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Presented at International Fastener Expo 2021

In early 2020 as COVID swept across the globe, supply chains began to reel as the consequences of the pandemic forced actions such as factory shutdowns and workforce shortages. The resulting leadtime increase led to a jump in order quantities to account for the extended time between receipt of shipments, but between March and May of 2020 there was a massive plummet in demand. All of a sudden businesses had more inventory than they had had in the recent past and half the demand, leading to a tremendous jump in ‘Days on Hand’. 

Fortunately, this March to May stretch did not last and demand recovered quickly and continues to climb. The only issue is leadtimes have not recovered like demand, in fact, they have continued to decline. This has led to the opposite problem experienced in March through May as businesses now have declining ‘Days on Hand’ caused by rising demand and inability to get items on the shelf. 

The above is obviously applying a broad brush to the current set of issues created by COVID, but is representative of the “general” inventory issues present for most businesses. Using some anonymized client data from Hydrian, it is possible to see how these effects have played out with a real business and lends itself to a discussion on how to mitigate the effects of the current state. 

Pulled from actual client data, we can see in the graphic below that since September of 2020, lead times have not only risen but the spread between the median lead time and 75th percentile of leadtime has widened. This means that it takes longer to get what you ordered from your supplier AND the actual count of days you will receive it in is less predictable, culminating in increased inventory values. 

In the chart below, it is clear to see how leadtimes have affected inventory investment. Inventory on order has risen to account for increased demand (shown by the red line), longer leadtimes, and less predictable lead times. However, we also see inventory on hand declining which tells us that receipt of shipments cannot keep up with demand due to these leadtime delays.

With unprecedented ‘inventory on order’ levels, the potential for an “ocean” of excess stock is a real concern if supply chain challenges suddenly resolve themselves. However, what we know about COVID is its impacts are hard to predict, so being prepared to be nimble regardless of circumstances is the new requirement. Below are some strategies to minimize stockouts in the face of huge demand and supply uncertainty and ensure that when lead times do recover and customer demand returns to normal, inventory doesn't balloon in value due to a bullwhip effect. 

1. Develop highly responsive inventory controls (e.g. min/max) and buying strategy

a. As lead times or demand grow, get more inventory “into the pipeline”

b. Conversely, be ready to reverse changes if demand falls or suppliers improve

2. Work with suppliers to adjust PO qtys, push / pull deliveries, and cancel if needed

a. Establish guidelines for “finalization” dates of PO qty, release date, etc

b. Share sales forecasts with suppliers (and ensure they utilize them)

3. Recognize unavoidable excess before it hits your shelf

a. If quantities can’t be changed / cancelled, start liquidating excess before it arrives

b. Consider price reduction, added marketing spend, or other promotion

c. When it makes sense, divert incoming POs to other facilities

4. Track appropriate metrics for measuring supplier and internal performance

a. Track both median / average as well as the distribution of lead times

b. Inventory turns / days on hand, in-stock rates, delivery speed, etc

A link to the full presentation can be found here.

Presented at Home Delivery World 2021

Before beginning, it is important to define two different types of stockouts in a network with multiple distribution centers:

1) Local Stockouts: Out of stock at the “best” or closest distribution center to the customer but in-stock in other distribution centers across the networ

2) Global Stockouts: Out of stock at all distribution centers in the network

There is obviously a cost to global stockouts which is fairly straightforward to understand, but there is also a dramatic cost to local stockouts. Based on experience with our customers, the measurable cost of a local stockout in a national, multiple distribution center network consists of the below, (this does not account for costs associable to intangibles such as diminished brand reputation or customer lifetime lost value): 

• 20% of order lines ship from non-local distribution centers 

• 15% of orders have 2+ shipments due to splits caused by the local stockout

• 2.5 additional zones are traveled on average for non-local shipments at a 20-25% freight cost premium

• 1.8 days of additional delivery time is added on average

• 14% of total outbound freight cost is attributable solely to the local stockout

One option commonly seen to minimize the effects of local stockouts is to ship material from one facility that has the needed inventory to the facility closest to the customer.  However, this approach will significantly increase freight costs, transit time / distance, and shipment counts per order, as well as causing higher rates of damage and return. The below details 4 different strategies for managing a multi-line order and an approach we would recommend using. This can also be seen in the graphic below or in the full presentation here. 

1) Ship Complete

• Minimizes shipments / DC labor

• Can result in holding partial orders for long periods

2) Ship Each Line from Closest DC

• Ensures fastest average delivery of all line items

• Can result in many customer shipments over many days

3) Least Freight Cost

• Calculates freight cost of all combinations, choosing least cost method

• Does not consider delivery speed or number of shipments

4) Economic Service Model (Hydrian recommendation)

• Assigns cost to service outcomes (e.g. speed / # shipments) as well as freight

• Results in overall lowest cost based on factors enterprise values most

Fill Rate vs In-Stock Rate: What's the Difference and Why It Matters

At the start of any engagement with a client, one of our first tasks is to agree on the language we'll use to talk about inventory performance. One of the most important metrics is how much of your product is in-stock and available for sale to customers each day. In this post, we'll talk through different ways to measure in-stock performance, how to calculate each one, and how each one can help you improve customer service in different ways.

Definitions

A sample of terms we hear clients use to talk about inventory performance include:

• Fill rate

• Backorder Rate

• In-Stock Rate

• Service Level

While each of the terms above has a textbook definition, we've found that it's rare for clients to use that exact definition in their operation. Below, we'll stick to the most common usage of each.

Fill Rate / Backorder Rate

Fill rate and backorder rate both refer to the percentage of actual demand from customers that you were able to fill immediately from inventory on the shelf. In companies that do not allow backordering, order lines that cannot be filled from stock are generally cancelled, and the customer is notified.

For example, assume a customer orders 100 units of an item, and you only have 50 in stock. You ship the 50 and backorder or cancel (depending on your policy) the remaining 50 units. In this case, you have a unit fill rate of 50% (from here on out we will use "fill rate" to mean both fill rate and backorder rate).

Unit, Line, and Order Fill Rate Examples

In the example above, we are using units shipped from stock for our fill rate. Many companies will instead measure their line fill rate. The difference is that 100% of the units on a line must be in-stock for that line to count as in-stock. So if a customer placed a 10 line order and all lines were fully in stock except the one above, that order would have a 90% line fill rate - we don't get any credit for the 50 unit partial fill.

An order fill rate works the same way - all units on all lines of the order must be 100% in-stock in order for the order to count as in-stock. If we received 10 customer orders and all but the order above were 100% in-stock, we'd end up with a 90% order fill rate. We don't get any credit for the 9 perfect lines on that last order, because the 10th line only had a 50% unit fill rate. Another term for order fill rate is "perfect order rate" since from the customer's perspective, a successfully filled order, where all units on all lines are in-stock, is the best possible outcome.

We'd recommend tracking all three - unit, line, and order fill rate. Unit fill rate is the standard in many industries, but it can be dominated by low-impact items if you sell some SKUs at extremely high quantities relative to others. Line fill rates can correct for that sort of bias. Finally, order fill rates are probably the best measure of a total customer service success.

In-Stock Rate

In-stock rate measures the percentage of expected demand that you have in-stock and available for sale. There are two major implications of using expected demand, rather than actual demand, as an inventory metric:

1) In-stock rates are generally based on a sales forecast, and as such, are subject to forecast error. For example, if you haven't sold an item for a couple of months, you may have a zero forecast and won't "ding" yourself if you are out of stock on that item. Of course, that doesn't mean that a customer won't buy that item. The broader and longer the "tail" of low volume items in your catalog, the less reliable in-stock rate will be as a metric.

2) In almost every business we work with, sales are depressed when an item is out of stock. Even among companies that don't purport to advertise or share inventory status with customers, we see fewer orders arrive on days when items are out of stock vs in-stock. What this means is that fill rate (which measures only actual demand from customers) is going to be a falsely optimistic measure of performance, since you can't have a backorder if the customer never bought the item! This is the main reason to utilize in-stock rates as well as fill rates in your metrics. (We'll do a future article on "spill rate" which will allow you to quantify the financial impact of lost sales when out of stock.)

When is an Item In-Stock?

Generally, we recommend counting an item as in-stock if it has at least one day of expected demand or the median customer order quantity (whichever is greater) in stock at the start of the day. However, we find that unless you run an extremely tight inventory, the result you get using this method will be extremely close to the result achieved if you count any item that has any units available as in-stock.

Weighting In-Stock Rate

Most of our clients that utilize in-stock rate track this metric for each sales velocity class. For example, they will have an in-stock rate for A, B, C, and F items. While this is a good start, we strongly recommend weighting in-stock rate by sales volume at the item level.

For instance, if you have an item that sold 80 times in the last 90 days, and another item that sold 20 times, both may be "A" items. But the former item is four times more impactful to customer service if it is out of stock. A single, weighted in-stock rate is usually the best indicator of overall customer experience.

Simply take all the SKUs you stock, find the percentage that are in-stock on a given day, and then weight that percentage by each item's forecast, recent sales, or some other volume indicator. We recommend weighting by order lines rather than units if possible, and find that lines sold during a rolling 90 day period is a good measure.

Service Level

Service level is a term that has a wide range of definitions among our clients. Generally, it refers to either the fill rate, backorder rate, or in-stock rate... depending on which of those metrics the client in question tends to prioritize. So feel free to be as liberal as you like with this term.

 

One of the questions we are asked by nearly every new client is: "What should my fill rate (or service level / in-stock rate / backorder rate) be?" Without diving into item-level sales and supply chain data, this is an impossible question to answer, and we strongly caution against trying to set fill rates against an industry benchmark.

We have clients with profit-maximizing fill rates in the 80% range, and clients with profit-maximizing fill rates well above 99%. This is a number that will vary not just by industry and company, but also among the different items sold within a single warehouse. In this article, we'll talk about the 5 main factors that you should use to determine the right service level for any item in your inventory. In the end, the goal is to reallocate inventory dollars from low-quality items into higher quality, maximizing profit.

1) Profitability

Items that are out of stock will sell less (if at all, depending on a company's backorder policy). Thus, you want to make sure that the items which return the most profit are also in-stock the most often.

2) Holding Cost

Item that are more expensive to keep in inventory should be more conservatively stocked, which will naturally lead to lower fill rates. For example, all else being equal, you want large, bulky items like bubble wrap to have a lower in-stock target than, say, a small pack of washers with the same cost and margin.

3) Sales Volume and Variance

As said above, many companies target different service levels based on sales volume. This is the right approach. Another thing that should be considered is sales variance. For example, assume two items have the same total sales, but one item sells smoothly and consistently while the other has more "chunky" demand. The more consistent item should have a higher target in-stock rate.

4) Lead Time Length and Variance

Items which have long or highly variant leadtimes are harder to stock efficiently. They require more safety stock, and thus, will have a lower profit-maximizing in-stock target.

5) Strategic Importance

Finally, if an item is an own-brand, "front page" flagship, or otherwise strategically important item, you may want to target a relatively high in-stock rate, no matter how it stacks up using the other metrics above.

 

Most of our clients receive notices from vendors when leadtime changes significantly. Sometimes these notices are at the product level, for example when a SKU is on extended backorder. Occasionally, a notice may impact many items, such as when a manufacturing facility is temporarily shut down.

The COVID pandemic is causing more frequent supply chain disruptions, leading to an increase in leadtime updates from vendors. Hydrian has been getting a lot of questions about how to respond, particularly when it comes to updating leadtimes within an ERP or purchasing system. In this short article, we will provide some pointers on how to use leadtime updates to improve customer service while avoiding unnecessary excess stock.

Determine the type of leadtime change

The most important question to answer before taking any action in response to a leadtime update is: how long will the new leadtime be in effect? There are generally two possibilities here:

1. The first and most common situation is that the new leadtime is due to a temporary delay, such as when a needed component is backordered, or a facility is shut down for cleaning. In this situation, once the backorder is resolved or the facility is back online, all open orders can be fulfilled and will ship simultaneously. We refer to these leadtime delays as shark fins.
2. Alternatively, the new leadtime may represent a long-term change. For example, a vendor may be shipping product from a new facility that is further from your warehouse. In that case, leadtimes will likely never return to their prior level. We refer to this leadtime changes as plateaus.

When to act on a leadtime update

Many systems automatically update leadtimes based on recent receipt history, which is generally a good thing. However, depending on the type of leadtime change that has occurred, it's important to ensure that the leadtime in the ERP or purchasing system is reflective of what future leadtimes will actually look like.

In the first scenario, there is nothing that can be done to avoid stockouts - ordering more product will only cause an even larger receipt to arrive once the disruption is over, exactly when the extra inventory is no longer needed. In this case, the vendor's leadtime update should be used solely as a service tool, to communicate with customers about when they can expect delivery. Receipts impacted by the temporarily increased leadtime will need to be excluded from the system's calculation, or leadtimes will need to be manually adjusted downward so that inventory targets are not increased in error. This is illustrated in the chart below.

In the second scenario, leadtimes must be adjusted upward in the ERP or purchasing system, so that inventory targets can be increased appropriately. This will likely need to be done manually, to reflect the new reality and override the older, shorter leadtime history. The goal here is to get the system to increase the amount of product on-order at any given time, so that high service levels can be maintained despite the longer transit time to your facility. This is illustrated in the chart below.

One of the counter-intuitive rules of inventory management is that after a sudden drop in sales (like the one many of our clients are experiencing) inventory on-hand will rapidly increase before falling back below its original level. This is because vendor purchase orders are, to some extent, created to replace future sales that are going to occur during leadtime. If sales during leadtime are lower than expected, there will be more inventory remaining on the shelf when receipts arrive, leading to excess stock.

The chart below shows a hypothetical client that has around $1MM in weekly COGS, and typically has $4MM in inventory, with another $4MM in open POs not yet received. Leadtime is 2 weeks. At week 3, we've modeled a 25% sales drop. We assumed that the drop was immediately detected and that inventory targets (and thus purchasing) were immediately reduced:

 

Note that despite a drop to zero purchasing as we attempt to draw down the inventory, dollars on hand increases 12.5% to $4.5MM before finally starting to fall.

Had vendor leadtime been longer, the increase in inventory would be proportionally larger. For example, if this was an overseas vendor with a 12 week leadtime instead of the 2 week leadtime modeled, inventory would continue to build by $250k per week to a total of $7MM, a 75% increase! That increase will happen regardless of reductions in purchasing, because all of that excess stock was already on order when the sales drop occurred.

Mitigating the Spike

There are a few ways to minimize the damage from rising inventory value if there is a sudden drop in sales:

• Ensure that forecasts and inventory targets are updated frequently (at least weekly) during periods of high sales variability.
• As new inventory targets are set, look for items that will be overstocked once all open POs arrive. Contact vendors to see if these POs can be at least partially cancelled or pushed back.
• Utilize forecasts with a higher bias towards recent sales so that sales drops and spikes are quickly detected and properly weighted. If your system uses a simple monthly forecast (e.g. last 90 days / 3 or even last 12 months / 12) then extensive manual overrides will be needed.
• If space or cash are a concern, it may make sense to utilize discounts or other marketing activities to increase sales velocity closer to normal levels, thus reducing the amount of excess stock.