Evaluation of Days in Inventory to determine importance. 

We can see that inventory varies by country, and that overall against all industries, China takes the lead when it comes to holding inventory, but what about specific industries?  How do industries differ from country to country?  While the U.S. and China are countries with a vast amount of inventory, countries like Japan and Germany show them in the top 10 for inventory around the world.  How important is Inventory to these countries, and what problems do they face?

Looking at the median ranges in terms of Inventory as a function of total assets, we see that Materials takes the top spot in Germany at 19%, with Consumer Discretionary a close second at 16%. Telecommunications is the lowest at 3%.  One thing to note, Real Estate seems to have spiked between 2020 and 2023.

Japan takes a slightly different track than Germany, with Real Estate taking the lead in terms of the median of Inventory as a function of total assets at 44%(This tracks similarly with China).  No other industry comes close to the amount of inventory/total assets as Real Estate from this chart. Telecommunications is the lowest at 2%. 

If we drill down a little deeper within the industries, we see a very interesting picture.  The Inventory-to-Total Assets benchmark reveals several similarities and differences between Germany and Japan. Overall, industry structure drives inventory intensity in both countries, with capital-intensive sectors such as Semiconductors and Technology Hardware showing relatively high inventory ratios, while asset-light industries like Software & Services maintain very low levels. Consumer-oriented industries such as Food, Beverage & Tobacco and Household & Personal Products fall in the mid-range in both markets.

However, some differences emerge. Germany generally exhibits higher inventory ratios in manufacturing-heavy industries, particularly in Technology Hardware and Semiconductors, suggesting greater working capital tied to production and supply chain buffers. In contrast, Japan shows notably higher inventory intensity in Real Estate, where median and upper-percentile values exceed those of Germany, reflecting larger development or land holdings. Despite these variations, the overall pattern is consistent across both countries: inventory levels are primarily shaped by industry characteristics rather than geography.

Looking at the picture of Days in Inventory, we see that for Real Estate, and exponential increase from the low end to the high end.  Why does the 90th percentile have a days in inventory of 1,664 days?  This is around 4.5years!  This again could point to a high amount of high-value real estate for high-end companies. We also see this jump show up in utilities, where it is even a bigger jump.  At the median, it is 33 days, but at the 90th percentile, it is 2,367 days or 6.5 years! Other areas of concern include Healthcare and IT. 

For Japan, we see that Real Estate and Healthcare have the highest days' inventory. With Real Estate, while it starts very low at the 10th percentile, with only 3 inventory days, it shoots up very rapidly, and at the median is already at 264 days.  This can also be seen with healthcare, where it starts out at 7.97 inventory days, about 1/2 of the U.S but shoots up to 118 at the median.  The IT numbers are interesting as at the 10th percentile, it is only 1/2 day in inventory.  However, that may have something to do with what IT we are talking about or that the companies at the 10th percentile may be very small. 

If we drill down a little deeper, we see the Inventory Days benchmark shows that while both Germany and Japan follow similar industry patterns, notable differences emerge in the magnitude of inventory holding periods.  In both countries, capital-intensive sectors such as Real Estate, Semiconductors, Technology Hardware, and Pharmaceuticals exhibit the longest inventory cycles, while asset-light industries like Software & Services maintain very short inventory days. Consumer-facing sectors such as Food & Staples Retailing and Household Products fall in the middle range across both markets.
However, Germany generally displays higher median inventory days in several manufacturing-driven industries, particularly Technology Hardware, Semiconductors, and Pharmaceuticals, indicating longer production cycles or greater inventory buffering. For example, Germany’s medians in Technology Hardware and Semiconductors are substantially higher than Japan’s. In contrast, Japan shows higher median inventory days in Real Estate and maintains more moderate levels in certain consumer sectors compared to Germany’s more extreme dispersion.

Overall, while the structural pattern by industry is consistent between the two countries, Germany tends to exhibit greater variability and, in several industrial sectors, longer inventory holding periods than Japan.

The chart shows median inventory days for German industries from 2017 to 2024, highlighting clear sector differences and a pandemic-era spike in inventory holdings.

Real Estate in Germany is the most extreme case, rising from roughly 160 days in 2018 to over 600 days in 2022, before falling back to about 215 days in 2024. This sharp increase reflects prolonged development cycles and pandemic-related slowdowns, with inventory levels still structurally elevated compared to pre-2020 levels.

Most other German sectors fall within a more moderate 60–120 day range. Industrials and Materials peaked around 100–110 days in 2022, consistent with supply chain bottlenecks, but have since stabilized. Information Technology and Health Care also saw temporary increases during 2020–2021, IT rose from about 45 to 75 days, and Health Care approached 150 days, before moderating as supply pressures eased.

In contrast, Energy and Utilities remain relatively low throughout the period, indicating limited inventory strain. Overall, inventory stress in Germany appears to have peaked in 2022, with most sectors now normalizing, though Real Estate and some capital-intensive industries continue to carry higher-than-pre-pandemic inventory levels.

The chart shows median inventory days for Japanese industries from 2017 to 2024, highlighting steady structural differences with more moderate volatility than seen in Germany.

Real Estate in Japan remains the highest sector but is far less extreme than Germany, fluctuating between roughly 210–265 days over the period. After dipping slightly in 2020, it trends upward, reaching about 265 days in 2024, suggesting longer development cycles but without the sharp pandemic spike observed in Germany.

Most other sectors fall within a 40–120 day range. Health Care steadily increases from about 103 days in 2017 to nearly 120 days in 2024, indicating gradual inventory buildup. Materials also trend upward from roughly 75 days to over 90 days, while Consumer Discretionary and Consumer Staples remain relatively stable in the 40–50 day range.

Energy, Utilities, and Telecommunications remain consistently low (generally below 30 days), reflecting faster turnover and less inventory-intensive operations.

Overall, Japan’s inventory trends show gradual increases rather than sharp spikes, suggesting more measured adjustments during and after the pandemic. While some sectors, particularly Real Estate, Health Care, and Materials, show elevated inventory levels in recent years, the data does not indicate the same level of extreme supply chain disruption seen in Germany.

The relationship between inventory turnover and revenue growth in the semiconductor industry appears moderately positive during expansion years but weak overall. In 2021 and 2022, higher inventory turnover is associated with stronger revenue growth (R² roughly 0.10–0.14), suggesting that companies moving inventory more quickly benefited from strong demand and tight supply conditions during the chip shortage cycle. However, this relationship weakens significantly in 2023 (R² near zero), reflecting the industry downturn and inventory correction phase. By 2024, a slight positive relationship re-emerges, indicating early signs of demand recovery. Overall, inventory turnover appears to align with revenue growth primarily during cyclical upswings rather than consistently across periods.

The data show little consistent relationship between inventory turnover and operating margin across semiconductor firms. The trendlines are generally flat or slightly negative, and R² values remain low (mostly below 0.07), indicating weak explanatory power. This suggests that operating margins in the semiconductor industry are driven more by factors such as pricing power, product differentiation, technological leadership, and scale efficiencies rather than inventory efficiency alone. For example, companies with moderate turnover can still generate high margins if they possess strong competitive advantages, while higher turnover does not guarantee superior profitability. Thus, operating performance appears more structurally determined than operationally driven by inventory movement.

The relationship between inventory turnover and ROA is also weak and slightly negative in most years, with very low R² values (generally under 0.03). Although inventory is a component of total assets, turnover does not meaningfully explain differences in asset returns across firms. This reflects the capital-intensive nature of the semiconductor industry, where ROA is heavily influenced by fabrication investments, R&D intensity, and business models (fabless versus integrated manufacturers). As a result, asset efficiency depends more on capital structure and strategic positioning than on inventory management alone. Inventory turnover, while operationally relevant, does not appear to be a primary driver of overall capital returns in this sector.

Inventory turnover shows a moderate positive relationship with revenue growth during expansion years (2021–2022), but this relationship weakens significantly during downturns.

There is little consistent relationship between inventory turnover and operating margin or ROA.

Profitability and asset returns are driven more by technological advantage, pricing power, capital intensity, and product mix than by inventory efficiency.

Overall, inventory turnover is somewhat informative during demand surges but is not a primary driver of profitability or capital performance in the semiconductor industry.

The relationship between inventory turnover and revenue growth in the automobile industry is inconsistent and varies by year. In 2021, there appears to be a strong negative relationship (high R²), largely driven by outliers such as Tesla during the post-pandemic rebound period. However, in 2022 and 2023 the relationship becomes weak or nearly flat (very low R²), suggesting turnover did not meaningfully explain revenue growth during normalization and supply chain adjustment phases. By 2024, there is only a modest positive relationship (R² around 0.33), indicating that companies with slightly higher turnover may be experiencing steadier growth, but the relationship is not particularly strong.

Overall, revenue growth in autos appears not to be driven by inventory efficiency but probably by other factors such as demand cycles, pricing adjustments, and supply constraints (e.g., chip shortages).

Across most years, the relationship between inventory turnover and operating margin is negative and relatively strong in certain periods. In 2021 and 2022 especially, higher inventory turnover corresponds with lower operating margins (high R² values in those years). This likely reflects the post-pandemic supply imbalance: companies with lower turnover (tight supply, limited inventory) were able to maintain stronger pricing power and margins, while higher turnover may have coincided with discounting or normalization of supply.

In 2023 and 2024, the negative slope remains but weakens somewhat, suggesting margins are mostly likely being influenced by broader cost pressures (labor, raw materials, EV investment) rather than inventory movement alone.

Overall, autos show a noticeable relationship between turnover and margins, but it is often inverse rather than positive.

The ROA relationship shows a clearer negative trend in multiple years, particularly 2022 and 2024 where R² values are moderately high (around 0.68–0.72). Higher inventory turnover is associated with lower ROA in those periods.

This reflects the capital-intensive nature of auto manufacturing. Companies with very high turnover may be operating with thinner margins or lower asset bases relative to revenue, while firms with moderate turnover but strong pricing power (e.g., during supply shortages) generate higher returns on assets.

Overall, the auto industry shows a more meaningful inverse relationship with ROA. Asset returns here are strongly influenced by capacity utilization, pricing cycles, and fixed cost leverage.

Inventory turnover does not consistently explain revenue growth across years.

There is a more noticeable and often inverse relationship between turnover and operating margin, particularly during supply imbalance periods.

Higher turnover is sometimes associated with lower ROA, reflecting the capital-intensive nature of auto manufacturing and the impact of pricing power during shortages.

Overall, inventory dynamics play a more visible role in auto performance than in semiconductors, but outcomes are largely shaped by cyclical supply-demand conditions rather than pure operational efficiency.

Ranking all US pharmaceutical companies by inventory days, we can see that Merck  & Co. Inc. ranks 14th, Johnson & Johnson ranks 18th, and Eli Lily and Company ranks 32nd.

Trend analysis shows that Eli Lily had constantly higher inventory days than Merck and Johnson & Johnson.  Eli Lily also had the highest gross margin, implying the highest pricing, which likely resulted in the lowest revenue growth. With the Net Margin, while there are peaks and valleys for all three companies, overall Eli Lily very often has the lowest margin in comparison with the other two companies.  However, it should be noted that in 2024, while Eli Lily had an increased days in inventory, it had a stable net margin of 24%, pretty close to Merck at the top spot of 27%.  However, J & J had the lowest net margin while also having the lowest gross margin, meaning they are selling their products more cheaply.  That, on top of J & J having the highest total revenue asks the question, is in fact J & J having a problem with their inventory, not Eli Lily? 

Revenue breakdown for 2024 shows while the lowest net margin for J & J with the highest SG&A and COGS, higher than the U.S. industry average.  If they have the lowest gross margin and are selling their products lower price, and their revenue is the highest of the three companies, why is the net margin so low? Answer: J &J has a much higher SG&A cost and COGS than others. Does that mean they have an inventory problem? 

When taking a look at the detailed assets, the picture becomes clearer.  In order to understand what is going on with these companies a look at Net Intangible Assets and how it relates to the Inventory will help to determine if any of these companies truly have an inventory problem.  For J & J, with net intangible assets around 45% and inventory at roughly 6.9%, J&J’s balance sheet reflects a mix of intellectual property and tangible operating infrastructure. Inventory represents a relatively small portion of total assets, indicating efficient working capital management. The company is innovation-driven but still supported by meaningful physical operations. With inventory at 9.6% of total assets and net intangible assets at only 15%, Lilly’s balance sheet is less intangible-heavy than a typical pure pharma profile. This suggests a larger portion of assets is tied to tangible items such as inventory, manufacturing assets, and working capital. Inventory represents a meaningful component of the asset base, indicating that operational scale and product demand (e.g., high-volume drugs) play a significant role alongside intellectual property in driving performance. There could be an inventory problem, however, due to the high increase in inventory in 2024, but still a pretty high net margin, it may just be that the company needs to keep certain drugs at high volume due to current high demand and not necessarily that there is inefficiency at play.  As for Merck, with inventory at the lowest of the three companies and lower than the industry average at 5.22% of total assets and net intangible assets around 32%, Merck has a meaningfully IP-driven balance sheet but still maintains tangible operating support. Intangible assets (patents and acquired drug rights) represent a much larger share of assets than inventory, indicating performance is primarily driven by proprietary products rather than working capital intensity. Inventory plays a relatively small role in the overall asset structure, suggesting efficient inventory management within an innovation-focused pharmaceutical model.

The chart shows a strong positive relationship between inventory turnover and SG&A as a percentage of revenue, with an R² of approximately 0.86, indicating high explanatory power. As inventory turnover increases, SG&A ratio also rises. This suggests that higher operational activity (moving product faster) is associated with greater selling and administrative intensity.

For Eli Lilly specifically, this likely reflects increased commercialization efforts tied to strong product demand (e.g., expanding sales force, marketing, distribution expansion). Rather than inventory efficiency reducing SG&A, the data suggests growth-driven inventory movement may require higher SG&A spending.

Overall, in this pharmaceutical context, higher turnover does not appear to lower cost structure, instead, it may signal expansion and scaling costs that raise SG&A relative to revenue.

Looking back at Eli Lilly again as they had the highest inventory days with the highest gross margin, we see that market value does not primarily move with improvements in inventory management, as its valuation is driven more by drug pipeline strength, patent protection, and revenue growth than by working capital efficiency. Even if net income improves through better inventory management, the impact on market value may be limited compared to breakthroughs in product development or clinical success. In Lilly’s case, innovation and future earnings potential have a much stronger influence on valuation than inventory optimization alone.