How to reduce working capital
Many companies are often faced with the challenge of reducing their working capital, more precisely inventory capital, while at the same time ensuring that ordering-related costs are also being minimised. An adapted approach to the coverage method could help reduce your inventory capital significantly without increasing the related ordering cost.
In this article, we will introduce possible dilemmas when optimising ordering sizes, how to use and adapt the coverage method when facing different ordering barriers, other criteria to consider upon ordering and, lastly, a short case on how this approach has been used in practice.
This article takes the perspective of purchasing and expensive quality controls being the barrier to ordering more frequently, but the content could just as well be relevant to internal production ordering sizes, as well as other ordering barriers such as limited number of orders possible due to administrative burden, or a maximum amount of goods receipts possible for the warehouse.
A simple method that creates an exchange curve for the common order denominator in your product portfolio (could be number of orders, quality FTE etc.) and finds your optimal inventory value position within this curve.
Purchasers are often faced with the dilemma of reducing inventory capital while also respecting constraints from quality and other departments.
The economic order quantity (EOQ) by Wilson1 has always been considered one of the most classical ways to minimise the total inventory holding and ordering cost – but using it in practice can be very difficult, as its parameters can be hard to estimate and quickly become too theoretical. Moreover, it struggles to include other parameters that could be relevant when determining the correct order size.
This could be areas such as:
Inventory can be tied up by many elements: safety stock, cycle stock, pipeline stock, decoupling stock, excess stock, anticipation stock and congestion stock. Please see our article on eight inventory management principles for more details2. Cycle stock is determined by your lot size and, in theory, it is calculated by the average of your lot size.
In the effort to reduce cycle stock and thereby inventory capital, you must generally reduce order sizes and order more frequently in smaller quantities as seen in the picture below.
However, more frequent ordering will increase ordering costs, and this is what EOQ by Wilson is trying to balance.
Certain industries face very high ordering costs due to heavy regulations in terms of quality assurance, as they need to conduct thorough quality inspections of each order receipt. In such an environment, this is typically the biggest trade-off when purchasing raw materials. The larger the ordered quantity, the fewer the orders, and thereby fewer number of quality inspections3. By reducing the order size in this scenario, the number of quality inspections will go up.
Typically, some products are quick and easy to perform quality inspections on, while others are not. Also, their inventory value differs. The balance between these two variables is what our adaptation of the classical coverage method4 aims to strike.
By fixing the amount of quality inspection time available – perhaps by historic use or future FTE availability – we distribute this inspection time most optimally to minimise inventory capital.
As with any other theoretical method, this adaptation of the coverage method might also determine “optimal” order sizes that might not be “optimal” in practice – they simply do not take all relevant factors into account. We therefore suggest combining the method with several other criteria to reach realistic and efficient order sizes.
These criteria can be very specific from company to company, but examples of these could be as depicted in the model below. When combining the order quantity found with the coverage method and all other relevant criteria, a simple decision tree could be used – this enables the purchasers to have simple and easy rules and guidelines on how much to order.
As with many other methods, it is very important to keep in mind that this approach should be used to give you a strong recommendation for the correct order quantity. But in the end, you have to evaluate it – it could be that you need to round off the quantity to an appropriate measure or have to take volume discounts into consideration.
We typically see that companies are facing challenges with limited warehouse capacity and a strong focus on freeing up capital tied in their products. In situations like these where they are not looking to increase their quality inspection resources (or equivalent barriers), we have helped implement this approach, and we typically see a high impact as their cycle stock and inventory capital on average are reduced by 20-50%.
We realise that this approach to finding the correct order size may seem a bit simplistic, but this is one of its biggest strengths, as its simplicity makes it easy to put into use.
Please feel free to contact us, if this article inspired you to take a closer look at your journey towards reducing inventory through better purchasing or balancing all the different criteria influencing your inventory levels.
1 Erlenkotter, D. Ford Whitman Harris and the Economic Order Quantity Model. Operations Research 38.6 (1990): 937-946.
3 Assuming one inspection per order, regardless of the quantity.
4 Murdoch, J. Coverage Analysis – New technique for optimising the stock ordering policy, proceeding from one day conference held at Cranfield. 1965.
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