You hit many of your sales and fulfillment targets. In other areas, you wish you could have been more efficient or effective.
Now’s the time to take a hard look at which peak omnichannel operations went well and which fell short of goals. By carefully analyzing peak data now, you can capture lessons learned and apply them to optimizing next year’s peak performance.
Past Peak Data for a Better Peak Future
When you’re in the middle of peak, you capture data in near real time to try to understand changing demand and quickly adapt processes to improve sales and customer experiences. You’re looking at a snapshot to understand a moment in time. You might even use machine learning for more predictive inventory placement and staff scheduling.
After peak, take the time to analyze your entire dataset to determine what went well and what didn’t. This is your opportunity to explore every aspect of your operations.
Start with end-of-day or end-of-shipment-cycle data. Then analyze it over a week. Then extend your analysis to the entire peak period. You want to capture the end state – plus all the actions that contributed to that outcome.
Look at performance metrics in areas like overall sales, order fill rates, split shipments, how long it took from online order placement to delivery, how many ship-from-store orders bounced from store to store before they were fulfilled, and so on.
Examine total orders as well as orders by store location. If a store missed or exceeded targets, drill down to figure out why. Did an underperforming store experience unexpected demand? Did it lack staff or supplies? Could an overperforming store handle even more orders? Can you roll out its strategies to the rest of your stores?
Analyzing Across Omnichannel Operations
You can apply your lessons learned to key areas of your peak omnichannel operations. Here are a few:
Use your data insights to determine where last year’s demand came from. Which stores had the most sales? To which locations were the most items shipped? That will tell you where to place inventory – so you can offer merchandise where customers want it, staff your stores appropriately, and reduce shipping time and costs.
Store-to-store and channel-to-channel fill rates – You want to be sure all your channels are performing optimally during peak. That requires appropriate metrics. For example, your target overall fill rate might be 98%, but your target per-store fill rate might be 80%.
Use your historical data to both establish and meet these targets. Last year’s peak performance should help district and store managers uncover any gaps. Did stores have enough staff? Did staff have enough shipping supplies? Did carriers pick up shipments at the right times? Your data should point the way to root causes – and the right solutions.
Managing peak-season associates and inventory – You should know the volume of orders that flow through your store-fulfillment channel. You should also measure how volume fluctuates during each day and even each hour of peak. That knowledge will help you manage store staffing – as well as inventory.
At some times of day you may have more walk-in customers. At other times you may handle more ship-from-store orders. Your data should tell you how much time it takes an associate to serve a customer and how much time it takes to pick, pack and ship an order. Layering that knowledge over store activities should enable you to staff accurately.
At the same time, during peak, inventory is in flux from the moment a store opens. So you need a clear picture of how much inventory goes to walk-in traffic and how much goes to fulfillment traffic. That way, you can make sure you have enough inventory for each channel – without overages.
Leveraging stores close to the customer – Identifying where customer demand is coming from will help you leverage the right stores for walk-in traffic and the right fulfillment-enabled stores to decrease shipping time and costs.
A heatmap will let you easily visualize store locations and demand sources. Look at where the majority of orders are shipped to and see whether store (and distribution center) locations match demand. Break out where there’s the most in-store, BOPIS and ship-from-store sales. That knowledge will enable you to accurately plan inventory placement, staffing and fulfillment capabilities for next year’s peak.
From Past to Forecast
Ultimately, last year’s peak omnichannel data should enable you to proactively plan for next year’s peak – rather than reactively adjust throughout peak season. Combine your historical data with external factors such as market trends. Consider tapping consultants for guidance. Layer in new products or categories you might be adding, as well as planned promotions.
Last year’s peak performance might have hit targets. By applying lessons learned, next year’s peak performance is much more likely exceed them.
Anthony Hockaday is director of client services for Radial.