‘Days sales in inventory’, alternatively referred to as “days in inventory (DII)”, “days in inventory outstanding (DIO)”, or “inventory days of supply”, serves as a measure indicating the number of days a business maintains its inventory based on sales value. A common misunderstanding is associating ‘days sales in inventory’ solely with the time required to deplete inventory. While a ‘days sales in inventory’ of 40 days might suggest that inventory will be sold out within that timeframe if only one product type is sold, in reality, ‘days sales in inventory’ calculates the average inventory turnover in terms of dollars, especially in cases where multiple products are involved. Within the 40-day period, certain products may cycle through inventory multiple times, while others may have longer sales cycles.
‘Days sales in inventory’ originates from a fundamental query common for business proprietors and managers: How long will my inventory last? The conventional method of calculating ‘days sales in inventory’, based on financial records, quantifies this duration in monetary terms, averaged over time. Essentially, ‘days sales in inventory’ indicates the average duration required for cumulative sales to match the mean (or current) inventory level. This averaged metric, typically computed over a recent quarter or year, serves as a tool for both companies and investors to assess, in relative terms, the efficiency and effectiveness of sales and inventory management practices.
An increase in ‘days sales in inventory’ typically signifies either an excess inventory accumulation or a slowdown in sales. Conversely, a lower ‘days sales in inventory’ is generally preferred, although the optimal threshold varies across industries and companies. It is imperative to maintain ‘days sales in inventory’ above zero to avoid the risk of inventory levels dropping dangerously low, which could impede order fulfillment capabilities.
‘Days sales in inventory’ serves as a valuable tool for planning, provided that the averages don’t overlook significant cyclical fluctuations. For instance, in businesses with seasonal patterns, relying solely on an annual average might not offer meaningful insights. Additionally, it’s crucial that no significant alterations occur in your cost structure or sales environment from the start to end of the data period being analyzed for planning purposes. This means that if anticipated changes, such as implementing a new supply chain or launching a new product, are expected to impact future DSI, historical DSI data may become less relevant for planners.
Why Businesses Should Care About Days Sales in Inventory
‘Days sales in inventory’ serves as an indicator of operational effectiveness
While a solitary figure for a specific period may lack significance on its own, continuous monitoring of ‘days sales in inventory’ over time can reveal fluctuations and patterns that offer insights into inventory management practices. For instance, a gradual decrease in ‘days sales in inventory’ might suggest successful implementation of a new sales approach, whereas a sudden increase could signal potential issues. (It’s important to note that ‘days sales in inventory’ alone shouldn’t be relied upon to diagnose problematic situations.) Additionally, ‘days sales in inventory’ facilitates comparisons between similar companies within the same industry over identical time frames.
‘Days sales in inventory’ plays a crucial role in managing cash effectively
Having excessive cash tied up in inventory can lead to various challenges, such as difficulties in meeting supplier payment deadlines or seizing new investment opportunities due to constrained finances. Additionally, for many businesses, the costs associated with storing inventory can be significant. Monitoring ‘days sales in inventory’ helps preempt such issues from arising.
‘Days sales in inventory’ serves as a pivotal aspect of inventory management.
While a retrospective analysis of past performance using traditional formulas can offer insights into previous quarters or years, applying the same methodology to sales forecasts and current inventory status, especially when meticulously tracked through Enterprise Resource Planning (ERP) and Warehouse Management Systems (WMS), provides valuable foresight into the business’s trajectory.
‘Days sales in inventory’ computations hold particular significance for companies primarily or exclusively dealing in tangible goods, especially those involving perishable inventory. A high ‘days sales in inventory’ for perishable products could lead to substantial financial losses, contrasting with standard inventory where an increase in ‘days sales in inventory’ indicates slightly elevated carrying costs and marginally reduced liquidity.
Calculate Days Sales in Inventory
There are various methods to compute it, but the most common ‘days sales in inventory’ formula is:
Days sales in inventory = [(average inventory) / (COGS)] x (days in the given time period)
Average inventory refers to the mean monetary value (not inventory units) of inventory held during a specified duration, while COGS represents the cost of goods sold for that corresponding period. For an annual assessment, one would divide the average inventory for the year by the COGS of that year, and then multiply the outcome by the number of days in that year. In cases where a company manufactures its own goods, the inventory calculation should include works in progress as well.
It’s important to note that the outcomes derived from this approach heavily depend on how average inventory is calculated. The conventional method involves summing the beginning inventory and ending inventory for the specified time period and dividing the total by two. However, consider two companies operating on a January 1 to December 31 fiscal year. Suppose both companies commence the year with $1,000,000 of inventory and conclude with $1,200,000 of inventory. Both companies would report an “average inventory” level of $1.1 million. However, if one company’s inventory surges from $1 million to $3 million before declining to $1.1 million by year-end, while the other company’s inventory drops to $500,000 before rebounding to the same endpoint, these “average” calculations might obscure significant annual trends and fail to represent an average day for either company accurately.
The formula can be adjusted slightly to provide a more future-oriented perspective, indicating the number of forthcoming days of inventory available at the present moment. To achieve this, substitute average inventory with the current inventory level (or the most recent available), while retaining the remaining components of the formula unchanged. This version operates on the assumption that the cost structure and sales rate of the current inventory will not significantly deviate from those observed during the time period specified for “days” and “COGS.”
Days Sales in Inventory vs Inventory Turnover
Inventory turnover complements ‘days sales in inventory’ by providing additional insight into inventory management. While ‘days sales in inventory’ indicates the average duration for a business to sell its inventory, inventory turnover reveals how many times, on average, the business replenished its inventory within a specified timeframe.
Both ‘days sales in inventory’ and inventory turnover share conceptual and mathematical similarities. For instance, if a business’s ‘days sales in inventory’ for the previous fiscal year amounted to seven days (one week), its inventory turnover would be 52, reflecting the number of weeks in a year. Similarly, if ‘days sales in inventory’ corresponds to a month, the inventory turnover would be 12.
It’s important to recognize that like ‘days sales in inventory’, inventory turnover is an average measure, which implies that it may conceal the actual time required for selling each individual item in inventory. Put differently, certain products may have faster turnover rates than others.
Benefits of Calculating Days Sales in Inventory
A primary advantage of computing ‘days sales in inventory’ lies in its utility for benchmarking. By evaluating its performance against publicly traded rivals and its own historical data, a business can gauge its standing. A consistent decline in ‘days sales in inventory’ may indicate enhancements in inventory management or sales prediction methods, whereas a reversal in this trend could serve as a warning signal, prompting leaders to investigate potential issues with personnel or suppliers that might have otherwise gone unnoticed. Furthermore, DSI’s trajectory over time, combined with other pertinent metrics, can offer valuable insights to guide strategic decision-making processes.
When engaging in benchmarking, it’s essential for a business to ensure comparability by comparing similar entities. For instance, if a business specializes in selling phones, it would be inappropriate to benchmark against a company like Apple, which offers a broader range of products including computers and digital music. Similarly, quarter-over-quarter comparisons may lead to misleading conclusions for seasonal businesses.
Additionally, some investors value insights provided by ‘days sales in inventory’. Therefore, if a company’s financial statements are not publicly available or regularly reviewed, including the ‘days sales in inventory’ calculation in reports and presentations could help investors make informed choices.
Examples of Days Sales in Inventory
Let’s explore several methods for calculating ‘days sales in inventory’ using a prominent publicly traded company that primarily deals in physical products: Walmart. Their basic financial statement data is readily available.
Example 1: From the conclusion of fiscal year 2020 to fiscal year 2021, Walmart experienced an increase in inventory from $8.99 billion to $10.65 billion. During fiscal year 2021, its total cost of goods sold (COGS) amounted to $65.7 billion. To determine Walmart’s ‘days sales in inventory’ for fiscal year 2021, we employ the following formula:
Days sales in inventory = [(average inventory)/(COGS)] x (days in the specified time period)
In this instance, the average inventory is calculated as ($8.99B + $10.65B) / 2 = $9.82B, and COGS equals $65.7B.
Therefore, days sales in inventory = ($9.82B / $65.7B) x 365 = 54.6 days
Example 2: Let’s consider a scenario where our interest lies more in obtaining the most current data available rather than assessing Walmart’s performance over the entire year. In this case, we will base our calculation on the most recent quarter instead of the entire fiscal year, and we’ll utilize the ending inventory figure instead of computing an average. As per the provided data, the cost of goods sold (COGS) amounted to $18.13 billion, while inventory stood at $14.96 billion. Utilizing our ‘days sales in inventory’ formula:
Days sales in inventory = ($14.96B/$18.13B) x 90 = 74.3 days
We observe a notably higher outcome for this latest quarter—an increase of over a third. So, what insights do these figures offer?
Analyzing the findings: Historically, the outcomes of both computations exhibit an upward trend compared to previous periods, with the quarterly ‘days sales in inventory’ surpassing that of the same quarter from the preceding year. It appears that the most recent quarter significantly influences the overall increase in ‘days sales in inventory’ for the entire year.
Given the positive sales growth observed in recent quarters and across recent years, one might question whether Walmart’s efficiency in inventory management and sales forecasting has diminished. Plausible narratives could revolve around labor shortages and challenges within the supply chain. However, an alternative interpretation could suggest that the escalation in inventory levels represents a strategic response to supply chain complexities, particularly in anticipation of the high shopping demand during the winter holiday season when stock outs could prove exceptionally costly. Augmenting inventories may be a deliberate strategy to mitigate potential shortages and adopt a cautious approach.
An alternative explanation is that Walmart anticipated faster sales growth compared to previous years. It’s important to note that the pace of sales is determined by historical COGS data; therefore, if sales were to surge significantly, the entire 74 days might not be required to turn over inventory within a single quarter.
So, should there be any cause for concern? Evidently, Walmart investors appear unfazed by this abrupt rise in a metric that some sources suggest could indicate declining efficiency. In fact, as of the present moment, Walmart’s stock has outperformed the market over the past six-, and 12-month periods. With the confidence exhibited by Walmart’s investors, coupled with the company’s expanding business and the understanding that increasing inventory levels could be a prudent response to supply chain challenges and unpredictable spikes in demand, it’s reasonable to infer that this increase likely reflects a strategic shift rather than sudden inefficiency.
This example shows us the limitation of relying solely on ‘days sales in inventory’ to assess the vitality of a business, even when the numbers appear striking.
How does Warehouse Management Software Help?
Utilizing warehouse management software has become almost indispensable when leveraging ‘days sales in inventory’ for decision-making purposes. The traditional method of computing ‘days sales in inventory’ from financial statements, which can be time-consuming to compile and may not always reflect the most recent data, often falls short in providing comprehensive information, particularly in corporate forecasts, conducting “what-if” scenarios, or examining incomplete quarters or fiscal years. Advanced warehouse management software enhances the precision of financial statements and expedites the process. However, the true value of quality software lies in its capacity to calculate metrics in real-time, enabling prompt responses to specific queries.
Optimize Warehouse Management with PALMS™ Smart WMS
PALMS™ Smart WMS aids businesses in inventory monitoring and tracking. Among its advantages, the software enables swift data compilation and metric calculation, which can be tailored and exported for external analysis. Additionally, it provides features for inventory optimization, directly impacting ‘days sales in inventory’.
Furthermore, employing warehouse management software like PALMS™ Smart WMS, either as a standalone solution or as part of a comprehensive ERP system that integrates data from various business segments, offers the capability to gather detailed data for calculating individual product-based metrics akin to ‘days sales in inventory’, instead of providing a singular figure for the entire company. This approach circumvents the issue of blending diverse data into averages as discussed above. Such granular data holds significant value for numerous business stakeholders, ranging from product managers to the CEO.
