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In today’s environment of demanding and fickle consumers, the importance of meeting customer demand and minimizing out-of-stocks is crucial. How do you do that?
There are a number of considerations, in this article I’ll cover one of the major ways, lead time reduction. In part two I will discuss another often-overlooked and underappreciated line of attack.
Let’s look at replenishment in the foodservice industry, as this is a particularly challenging industry with unpredictable and erratic demand.
In foodservice, time is your enemy. Extra inventory can quickly turn into waste, while any delays in the replenishment of inventory can result in lost sales, disappointed, or even lost customers.
How do you walk this fine line of tracking demand without carrying too little or too much inventory?
Forecast accuracy is important, but given the inability of most systems to forecast at the store level it is much more important to respond to demand signals more quickly. Shortening your replenishment cycle time to 2 days will have a much greater impact on service levels and virtually guarantee you are never out of stock.
A Typical Replenishment Example
Let’s take an example. Say the notification of point-of-sales (POS) transactions and updated inventory positions occurs at the end of each day.
Day 1: Capture POS and transfer to planning system. Update inventories. Update sales histories.
Day 2: Analysis of inventory and generation of new purchase orders.
Day 3: Vendor receives PO, analyzes and commits to a ship date based on available supply.
Day 4: Assuming the vendor has plenty of stock available; the order is shipped from the vendor distribution center.
That’s pretty fast for a system where each node analyzes and acts within 24 hours.
Real Time Information Means Rapid Replenishment
But what if it were faster? What if there were a real time connection between stores and DCs? What if information could flow between trading partners within the same network? And what if we could automate the “analyze” steps and thus slash response time?
Day 1: Capture POS and transfer to planning system. Update inventories. Update sales histories. Automated purchase orders, automated order confirmation, automated shipping orders.
Day 2: Order ships from vendor DC.
It’s possible with a real time, multi-party cloud platform.
A Real Time Multi-Party Platform
With a real time, multi-party platform there’s no waiting for a nightly refresh, information is instantly shared with customers and their suppliers. Real time visibility is available to all trading partners, while data flows across the network, ensuring all parties are always in sync.
A real time platform also bridges the chasm that exists between traditional planning and execution, allowing plans to be formulated more accurately, based on real time execution data.
Consider stock-outs. If there’s nothing on the shelf or if menu items are unavailable, consumers cannot buy and you lose sales. Or worse, they may opt to purchase a competitor’s product, or you might lose them as a customer completely.
This is where a real time cloud platform can help. First, since there is no lag, it is reasonable to expect replenishment time in our example to go from 3 days to 1 day. The impact of this reduction can hardly be overstated. It means 2 days of sales where there would have been zero. It means satisfied customers where there would have been two days of dissatisfaction and potential loss of loyalty.
Second, since statistical engines use historical data to predict the future, if that historical data includes zero sales, true market demand may be understated. An advanced cloud platform can adjust for this by isolating stock-out periods and replacing zeros with an estimate of what sales would have been had there been stock available to purchase. This creates a more realistic picture and helps the engines produce more accurate predictions in the future.
This is just scratching the surface. A real time cloud platform offers other interesting and powerful possibilities, including, single version of the truth for all parties, end-to-end visibility, “demand sensing,” automated ordering and demand translation, and reduced IT costs. I will discuss some of these aspects in a follow up article.
Essential Reading on Foodservice and Replenishment
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