Just how “bad” is that stock out for your customer?
In an ideal world, your products would have on-shelf availability whenever your customer needs them. However, this is often not the case for many businesses. It’s also essential to note that, not all stockouts or out-of-stock (OOS) carry the same severity levels or require the same form of action. In this blog post, we’ll discuss a simple coding system using descriptive analytics that can help you easily identify different severity levels for your stock out.
Creating Your Inventory Stock Out Level Codes
To create the stock-out severity codes, we are assuming that you:
- Use replenishment types to plan inventory
- Hold finished product inventory for “Make to Stock” and “Re-Order ”
- Hold NO finished product inventory for “Make to Stock,” “Assemble to Order,” “Engineer to Order” etc.
- Stocked out means zero finished product inventory on hand
- Further, let’s assume it’s not stocked out unless it is “Make to Stock” or “Re-Order Point.”
Now we’re ready to begin.
Defining Your Stock Out Severity Codes
Code 1.0: What’s the worst that can happen?
Suppose we have nothing on hand and open customer orders are greater than zero. What we’d like to know is if there is anything in transit. That way we could say, “It’s on its way.” This means we need to compare zero on hand to in-transits and open orders. With no in-transits and open orders greater than zero, we’ll need to get things going to appease the customer. Time to start talking to the Master Scheduler and building your arsenal of knowledge for a customer in need.
Code 1.0: On Hand=0; In-Transit=0; Open Orders>0
Code 2.0: What’s next to worst?
When we see nothing on hand and customer orders greater than zero, we look to in-transits. If we see in-transits greater than zero, but less than customer orders, we can appease the customer with partial orders while talking to the Master Scheduler.
Code 2.0: On Hand=0; In-Transit<Open Orders; Open Orders>0
Code 3.0: Getting back to normal.
By now, you see where this is headed with on hand being zero and in-transits greater than open orders.
Now we can truly say, “It’s on its way.”
Code 3.0: On Hand=0; In-Transit>Open Orders; Open Orders>0
Code 4.0: What if there are no open orders and nothing in transit?
Compare to the forecast.
The worst case in this scenario would be for nothing on hand and nothing in-transit, but with a forecast greater than zero.
Code 4.0: On Hand=0; In-Transit=0; Open Orders=0; Fcst>0
If we see in-transits and compare them to forecasts, and with an in-transit less than the forecast, we’re in a situation similar to Code 2.0, only less severe since there are no open orders. Now is the time to review production schedules for execution and review safety stocks.
Code 5.0: On Hand=0; In-Transit<Fcst; Open Orders=0; Fcst>0
Code 6.0: Normal mode, just stocked out
Nothing on hand, but in-transits greater than forecasts means we’re okay as long as the order does not come in before the in-transit arrives, then we’re back to Codes 2.0 & 3.0.
Code 6.0: On Hand=0; In-Transit>Fcst; Open Orders=0; Fcst>0
The illustration below shows how you would interpret an alert using this type of coding system.
Table I. Conditional Logic for Stock Out Severity and Alerts
Managing Stock Out Risk
Everybody experiences stockouts, but it’s nice to know more about them to manage their impact on the customer. These alert codes will help, but remember, they come to you at the SKU level, where we meet the customer. The Stocked Out Severity Code is but one of many descriptive statistics to keep you informed.[Read More: Improving Data Visibility with Descriptive Statistics: How to Visualize the Product-Volume-Variability-Velocity Matrix] Consider a toolkit containing SKU views of volume, variability, and velocity:
- Pareto analysis for volume (hurdle rates for high/low volume)
- COV (coefficient of variation) by SKU
- ADI (average demand interval) how fast does it move? Every month? Every six months?
Knowing more about the SKU keeps you sleeping at night and reduces the anxiety that everything has top priority.
Enjoyed this post? Subscribe or follow Arkieva on Linkedin, Twitter, and Facebook for blog updates.