Inventory Management Review

Advanced Economic Order Quanitity

In previous articles I've referenced the Economic Order Quantity (EOQ).  This article is going to be the first of a few articles detailing various aspects of EOQ.  This first post will discuss the basics and go step-by-step through an example of how to use EOQ when trying to determine how much to order for a single good that has a known projected demand.

First of all, what is EOQ?
EOQ is a mathematical formula designed to minimize the combination of annual holding costs and ordering costs.  There is a lot of hype about just in time inventory systems (JIT), which achieve smaller inventories through very frequent orders, but frequent ordering can often result in an over-spending on ordering costs.  Even though companies often miscalculate their ordering costs, which makes frequent ordering seem costly, EOQ is an important tool for determining what inventory should be.  Let's move on to the example to help explain what EOQ is.

Chuck Co. is a firm that manufactures toys requiring a part that costs $12, and can be received from multiple suppliers.  The firm, which recently began ordering once a week instead of twice a month, in order to reduce inventory, wants to know how much it should order at a time because it has noticed that while their holding costs have decreased, they seem to be spending more on overtime for floor managers than they used to.  While Chuck Co.'s inventory manager is happy, the plant manager is not sure the reduction in holding costs is worth the overtime pay.  Here's the data they've provided us with:

Demand (variable D)
Annually, the part for the toy is consumed at a rate of 150,000 per year.  While there is seasonality in the toy industry, this firm produces at a level rate because of union agreements.

Ordering Costs (variable S)
Chuck Co. has identified 2 major costs associated with ordering; floor manager overtime required and plant manager time.

The floor managers find themselves with very little time to process orders during their shift.  When an order needs to be made, a floor manager from the day shift needs to work 2 hours of overtime to shop the multiple suppliers and place the order. Overtime pay is $21/hour.

The plant manager spends 1 hour per order to approve the order, determine the tax implications of the order and authorize payments. Earning $80,000 per year and working 2000 hours per year, the plant manager at Chuck Co. earns $40 in the 60 minutes he requires to process the order.

Total, the ordering cost is $82 per order.

Holding Costs (variable H)
When I wrote about Holding Costs, I mentioned the different factors that drove holding costs.  For Chuck Co. the most major factor is opportunity cost.  Another toy in their product line is currently earning 20% a year for every dollar invested in it.  Chuck Co. would like to invest more into the product line but their credit rating and unhappy investors are currently preventing this from happening.  Each dollar in inventory is another dollar that could be in the 20% gain product line.

The opportunity cost for every dollar invested in inventory is the 20% that could be invested in the other toy, plus an additional 2% from rent and other various holding costs.  Ultimately, the holding cost is 22% annually.  Multiply this by the cost of the part ($12) and the holding cost is $2.64 annually.

EOQ
Using the information presented above, the EOQ formula can be used to determine the optimal order.

The formula is:
EOQ=SQRT{(2DS)/(H))}

Plugging in the numbers given from Chuck Co. we get:
EOQ=SQRT{(2*150,000*$82)/($2.64)}=3053

According to these calculations, the most efficient amount ordered is 3502 per order.  Spread out over the annual demand of 150,000 per year, the part should be ordered 49 times per year (150,000/3053).  Seemingly, leading the once per week reorder calculation to be roughly correct, however, this calculation has an error in it.

Common Misconceptions Regarding Ordering Costs
Chuck Co. identified 2 major costs associated with ordering.  Only one of them however is actually driven by the amount of orders placed.  When using EOQ to minimize ordering costs, only costs that can actually be minimized should be taken into consideration.

Specifically, only the overtime hours in our example are true ordering costs. The plant manager definitely spends time ordering and he is getting a salary during those hours, but this salary is a part of his overall duties as the plant manager.  If ordering frequency went down by 10%, it is unlikely that his hours and salary would be scaled back.  His salary is a sunk cost and must be treated accordingly.

The floor managers' hours, however, actually do go up and down in accordance with the number of orders placed.  Each order they place, they receive $42 of overtime compensation for.  Thus, $42 is our true ordering cost. Let's take a look at how this affects our calculations:

Correct EOQ=SQRT{(2*150,000*$42)/($2.64)}=2185

This order size leads to 68 orders per year (150,000/2185), making the old calculation, and the once per week practice wrong.

EOQ can be a very effective tool for helping to optimize inventory.  However, in order for it to be effective, it requires good and thoughtful data.  This means having decent demand projections, well-evaluated holding and ordering costs.  The next post will discuss how much money this correct order size actually saves Chuck Co. and will cover some derivations of the EOQ formula.

Different Inventory Systems

Assuming a firm has performed Economic Order Quantity and Reorder Point analysis to determine how much to inventory to order and when to reorder inventory, the firm still needs to be able to keep track of inventory levels so they know when they reach the Reorder Point. This article will detail a number of different inventory systems starting with the most archaic and working up to the most advanced.

Physical Counts (Periodic System)

The most basic method of inventory tracking is physical counts. Physical counting is exactly what it sounds like; if you want to know your inventory level, you better take off your shoes so you can count on your toes when your fingers run out. Prior to my work described in Notes from an Inventory Management Consulting Job, the firm I consulted for relied on physical counts to try and figure approximately where they were at. Lucky for them they didn't bother with ROP because as you can appreciate, it's very difficult to reorder at the reorder point if you aren't constantly aware of your inventory levels.

Two-Bin System

The two-bin system is only slightly more sophisticated than the physical count system. Using the marvels of modern technology, this system uses two bins of materials. When one bin is empty, it's time to re-order.

Perpetual Tracking

A perpetual track is the method I designed in the previously mentioned consulting job. This method of counting is demand driven. Instead of counting how many items are in inventory, you count how many leave inventory. The demand can be tracked by batches of inventory usage, such as demand that is entered once a week, or they can entered in real-time which provides the ability to continuously monitor inventory levels. If you are already in the practice of counting demand, this is a great way to track inventory because it involves little additional effort. For what I set up, it was ideal because there is little variability in the products that are demanded. For a supermarket, this can be more difficult because of the variety of products sold. Luckily, the next section highlights how firms with broader product lines get over this hurdle.

Universal Product Code (UPC)

UPC is a system that supermarkets first implemented in the 70s (more info). This requires unique codes to be put on all types of inventory and is usually accompanied by a bar code that can be scanned via infrared scanning guns. If you've been to the supermarket at in the last 30 years and had a pulse at the time, you probably noticed that everything you buy is scanned into their system. In addition to helping the market determine how much you should pay, this also gives supermarkets, and other firms, the ability to track and count the movement of any and all inventory with a simple infrared scan.

My favorite example of infrared product tracking is the implementation of package tracking that Fedex and UPS have incorporated into their business processes. In case you're unaware, both Fedex and UPS now track all packages at every stage from pickup to delivery. The beauty behind the system these two companies have implemented is that not only does it directly help their operations management, but it also directly improves customer service. Now, customers can log onto a Fedex or UPS website from anywhere in the world, enter in the tracking number they received when they dropped the package off for shipping and know exactly where their package is in real time. Marketing studies have shown that informed customers are typically more satisfied and this process is a wonderful example of how the businesses are able to inform themselves and their customers with one technology.

Radio Frequency ID (RFID)

RFID, which I have written an article about, is another method of tracking inventory. Instead of using technology to track inventory as it is moved, RFID counts inventory automatically from a remote location. This is superior to perpetual inventory tracking or perpetual inventory with the UPC for a couple of reasons. Most notably is that RFID accounts for shrinkage (lost inventory, not what happens to Costanza in cold water). As much as we might not want inventory to just disappear, the fact of the matter is, things grow legs. Also, inventory is often scrapped. Perpetual counts that lower inventory levels only when there is demand don’t account for lowered inventory when a good is stolen, unless the thief enters it into the system to be a nice guy. RFID counts what is actually there, and it can tell you exactly where it is.

Different systems have their time and place so you should consider what's right for you. It may turn out that the two bin system is a great fit for your operations. If holding costs are really low, why not go for the two-bin approach. Hell, you might not want to even invest in two bins. Maybe you can easily do a physical count on a daily basis. The key is to find a system that works for your needs.

Inventory Holding Costs Quantified

I have been receiving a lot of inquiries regarding the specifics of calculating holding costs. By and large, you can read about what drives holding costs in my article A Simplified Look at the Pros and Cons of Inventory. This article is intended to provide greater detail regarding the quantification of holding costs. The first section is going to discuss rough estimates and the second section will discuss methods involved with detailed holding cost analysis.

Rough Estimatations

Typically, holding costs are estimated to cost approximately 15-35% of the material's actual value per year. The primary factors that drive this up include additional rent needed, great insurance premiums to protect inventory,opportunity costs, and the cost of capital to finance inventory.

A More Detailed Look at Holding Costs

First of all, it is generally best to think of holding costs in terms of  their annual costs. To do this, you will need accurate representations of your annual inventory levels. My previous article, Average Inventory Levels, details this step by step. Personally, I suggest tracking inventory month by month and using these values to find the average holding cost as opposed to taking the year's beginning, the year's end and averaging the two.

So now you have your average inventory. This needs to be performed for finished goods, work in process, and raw materials inventory.

Now, you need to figure out what percentage of the total value of the good is being incurred as a holding cost. Cost of capital and opportunity costs should be the first things you think of. If you are financing the goods with a 10%/year loan then the holding costs are at least 10% annually. When you are evaluating the total value, include the value of any labor that has been added to the goods.

Next step would be to consider the cost of storage. Based on the inventory you need to carry, how much space do you need and how much does that space cost per unit as a percentage of each good.

Again, determine the insurance cost that should be allocated to each good as a percentage of that good.

Evaluate the probability that a good will rot, or otherwise become obsolete and assess the average rate at which this occurs and use this to quantify the average holding cost per good as a percentage of that good on an annual basis.

Determine if there are any other costs you can think of that are incurred simply by being in possession of a good. If you can think of any, treat them as holding costs.

Add up all of these percentages and together they make your holding costs.

Average Inventory Levels

I have recently received a lot of inquiries regarding average inventory levels so I thought I would devote and article regarding how to find them. The first half of this article covers how to find what inventory levels should be, and the second half covers what they have been in the past.

Part I: How to Optimize Average Inventory Levels

This section is mainly here to provide a brief description for how optimal inventory levels for materials are kept assuming the company is a textbook example with no strange variables. Essentially, this section can serve as a starting point for inventory managers. 

First thing you need to determine the ideal inventory levels is a material's Economic Order Quantity (EOQ). This is the amount you should be ordering when you place orders.

Next you need to determine your Safety Stock (SS). This is the amount that you should have remaining when the EOQ arrives. 

Basically, safety stock is the average bare minimum you will have at any give time, and EOQ+SS is the average maximum amount you will have at any given point in time. This should be intuitive because safety is what you have when your shipment arrives and when the order arrives (EOQ) it gets added to the safety stock. 

I say average minimum and maximum because you might not receive the EOQ exactly when you planned to and therefore may have more or less. On average you should have the SS amount when you receive shipments. Between these two average minimum and maximum values lies your long-term average inventory. 

The formula for this is:

Optimal Average Inventory=(EOQ+SS+SS)/2 

This is for materials. For finished goods, you should aim to keep an inventory level designed to prevent a stock out. This level would be a safety stock of finished goods, thus making the ideal average inventory for finished the safety stock value based on your company's service level. 

Part II: How to Assess Inventory Levels 

Simplistic Method - Historical Inventory Levels

Most methods of accounting take the beginning inventory of a period, add it to the ending inventory of a period, and divide by 2. This essentially provides the mathematical average for a given month. 

For example, if your inventory level for a good is 2000 on July 1st, you produce 3000 units and sell 1000 units by July 31st. This leaves you with 4000 units. The formula is: 

Avg. Inventory = (Beginning Inventory+(Beginning Inventory+Units Produced-Units Sold))/2 

Avg. Inventory = (2000+(2000+3000-1000))/2 = 3000 

Or more simply:

Avg. Inventory = (Beginning Inventory+Ending Inventory)/2 

Avg. Inventory=(2000+4000)/2=3000 

So this covers historical looks using an accounting approach. A lot of firms use this method to evaluate their average inventory levels. Personally, I have a problem with this method which I believe the following example will help to illustrate: 

Daily Weighted Average Inventory Approach

Suppose you start with 10,000 units on May 1st. Also suppose you produce 10,000 units in that month spread out across 21 business days. Now (and this is the important part) suppose you sold 20,000 units in May. This brings the ending inventory to 0. Using accounting methods, the formula gives us 10,000 as the average inventory. 

So why is this so bad? In short, because the average inventory is not 10,000 units. In fact, there were only two days in which 10,000 units or less were held and these days were May 1st (10,000 units) and May 31st (0 Units). Assuming that production was level through the 21 day working month, this means that 500 units were produced daily, thus raising inventory by 500 units a day until inventory was dropped by 20,000 on the 31st. Here is what the inventory levels look like in the month of May (each record represents the end of 1 working day in a 21 day work month). 

1) 10,500
2) 11,000
3) 11,500
4) 12,000
5) 12,500
6) 13,000
7) 13,500
8) 14,000
9) 14,500
10) 15,000
11) 15,500
12) 16,000
13) 16,500
14) 17,000
15) 17,500
16) 18,000
17) 18,500
18) 19,000
19) 19,500
20) 0
Average=14048 

Clearly, this method of average inventory provides much different average inventory values than accounting procedures. It gives each day of the month an equal weight as opposed to giving the first and the last day of the month 50% weight each which I believe to provide more accurate results.

My example may seem a bit extreme, but consider a company who produces large runs of goods for another company and agrees to hold onto their inventory delivering once a month. In this case the supplier could start and end with 0 units each month end ship it all off, ending with 0 units each month making the average finished goods inventory 0. Their average inventory sure as hell isn't 0. They are higher, and they may be much higher. For this reason, it is very important to carefully choose how you assess your average inventory levels.

Why are inventory levels so important?

To put it simply, average inventory levels are important because they allow you to determine how much money you have tied up in inventory and how much value your inventory assets hold. Helping to determine what they should be can help cut back on unneeded inventory, and knowing what they are can help you determine average warehouse usage, inventory risk, percentage of assets that are made up inventory, holding costs, etc. To review information regarding high and low inventory levels, refer to my previous article, The Pros and Cons of Inventory.

A Subjective Look at Order Quantities

For the most part, this site focuses on mathematical optimization techniques and descriptions of optimization techniques. This article is intended to give a brief introduction of other factors to consider when managing inventory levels.

In a previous article, I detailed the economic order quantity (EOQ), which is the mathematically "perfect" amount of inventory to order designed to minimize holding costs and ordering costs based on a given demand. Generally speaking, this is a very good level to order. Now I am going to provide potential reasons why perhaps it might be a good idea to order a different amount: 

EOQ is too large

For whatever reason, your holding costs are very low for a particular item and you simply do not want to hold that much inventory. Maybe you don’t even have enough space for it. In some cases the EOQ may necessitate an increase in warehouse space which will drive up fixed costs to an undesirable level. 

A large economic order quantity may result in inventory levels that carry too much risk. Computer companies such as Dell or Apple have a particular level of concern regarding obsolescence risk. Ordering a year's worth of processors may prove to be a poor decision in the event that a better processor is released three months after the shipment arrives. The fashion industry is also at great risk for obsolescence. 

Other firms may be more concerned about damage to large levels of inventory in the event of theft, fire, or other natural disasters. The less inventory you have on hand, the less than can be destroyed while you are responsible for it. 

EOQ is too small

Potentially, you may feel that the EOQ is too low for a number of possible reasons. Perhaps you fear a rise in the cost of your raw materials and a futures contract isn't appropriate for your situation. You may decide that the additional holding costs incurred by ordering a large quantity are less than the raise in price your supplier could soon be charging you. 

Perhaps you just don't want to bother with the EOQ. One firm I worked with had so much excessive space and was ordering materials that were so inexpensive compared to the rest of their operations that it wasn't even worth a second thought in trying to determine how many suppliers to order. They decided it was worth their while to just order as many as they thought they could reasonable expect to eventually use up.

  I generally don't recommend this method for firms with large inventory expenses, but if inventory is a very small part of an overall operation, maybe it's not worth the hassle to try and optimize.

Prefer to use multiple suppliers

Many firms feel more comfortable when they order from multiple suppliers, which can have many advantages. Two that come to mind right away are potential price and quality leveraging advantages and reliability insurance. Having multiple suppliers provides the opportunity to keep suppliers fighting to give you the best quality at the best price in fear that they may lose your business. Multiple suppliers also allow reliability because one supplier's inability to fill your order can be another supplier's opportunity to gain business. 

Unfortunately, if you do decide to receive shipments from multiple suppliers, you may lose out on quantity discounts and you may be forced to spend more time ordering. In an ideal situation you could switch off between the suppliers and order from two or more with the frequency in which you would order from just one. Regardless of increased ordering, utilizing multiple suppliers does bring up questions regarding the strict following of EOQ which should be evaluated prior to switching to or from multiple suppliers. 

What I have just listed is a partial list of reasons that could be taken into consideration with evaluating EOQ at your firm. This article is intended as a reminder that there are more variables to order quantities than merely holding costs, ordering costs, and demand. This is not to say that the EOQ formula is worthless, but rather that while it is an important part of managing inventory, it should not be followed blindly. Like all aspects of inventory management, remember to look at the inventory policy in conjunction to the rest of your firm’s policies.

A Simplified Look at the Pros and Cons of Inventory

I'm selling it sooner or later anyway, aren't I?

I spend so much time working with inventory that I often forget how confusing it can be to beginners. The most common mistake, and the one I made when I first started learning about inventory, is that it shouldn't matter how much you have because you're going to sell it sooner or later anyway. In a sense, this is true. Even if you turn your inventory over once every 3 years, you are selling all of it and the inventory helps to prevent stock outs and backorders. However, there are some serious costs to holding inventory. 

Anytime inventory is held, there are holding costs. Holding costs are simply the costs that are incurred just by holding onto inventory. These costs can come from a variety of sources. Here are just a few common costs associated with high levels of inventory: 

Higher rent from increased need for extra warehouse space to hold extra inventory. 

Higher premiums needed to insure extra inventory. 

Potentially, the inventory could spoil, expire, or become outdated and lose value. 

Oppurtunity costs. What else could you have invested the money and warehouse space in had you not been spending it on inventory? 

Remember, companies have a limited amount of assets available to them. These assets are aquired from money raised through equity and debt. Excessive inventory is a misuse of these assets because it essentially an investment in something that is just going to sit around. 

So why hold inventory?

The simple answer is that inventory is held in order to fill unexpected changes in demand and deliveries from suppliers. If there were never any changes in demand and if suppliers could constantly deliver supplies in the quantities needed, then there would be no need for inventories (excluding work in process inventories and negligible day's end inventories waiting for outbound shipping). 

However, demand does fluctuate, as do lead times from suppliers. Because demand fluctuates companies are not sure how much of a certain good to produce on a given day. Companies can make predictions, but the fact of the matter is, predictions typically only give a rough estimate of what will be needed on any particular day. One solution to this problem is to maintain a workforce with a very high unutilized capacity and to simply not use it most of the time, but to have it available in the event of a day with high demand. The other solution is to carry inventory. 

Inventory is a way or preserving excess capacity. On the days when demand was light, the workforce overproduced. Their work was stored as inventory and now if there is a day with very high demand that is beyond the capacity of the workforce, the inventory is there as a safety net against backorders. 

So why not hold loads and loads of inventory?

Well, don't forget about those damn holding costs. 

So why not maintain a workforce with a ton of slack capacity?

As much as the work staff would enjoy this, you can imagine this would be very expensive to maintain.
(On a side note, this is essentially what service sectors of the economy have to do. I remember I worked as a hotel valet when I was younger and there would be plenty of times when it would be so dead I wouldn't park a car for hours. But when it got busy, boy would it get busy. You can't inventory services and the ramifications of a stock out (in this case that would mean that there is no one to get your car) are too costly to deal with in many service positions.) 

So how much inventory should I hold?

This is subject to a wide variety of conditions. Simply put, you need to evaluate your holding costs, your backorder costs, and your demand. From there, it gets pretty tricky and I unfortunately already named this article "A Simplified Look at the Pros and Cons of Inventory" so as much as I'd like to help you, my hands are tied...what with the tiltle already being up and all.  Luckily some of my previous posts deal with some of the mathematics involved in determining some facets of optimized inventory levels.

What to do about seasonality

Without a fairly accurate sales forecast, managing inventory is essentially impossible. There is no way to determine optimal inventory levels and a corresponding production schedule without a projection of sales. Deciding on quantity of shipments received from suppliers is also out of the questions without a forecast. Once the forecast lands on your desk, you can begin to do your work. The first thing you should notice regarding the sales forecast is whether or not the product is seasonal or not. Assuming it is seasonal, there are several issues to consider regarding its production schedule. Ultimately, you need to decide whether or not you want to produce the product at a constant level throughout the year (thus building up inventories and selling them off during the busy season) or whether or not you want to produce products at a level that chases demand (producing the items right before you can sell them).

The first issue to look at is the holding cost of your product.  If holding costs are very low relative to the revenue received per unit, it may be worthwhile to produce at a constant level. Even if you only sell the item during the fall, production in winter that is held as inventory during spring summer may be worthwhile if holding costs are low enough. Chances are, if your product is that seasonal, it is not worthwhile to produce at a constant level.

Another issue to look at is how chasing demand may affect your production schedule. If you decide to produce only during four months of the year in order to accommodate the four months worth of seasonal demand that you have, you should consider how intensive those four months will be. If your company produces a plethora of other products, then this may be a simple reallocation of resources. Ideally you would have another product that just so happens to be sold during the remaining seasons. A good example of this is in the lawn mower industry. Unsure with what to do with themselves during the winter season, they began to produce snow blowers, which is a perfect fit as it is a similar design with an opposite seasonality…personally, I feel they should have just sold to the southern hemisphere, but then again, I’m not too sure about how many lawns there are that needing mowing in Paraguay. If however this is the only product your company makes, then there should be some serious considerations regarding the idle time of company resources. Perhaps outsourcing will become an appealing choice once you realize that without outsourcing, you will have 8 months of idle capacity.

Another important factor in determining the choice of production schedules is how your suppliers will respond. Perhaps they will prefer that you produce all at once so you can have large quantities sent to you which may result in quantity discounts. However, it is also possible that your supplier would prefer to produce at a constant level.

These are just some of the factors that will help you determine what do when facing the management of a seasonal product.

Safety Stock

First of all, here's the formula so you don't have to dig through my well-written article for it.

Safety Stock:  {Z*SQRT(Avg. Lead Time*Standard Deviation of Demand^2 + Avg. Demand^2*Standard Deviation of Lead Time^2}

If that wasn't clear to you, I suggest reading on.  This article will explain in detail what safety is used for, and how to use it.

Inventory management is about two things: not running out, and not having too much. Our desire to not run out, along with uncertainties in demand and supplier lead times are why we have inventory in the first place. Essentially, inventory is a reserve system to prevent a stock out. However, as important as it is to prevent such a stock out, we also don’t want to hold onto too much inventory because of holding costs. So how do you balance the two and what is the right amount? More importantly, when should you re-order in order to prevent a stock out? The answer to this can be determined by obtaining and applying the following information about the inventory you wish to manage.

Re-order Point (ROP)

1. What is the average lead time for the part/finished good that you need?

2. What is the standard deviation of that lead time? It is very important to track how long shipments take from you suppliers. If you are not doing this, start. It should be your top priority. Assuming you have tracked the data, excel can very easily help you determine your standard deviation. In excel, go to the toolbar and click on Insert, then click on Function, and choose STDEV and click ok. Then, enter in as much lead time data you have and presto, you have your standard deviation.

3. What is the expected demand you are working with?

4. What is the standard deviation on this demand?  Perhaps this is something you will be familiar with from experience, however, if not, this is something you should be able to squeeze out of Ted from the marketing department.  One way to find it is to look at historical demand and use the STDEV function in excel to determine it.

5. How sure do you want to be that you aren’t going to run out? 90%, 95%, 98%, 99%? Whatever you decide, this will become your service level. Using this percentage, a statistical z-table should be used to get the corresponding “z-value.” A good z-value webpage can be found at http://www.inventoryops.com/safety_stock.htm. So, for example, if you want a 98% service level, you would use 2.05 as your z-value.

Ok, so you’ve gathered this data, now here’s what you do with it.

(Underlined section is safety stock)

Re-order point=Average Lead Time*Average Demand + Z*SQRT(Avg. Lead Time*Standard Deviation of Demand^2 + Avg. Demand^2*Standard Deviation of Lead Time^2)

In this formula, the first term (Average Lead Time*Average Demand) is the average demand.

The second term {Z*SQRT(Avg. Lead Time*Standard Deviation of Demand^2 + Avg. Demand^2*Standard Deviation of Lead Time^2} is the term that allows for the safety stock. In other words, the second term is the optimal safety stock level.

It is not simple to gather all the data that is needed for the calculations. For a product with multiple parts, each part needs to have its own re-order point calculations and its own safety stock calculation. This can all become very confusing if proper computer modeling is not employed.

Although I mentioned excel earlier, excel is probably not sufficient for your company’s software needs. If you have not already done so, it is very important to look into an integrated software package for these calculations and many others.