Most of us agree that the high-level goal of inventory optimization is to reduce inventory levels while optimizing for desired service levels or fill rates, ideally across discrete levels and locations in the supply network. At a theoretical level these two variables should be correlated, meaning that as service levels increase the required inventory levels to support those service levels increase as well. In practice we find that most companies struggle to effectively tie inventory to service levels in a dynamic manor which results in excess inventory at some part/location combinations and not enough at others to support desired service levels. This allows good inventory optimization software solutions to initially deliver a quick win by both increase service levels while reducing overall inventory levels.
Once we have mathematically and dynamically tied service levels to inventory levels using a software solution, we can have the required conversation around what is the appropriate service level your company should maintain and at which levels/nodes/locations should these service levels be set. An important thing to note is that the relationship between service levels and inventory levels is a mathematical, non-linear, relationship. Below we graph the predicted on-hand inventory against the desired service level. It is worth noting that certain parts may have more or less variation in consumption that would impact the slope of the below graph but the principles that we will discuss below remain the same.
Often a takeaway of this is a rather frank and honest assessment around the cost of maintaining certain service levels. Companies often brag about 99.99% service levels without understanding the mathematical connection to inventory stocking levels (see graph above). The cost of moving from 90% service level to 95% is $356,330 while the cost from moving from 95% to 99.99% is $2,034,360 – nearly six times as much in just the pure inventory costs (not taking into account the increased carrying costs associated with that inventory). Typically one of two things is at play: either the company is carrying way too much inventory and when an objective cost to benefit analysis is performed there is no justification to carry that level of inventory or (the more likely scenario) the customer isn’t actually carrying enough inventory to support the 99.99% fill rate and either isn’t tracking stockouts effectively or hasn’t had the 0.01% stockout happen yet (mathematically speaking should happen once every 1,000 days).
Practically speaking, do you really need to stock inventory to a level where you cannot fill an order once every three years? It is important to note that this stockout can likely be avoided through other means that planners and supply chain executives have at their disposal. Can you expedite the order through your supplier’s factory? Can the product ship directly from your supplier or another node? Can the product be shipped via air rather than land, rail or sea? Can you talk to your customer and see if some or all of their order can be delivered a few days later? Using the tried and true examples above, it is significantly more cost effective, for the company as a whole, to expedite a couple orders a year in order to save millions of dollars of inventory and inventory carrying cost.
Setting service levels is a strategic decision that should involve multiple parts of the business and should be reviewed at some standard cadence (quarterly, yearly, event driven). Sales should be involved because they need to understand what customer service levels can be committed to as relates to new sales. Finance should be involved so that they can understand the impact that adjusting inventory levels can have on the rest of the organization (improvement in working capital can hurt future ability to fill sales orders). Production and operations need to be involved because the agreed upon service levels directly impact the required production and operational investments. In a perfect world all parties agree upon the service levels that have been set and are aligned on executing toward those service levels.
As we have mentioned in previous blog posts understanding and being able to make informed decisions around inventory and service levels based on dynamic real-time data is really just the beginning. Software can automate the tedious task of setting inventory levels and can make sure that your desired service levels throughout your supplier network are driving the corresponding inventory levels. It is important to remember that for you to maintain your desired service levels, the necessary reorder points (which are driving inventory levels) need to adjust dynamically based on changes in demand (forecast or historical); this type of optimization cannot be done manually or in excel. We have found that a purpose-built software solution that is integrated with a company’s ERP/MRP delivers the best results.
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