fortunate that big data analysis is designed to work with such large, normally unwieldy sets of information. When used in this manner, big data will help to reduce the level of risk exposure in your supply chain.
Offers Stronger Demand Forecasts
Big data analysis pulls information from a multitude of sources in order to produce reliable and accurate findings, predictions, and demand forecasts that might otherwise get missed. For example, big data elements like on-shelf-availability, transaction data, purchase orders, competitor pricing, and social media monitoring can combine to detect shifts in customer demand and make appropriate forecasts about how this will impact orders down the line. This information can then be used to adjust inventory levels or production in order to avoid shortages or overstocking.
Look to Lean Supply Solutions to Harness Big Data Analytics in Chain Management
Lean Supply Solutions is a third-party order fulfillment company in Toronto whose operations are based around the Lean Methodology, a proven philosophy focused on eliminating any operations, equipment, or resources that are not capable of adding value to clients’ supply chains. By striving to ensure that the right products are provided to the right customers at the right time, Lean Supply Solutions is able to offer consistent, accurate, and quality results.