Everything becomes buffering and buffering becomes everything. – Tom McCarthy
Managing on time performance (inbound or outbound) is a struggle for every retailer. Whenever there’s a delivery failure, somebody asks the inevitable question: “How do we prevent this from happening again?”
Sometimes the cause is known to be out of your control – a freak snowstorm leaves trucks stranded or there is temporary congestion at a facility. For these types of unpredictable reasons, it’s simply not possible to achieve 100% on-time delivery all the time.
But what about cases where a supplying location is chronically at 80%? What if it’s dozens of locations with this problem (which is not uncommon in retail)?
What we’ve seen is that, faced with this problem, many retailers have developed the bad habit of plastering over these issues by arbitrarily increasing their planning lead times. In many cases, they have even developed analytical approaches to calculate the demonstrated order-to-delivery times on historical orders and transfers, then automatically update the planning systems with increased lead times in an effort to boost on time delivery performance.
What often happens is that on time performance does improve (for a time), which tends to validate this approach. Then results start to slip again, triggering another wave of analysis or an increase in the frequency of lead time updates to ‘stay on top of things’.
The problem with this approach is that it assumes two things:
- That lead times are something that ‘just happens’ over which nobody has any control.
- That when on time delivery performance is failing, it must be because people aren’t being given enough time to do perform their tasks.
The actual order-to-delivery cycle time in a supply chain is the result of discrete processes (order management, picking, delivery and receiving). These processes must be routine, repeatable and – most importantly – designed to achieve the goal against which you’re measuring them.
The routine and repeatable part likely isn’t the issue in most cases. The amount of time it takes to pick an order or drive a fixed distance doesn’t have a lot of variation (especially when lead times are rounded up to the nearest day). Once you know what those standard times are, there really shouldn’t be any need to change them very frequently.
Yes, there are rare, infrequent events that will cause lateness, but those events can’t be blamed for chronically poor on-time performance.
More likely than not, the culprit is that one or more of the processes is not designed to achieve on time performance.
As an example, it’s commonplace for retailers to prioritize promotional shipments to stores that aren’t due to be shipped until next week ahead of regular shipments that are due to be shipped today. If the due date is not the primary prioritization criteria, then you can’t expect it to deliver high levels of on time performance.
It’s also commonplace for suppliers to prioritize their shipments based on the size of the customer order or the price being paid for the goods, neither of which has anything to do with when stock is required.
The problem here is that the processes involved do not respect dates – or at a minimum, don’t use the due date as the top prioritization criteria. How, exactly, does increasing lead times (which merely lengthens the amount of time between the order date and the scheduled ship date) solve that problem?
All it really does is erode the ability to adapt and react to changes and necessitates additional safety stock at the destination location to cover a longer frozen window.
Like anything in the supply chain, the key to solving chronic issues with on time delivery is to find the root cause of the problem and take the necessary steps to address them. To the extent that the processes are within your organization’s control, that can be relatively straightforward (assuming the intestinal fortitude exists to prioritize all shipments based on a due date, promotional or not).
If the issue is with a supplier, there needs to be a common understanding as to how their underlying processes work and what conditions are necessary to deliver consistently on time. This goes beyond using a scorecard to try to ‘shame them into submission’.
By adopting Flowcasting and sharing a time-phased schedule of their requirements, retailers can provide very valuable preparatory information to their suppliers that will give them visibility to shipping requirements weeks and months before the purchase order is ever placed.
Don’t fall into the bad habit of setting your lead times based on a data mining exercise. Look at them with a critical eye, identify where chronic failures are occurring and attack the root cause.