BI and Predictive Analytics in 2015?
Supply chain managers tired of being without the analytics tools typically bestowed upon marketing and sales departments at top tier retailers will no longer be forced to manually wade through spreadsheets to understand warehouse operations. In 2015, the warehouse will finally have access to its own suite of business intelligence tools delivering real time predictive analytics that help professionals at every level of the supply chain make informed decisions that improve the overall customer experience. Here is a rundown of who’s benefitting from real-time predictive analytics tools in 2015 and beyond:
The Retail Executive Gets Analytics to Predict Staffing and Capacity Requirements
Keeping up with seasonal demand fluctuations means fighting a constant battle to hire just enough new team members to meet capacity. Hire too many and you’re wasting money and training resources. Hire too few and you risk spreading staff too thin and sending out late or incorrect orders. By leveraging data on picking throughput, projected sales growth, and overall workforce productivity all from a single easy-to-read platform, Supply Chain VPs can make more informed predictions about anticipated seasonal demand and how much warehouse capacity to add.
The Warehouse Supervisor Uses Analytics to Manage Daily Delivery Deadlines
In an era when customers have little tolerance for late orders, warehouse managers need a full picture of operations to make sure trucks leave on time with complete manifests. Predictive tools that combine delivery information with pick rates and daily assignments can give warehouse managers a real time picture of the warehouse so that they can make decisions on where to move item selectors and how to rearrange product to prevent productivity lags.
The Shift Supervisor Leverages Analytics to Assess Worker Productivity
Without analytics on worker productivity, understanding which item selectors are performing optimally and which individuals could use additional help can be a tedious process. With real-time productivity data, not only can shift supervisors foster a healthy competitive environment but it’s also easier to identify lags and to correct them immediately. Shift supervisors can leverage the combined analytics from time and attendance records, pick locations, the warehouse map, and a user’s transaction history to address challenges related to warehouse layout and personnel training.
Thanks to the warehouse data revolution, more companies will be able to make smart predictions and stay ready for change as the retail industry continues to evolve at its fastest pace ever.