Inventory Turnover (Inventory Turns)

Joannes Vermorel, March 2020

In accounting, the inventory turnover (also referred to as inventory turns or stock turnover), is the number of times the inventory is sold or consumed during a given time period, typically a year. Inventory turnover is typically measured either at the SKU (Stock-Keeping Unit) level, or averaged out at a more aggregate level. Numerically, the inventory turnover is frequently defined as the ratio between the cost of goods sold divided by the average stock level, also measured in cost of goods. This measurement is intended as a proxy of the overall supply chain performance, especially from a working capital perspective. Inventory turnover is a widely used metric, especially among FMCG verticals.

Investments financing in production, taxes, income revenues and costs.



Overview of inventory turnover ratios

All things considered equal, a company that manages to buy a unit of product for $1 and then resell it for $2 while performing this cycle 20 times a year will generate twice as much gross profits than a competitor performing the same cycle only 10 times a year. Yet, the two companies have roughly the same working capital requirements as far as their inventories are concerned. Thus, while inventory rotations do not equate profitability levels, they are correlated to a large extent.

Also, when analyzing the inventory turnover ratios down to the SKU level, outliers are typically of prime interest from a Supply Chain Management (SCM) perspective. Indeed, SKUs associated with low inventory turnover ratios are frequently associated with excessive inventory, or even dead inventory and inventory write-off. Furthermore, low ratios increase the pressure on working capital requirements.

Conversely, high inventory turnover ratios are generally associated with goods being sold rapidly, and a healthy state of inventory, with few depreciation and obsolescence problems. While high ratios are frequently considered as the manifestation of good inventory management, they may also hint at insufficient safety stocks or insufficient protection against supply chain risks.

In practice, lead times are usually the driving force behind the observed inventory turnover ratios. Indeed, distant suppliers (possibly oversea suppliers) entail high stock levels, as the stock needed to cover the whole lead demand is higher, which mechanically lowers the inventory turnover ratios. Other factors like batch sizes, MOQ (Minimal Order Quantity), or EOQ (economic order quantity) also affect these ratios.

Inventory turnover formula

The inventory turnover ratio is classically defined either from the purchasing perspective or from the selling perspective. The purchasing perspective is reflected by:

Inventory Turnover = Cost of Goods Sold / Average Inventory at Cost

Where

  • the Cost of Goods Sold (COGS) includes the purchasing costs of the raw materials, plus the manufacturing costs if there has been a transformation prior to selling the end product for a given time period. This cost does not include selling costs (like advertising), or general administrative costs (like human resources).
  • the Average Inventory at Cost follows the same costing definition as the one used for the COGS but is applied to all the stock currently held by the company, either available on hand, or on order. This cost does not include inventory carrying costs.

The selling perspective is reflected by:

Inventory Turnover = Net Sales / Average Inventory at Selling Price

Where

  • the Net Sales represent the revenue generated by the units sold for a given time period, not including taxes (like VAT) and temporary rebates or discounts.
  • the Average Inventory at Selling Price follows the same valuation metric as the one used for the net sales, but is applied to all the stock currently held by the company, as above.

Both perspectives require the whole inventory to be taken into account in the calculation. This includes the stock on hand but also the stock on order. Indeed, as soon as the goods are ordered, the company carries the risk associated with those quantities, and thus those quantities negatively impact the company’s supply chain agility.

Many further “turnover” variants exist. The numerator always represents the flow of inventory, while the denominator always represents the state of inventory. Most of these variants are acceptable as long as the ratio is homogeneous, with aligned units for both values. In a more abstract way, it can be said that the inventory turnover tries to capture the ratio flow over state.

As a rule of thumb, the purchasing flavor of inventory turnover tends to be more prevalent among most verticals. When considering the stock levels associated with parts, components or raw materials, the notion of inventory selling price is somewhat fuzzy as only the prices of the finished goods are ever observed directly.

Panelists and compilers of industry data frequently use net sales as the numerator in the inventory turnover equation. The prime motivation for this practice is the reluctance of companies to share their fine-grained gross margins. Indeed, sales in volume are considered as less sensitive because selling prices are already public anyway.

Anecdotally, there are many popular post-hoc rationalizations for this state of affairs based on the “supposed” superiority of the selling perspective, which is primarily promoted by the very actors that are lacking the data to adopt the purchasing perspective. While the selling perspective is not without merit, it has nearly identical pros and cons compared to its purchasing counterpart.

Limitations of inventory turnover ratios

Despite the popular belief that inventory turnover ratios (or simply turns in the following) is a good proxy of a company’s supply chain performance, those indicators are proxies at best. They suffer from many limitations that are frequently under-estimated.

Hidden complexities. Measuring turns is a complex undertaking as most naive measurements are simplistic and yield nonsensical results. For example, the notion of COGS is a fairly ambiguous notion when suppliers offer price breaks, or when purchasing commodities are subject to ever changing market prices. Conversely, profits may be negatively impacted by returns, recalls, or promotions which, on the contrary, tend to optically improve (lower) turns. In practice, turns need to be hand-crafted with a lot of domain knowledge in order to mitigate issues that would defeat the original purpose of having turns as a fair reflection of supply chain rate-of-returns. Most enterprise software fails to deliver the proper level of detail when it comes to turns’ KPIs, forcing teams to fall back on spreadsheets to get “proper” measurements.

Stale indicator. By design, turns need to be averaged over long periods of time representing a multiple of the lead times in order to be statistically significant. Furthermore, the period of measurement frequently needs to be as long as one year to provide meaningful results due to demand patterns like seasonality. As a result, turns only outline fairly “old” problems - which should have been addressed already - or slow changes in the company’s supply chain that should have been discovered earlier through alternative indicators. The mitigation of the turns’ staleness requires, in practice, predictive technologies that can reliably extrapolate recent observations and correct their local (time-wise) biases such as seasonality, promotions, stock-outs, etc.

Bikeshedding. Like most supply chain indicators - and much like ABC analysis in particular - turns are highly susceptible to lengthy improductive discussions, with multiple parties involved within the company - accounting, finance, supply chain, manufacturing ... Furthermore, as the indicator is both simple in theory and complex in practice, KPIs based on turns tend to be deceptive in many ways, leading to further frictions between teams, and to a potentially incorrect framing of incentives. This limitation can be mitigated by a thorough documentation of the indicators’ fine print, which unfortunately goes against the initial perceived simplicity associated with inventory turnover ratios.

Lack of relevance. There are situations where inventory turns are simply irrelevant. In verticals driven by novelty - fashion, luxury, cultural products - products tend to be hit-or-miss, and the products’ demand life-cycle might be too short for turns to truly matter. In verticals driven by serial (repairable) inventory - aerospace, industrial equipment - the TAT (Turn-Around Time) is typically more meaningful than inventory turnover ratios.

Methods to improve inventory turnover ratios

There are several popular approaches to lower inventory turnover ratios, however each approach tends to also have its own drawbacks.

MethodProsCons
Reduce selling pricesLower prices increase demand, and trigger further economies of scaleLower margins and depreciation of the brand value
Reduce assortment depth, eliminate slow moversReduced supply chain complexity, reduced stocksPotential disservice to clients, loss of customer loyalty
Reduce lead times, more local suppliersNo upfront investment, better overall agilityIncreased transportation costs, more expensive suppliers
Reduce batch sizes, MOQ and EOQBetter overall supply chain agility beyond better turnsIncreased purchasing and/or manufacturing costs
Reduce safety stocksReduced working capital, reduced carrying costsPotential disservice to clients, stock-outs can be disruptive
Improve predictive assessment of inventory risksReduces not only the worst turns but also inventory write-offs and obsolescence costsDifficult to execute. Most software vendors won’t outperform the status quo
Incentivize backorders or delayed deliveriesBackorders involve little inventory risks and working capitalClients might go to competitors if delivery time is of the essence

Inventory Turnover mini-antipattern: Some manufacturing companies - typically FMCGs - implement inventory turnover ratios as a corporate performance KPI. Teams are incentivized, sometimes through bonuses, to lower the turns. Unfortunately those indicators are prone to be gamed in ways that adversely impact the company. For example, raw materials may be kept as raw instead of being transformed, just for the sake of lowering the inventory value, as intermediate goods have higher valuations than raw materials. Alternatively, large discounts may be offered to large clients just before the end of the quarter to lower the immediate stock levels and thus improve turns. As a rule of thumb, it is not advisable to incentivize teams to lower turns as those indicators are easy to game.

In conclusion, the “lower turns” perspective is narrow, and does not capture what is usually perceived as a high-performance supply chain. Thus, while turns should typically be lowered when a low cost opportunity presents itself, second-order effects, such as loss of client loyalty or maintaining non-competitive suppliers, must be assessed in order to decide whether the end result will be a net gain for the company.

Lokad’s take

Like most (seemingly) simple supply chain indicators, inventory turnover ratios are _one eyed_ and do not properly reflect the conflicting economic forces present within the company and its supply chain. Turns, much like safety stocks, are a balance between various risks, primarily the cost of inventory and the cost of stock-outs. Then, while turns may provide valuable high level insights about the supply chain, refining those measurements so that they are done the “right” way requires a lot of effort, which tends to be vastly underestimated by many companies, as most enterprise software vendors do feature out-of-the-box turn-like KPIs. Yet, those built-in capabilities are invariably simplistic with regards to the company’s specificities. Thus, in practice, those KPIs require bespoke implementations, which frequently exceed the capabilities of the BI (business intelligence) tools that are not geared toward complex financial engineering.