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Economic Order Quantity (EOQ) and Salescast

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Economic Order Quantity (EOQ) and Salescast

Salescast delivers many key inventory optimization metrics but it does not provide Economic Order Quantity (EOQ) by default. This aspect of Salescast is frequently considered as puzzling: indeed, if Salescast is capable of reporting the inventory level that should trigger a replenishment order, why can't Salescast indicate the quantity to be reordered as well? This page addresses this question.

Note: if EOQ values are already managed by your company software (ERP), then importing them within Salescast for reporting purpose is a very simple operation. We are assuming here that EOQs are not readily available.


Understanding the need for EOQ

If we assume a theoretical scenario where performing an inventory replenishment operation comes with zero overhead and is instant, then the optimal inventory replenishment strategy is to pass a backorder to the supplier whenever a client order comes in.

In practice, replenishment orders typically involve a certain amount of friction such as minimal ordering quantity and shipping costs, and require a certain lead time. Hence, generating as many backorders as there are client orders is usually not a tractable solution unless your business happens to be an eCommerce heavily relying on cross-docking.

The case of the Wilson formula

In the supply chain literature, when authors refer to the Economic Order Quantity, they typically refer to the Wilson formula developed by F. W. Harris in 1913. This model provides a simple formula that is easy to compute (see the Wikipedia page for further detail).

The Wilson formula requires only 3 variables:
  1. Rate of demand (aka forecasted demand)
  2. Annual holding cost per unit (known as carrying cost or storage cost)
  3. Flat order cost.

Nevertheless this model only works if the following assumptions are enforced:
  • The ordering cost is constant.
  • The rate of demand is constant.
  • The lead time is fixed
  • The purchase price of the item is constant i.e. no discount is available
  • The replenishment is made instantaneously, the whole batch is delivered at once.

In the Lokad experience, we are estimating that those assumptions do not hold for roughly 99% of the businesses. Yet, we are not dismissing extremely early works of both F. W. Harris and R. H. Wilson. One century ago, the simple fact of applying mathematics to supply chain was visionary. Lokad is only a modest descent from this vision, nevertheless a lot of time has passed since 1913.

The true complexity of EOQ

On first examination, the Wilson formula seems to indicate that a very simple solution exist to address the EOQ problem. Yet, we believe this is not the case. The formula does not take into account many factors that are often of equal or higher importance and does not account for constraints that might be given:
  • Minimum order quantity
  • Package sizes constraints
  • Receiving costs
  • Quantity discounts
  • Expiration dates
  • Obsolescence risks
  • Cash flow constraints
  • Varying shipping costs
  • Temporary discounts
  • Warehousing max capacity
  • Maximal quantity available on hand at the supplier location
  • ...

This is a rather long list already, and yet we are only barely scratching the complexity of real world situations.

EOQ is highly business specific

The main challenge for the determination of the EOQ is therefore that it is highly business specific, an often even product specific. In a two step process, first the appropriate algorithm needs to be determined, and the accurate inputs need to be identified. For example, in the case of cost allocations a very careful look needs to be taken on allocating the right cost and correct share of the cost. And this might change over time - for example, if the warehouse is owned and half empty, floor space is not included into the calculation. If at some point the warehouse is full and additional space needs to be rented, this cost is certainly to be accounted for.

What is 'optimal' depends on your goals. Example: cash vs. cost optimization

Optimizing inventory cost is not necessarily the same as optimizing cash. The latter might mean that you try to minimize capital that is tied up in your inventory by increasing the order frequency and thus reducing the order quantity at the benefit of lower 'spikes' in your inventory and lower average inventory levels. The result is a higher 'inventory turnover' or more 'inventory turns'. Businesses that are managed for cash flow might choose to sacrifice cost optimization at the benefit of cash. This strategic policy will directly impact your order quantities. Again, your goals might change over time.

Keep it simple

The good news is that depending on your business, all EOQ factors are not all equally important. Hence before embarking on finely tuning optimal order quantities or even seeking automation, your company needs to address simple questions:
  • What are the key factors that truly impact my business?
  • How much time can you invest for optimization
  • What is the ROI of optimizing my order quantities?
  • How frequently is this optimization going to change?

In our experience, optimal order quantities are typically less dynamic than reorder points and most businesses do just fine in reviewing and updating order quantities once or twice a year in a manual process.

I really need EOQ, can't Salescast do it?

As we pointed out above, the main challenge in calculating the EOQ is determining the right formula and inputs for your business and goals, and keeping them up to date. If you do have a clear idea of the EOQ formula to be used and the data required for the EOQ calculation readily available within your company software (an ERP typically), then Lokad will gladly implement and automation the delivery of EOQs along with reorder points. This work will be charged as a small customization package on top of the regular Salescast pricing. Just contact us and we can investigate the detail together.

On the contrary, if EOQ is still something very fuzzy and/or if the relevant data is known as NOT being available within your existing company software, then we strongly suggest to investigate this matter separately. Again, the Lokad team is here to provide guidance. Don't hesitate to .

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What people say

Classical solutions require too much manpower and don't scale correctly over hundreds of thousands of products. Lokad and Windows Azure were exactly the solution my business needed. Pierre-Noël Luiggi, CEO of Oscaro
The Lokad forecasting solution allows us to precisely forecast our sales and to optimize our inventory accordingly. The result is there: we are maintaining a 99% customer satisfaction level and deliver food that is often fresher than what can be found at local pet stores. Anthony Holloway, CEO at k9cuisine
Lokad improved the accuracy of our planning process significantly. The immediate impact was a stock reduction of almost 1 million € at a monthly cost of 150€. It was almost frightening to see our inventory levels getting so low! But what impressed me most is the ease of implementation and use. The integration was painless, and now it takes only a the click of a button and within 10 minutes I receive my forecast. The time saving for me is significant. Thomas Brémont, Head of Supply Chain Bizline

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