Today we will be continuing our series on Inventory Management with the concept of “Safety Stock.” I know it may not be the most exciting part of running a business, but getting it right can make a huge difference. Managing inventory is a part of nearly every business out there, but is particularly important for retailers who sell their products (inventory) for a profit. Nevertheless, even inventory management is also important to service providers (plumbers, electricians, etc.) for the very reason that they must manage their parts inventory to be able to service their customers.
But what is Safety Stock? Why should you care about it? Read on, friend.
What is Safety Stock?
Safety stock, in a nutshell, is the extra inventory you keep on hand to protect against the unexpected. Assume for a moment that you maintain your inventory levels to service your typical demand. That's great! But what happens when demand isn't typical? If you didn't have a level of inventory reserves this deviation from the norm would cause a stock out.
There are two forms of ‘the unexpected’ when talking about managing inventory:
Unexpected demand by customers (a sudden rainy day causes customers to come in and buy all your umbrellas for sale), or
Unexpected delays in supply (that same rainy day washes out a bridge and your regular umbrella shipment can’t get to you).
But when you have a level of Safety Stock (aka 'Buffer Stock') on the shelf, you are keeping a little cushion to ensure you never run out of your most important items and you can ‘weather the storm’ of the unexpected.
Another example:
Imagine a situation where you’re managing a popular coffee shop. It’s Monday morning, and you’re gearing up for the usual rush. Looking in the back of the store, you realize you’re out of coffee beans because your latest order hasn’t arrived yet. Shoot. And what happens next? Customers walk out frustrated, and you’re left with empty cash registers. This is where safety stock would save your bacon.
But how do you calculate how much safety stock you should keep on hand? Let’s explore two methods: the simple method and the service level method. (You can read more about Safety Stock and its calculation in The Tradesman’s MBA)
Safety Stock Example
Returning to the coffee shop example, let's say your coffee shop sells an average of 20 bags of coffee beans per day and your supplier usually delivers 5 days after you place the order, but can sometimes take up to 7 days.
On your busiest days, you might sell as many as 30 bags, while on a slow day, it might drop to 10. You want to ensure you have enough beans to handle these fluctuations without overstocking.
How many extra bags of beans should you have on hand to make sure any spikes in demand or delays in delivery don’t impact your ability to sell? There are a variety of ways to calculate Safety Stock and Google will give you a million examples. But they all boil down to two methods: A statistical method and a Simple Arithmetic method.
Calculating Safety Stock Using the Simple Method
The simple method is straightforward and a great starting point. It focuses on maximum and average demand and lead times.
Here’s what we know:
Maximum Daily Usage (MDU): 30 bags
Maximum Lead Time (MLT): 7 days
Average Daily Usage (ADU): 20 bags
Average Lead Time (ALT): 5 days
The formula is:
Safety Stock = (MDU × MLT) - (ADU × ALT).
Plugging in the numbers, we get:
Safety Stock = (30 × 7) - (20 × 5) = 210 - 100
Safety Stock = 110 bags.
What this means is that, using the simple method, you’d keep 110 extra bags of coffee beans on hand to make sure you never run out. This buffer covers you for those peak days and longer-than-usual lead times.
The downside of the simple method is that it's simple. A little too simple, if you ask me. And this lack of sophistication can be expensive; 110 extra bags isn’t nothing to sneeze at. This extra 110 bags ties up cash and adds to your holding costs which only drives up your overall costs (more on holding costs in a later essay).
Lucky for us, there is another way to calculate safety stock that, while a bit more complicated to calculate, is more sophisticated and, in many instances, more precise in how much extra stock you should keep on hand. It’s called “The Service Level Method.”
Calculating Safety Stock Using the Service Level Method
Instead of answering the question, “How much extra inventory should I hold,” the Service Level Method answers a different question. It answers the question:
"If I accept a x% risk of a stockout, how much extra inventory should I hold?"
This is definitely a different question. In order to answer this question, the service level method factors in the variability of demand and lead time and uses statistics to help you get to your answer. Don't worry if you've never studied statistics, the formula is not too bad and once you understand the concenpt and have your variables, it becomes very straightforward.
At the heart of the Service Level Method is the use of the probability and risk tolerance. What this means then is that you must determine ahead of time what level of risk of a stock out you are willing to accept. Let’s say you are willing to accept a 5% probability of a stock out. Stated another way, this means that on any given day, you will have a 95% likelihood of having stock on hand for your customers.
Now, a word about 100% certainty versus the 95% we're using here. Understand that 100% certainty is impossible. The reason 100% certainty is impossible is because this would mean that for every product you sold, you would have to immediately replace it that same day and/or have an infinite stock level in your warehouse. This, of course, is not going to happen, so we must go with something less than 100%. The 95% probability is the threshold that science uses when determining certainty.
The formula for The Service Level Method is:
Where:
Sigma d: Variability of Demand
Sigma s: Variability of Supply
L: Days of coverage
Z: 1.65, the “Z score” that equates to a 95% service level.
As you can see, the Service Level Method needs a few different numbers than what you did with the Basic Method. These look pretty complicated, so let’s step through this slowly.
First, let’s define what sigma means: It represents variability; a statistical measure that determines how much a value changes.
For example, using the coffee example above, the average daily usage (demand) was 20 bags per day. But, when we measure demand on a daily basis, we get:
Sun | Mon | Tue | Wed | Thur | Fri | Sat |
18 | 22 | 21 | 20 | 22 | 18 | 21 |
These daily values definitely average out to 20 bags per day. But how much do these values change each day? This is what ‘sigma’ (variability) measures and what the Service Level method needs for that extra level of precision.
The easiest way to calculate variability is in Excel using the ‘=var.s’ formula. When you plug in the daily values using the ‘var.s’ formula, you get a value of 2.9. This means that, on a daily basis, the demand varies by 2.9 bags per day. So open an excel spreadsheet, type in '=var.s' and select the values (Sunday thorugh Saturday) to arrive at the weeks variability of demand (Sigma d).
But what about the variability of supply (Sigma s)? This is the measure of how much your deliveries vary from your supplier. Looking at our records we see that
Shipment 1 | Shipment 2 | Shipment 3 | Shipment 4 | Shipment 5 |
5 days | 7 days | 3 days | 8 days | 2 days |
When we calculate variability (sigma) in excel using the same formula for these values, we get a result of 6.5 days. This means that the delivery times vary by 6.5 days overall. OK. Two down, almost there.
The final variable we must determine is “L.” or days of coverage. This is a judgment call on your part. Let’s just say we want 5 days of coverage for the purposes of this example.
You’ve probably noticed by now that we haven’t discussed ‘Z’ in the formula yet. This is called the ‘Z-score.’ It is a fixed number that essentially represents the 95% value you determined earlier. This value comes from statistical tables and, were you to change your risk tolerance to, say, 90% or 85%, the Z-score would also change. To avoid complicating things, let’s just stick with 95% and its corresponding Z-score of 1.65.
We now have the information we need to calculate our safety stock using the Service Level method.
Sigma d: 2.9
Sigma s: 6.5
L: 5
Z-score: 1.65
This means that, if we keep 26.3 bags in reserve as Safety Stock, we only have a 5% probability of a stock out.
As you can see that 26 bags of beans is a significant reduction from the 110 bags that the Simple Method would recommend for us! While calculating safety stock levels took us quite a bit more work, it would result in significant savings and greater precision.
Conclusion
Regardless of which method you decide to use to determine the amount of extra stock you should carry to account for the unexpected, all you REALLY need to know is that you don’t have to guess! There are methods (and more than just these two) to help you determine how much you should keep in reserve to ensure you minimize the likelihood of running out.
If you'd like to learn more about this and other key topics that help you manage your business efficiently and successfully, may I recommend The Tradesman's MBA? It covers all the topics you need to operate your small business effectively and efficiently. Planning, Strategy, Finance, Accounting, Inventory Management, Marketing and Project Management are all covered to help you avoid costly mistakes.
And, if you'd like to learn how BreathEasy Business Management and Consulting can help you lower your costs and keep more money in your pocket, please consider scheduling a discovery call. I'm absolutely positive that any issue you're seeing is fixable. You don't have to go it alone!
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