Supply Chain Part II — Inventory Management

Inventory turnover is a critical indicator of supply chain management performance in the retail industry; balancing inventory and demand is key to a company’s financial success. For publicly listed companies, metrics such as cash flow, capital occupation cost, and warehousing costs are essential in evaluating corporate value. I. What Is Inventory? Inventory serves as a tool for optimizing the trade-off between cost and service level—‘generating revenue’ (e.g., enabling sales) and ‘controlling costs’—to support maximum sales at minimum cost. Before introducing inventory management methodologies, it is vital to clarify several irreversible negative impacts caused by poor inventory management: In its difficult year of 2012, Li-Ning held inventory valued at RMB 3.7 billion. Based on its annual sales of RMB 8.6 billion that year, it would take approximately six months to sell through this inventory. As a result, all of the company’s working capital was tied up in inventory. To recover cash, discount sales were widely reported across Li-Ning outlets. By the first half of 2021, Li-Ning had closed 1,200 stores—a staggering 22% reduction in store count. Similarly, Vancl endured a painful 2011, with inventory reaching RMB 1.445 billion—nearly exceeding its entire annual sales. Though Vancl is a clothing company, its warehouses were piled high with unsellable rice cookers and mops. Chen Nian remarked: [Inventory] taught him an important lesson: “It’s no big deal if you intended to produce 20,000 units but only made 200. The real disaster is when you intended to make only 200 units—but produced 20,000.” From these two cases, it is clear that excessive inventory harms enterprises in the following ways: 1. High opportunity cost of cash; 2. High warehousing resource cost; 3. Depreciation due to aging, deterioration, or expiration over time; 4. Wasted labor and resources from inventory counting, movement, and other warehouse operations. Conversely, insufficient inventory also hinders healthy business development. An offline stockout analysis survey revealed that, upon encountering out-of-stock items: • 15% of customers choose never to purchase the item again; • 6% temporarily abandon the purchase; • 31% switch to another store; • Nearly half opt for substitute products. Thus, low inventory leads to: 1. Lost sales revenue; 2. Deteriorated customer experience; 3. Reduced market share; 4. Wasted marketing resources. Striking the right balance between inventory and demand is an elegant art. In inventory management, our goal is to satisfy maximum demand with minimum inventory—i.e., “just-right” inventory. II. How to Manage Inventory Effectively? The essence of management lies in monitoring key performance indicators. Key inventory metrics include: 1. In-Stock Rate 1) PV In-Stock Rate: Page View refers to website page views or clicks. The PV in-stock rate reflects the proportion of clicks on pages where the product is in stock, relative to total clicks. PV In-Stock Rate = (Total PV − Out-of-Stock PV) ÷ Total PV × 100% 2) Physical Inventory In-Stock Rate: (i) Local physical in-stock rate; (ii) Supported physical in-stock rate. The physical inventory in-stock rate reflects the proportion of SKUs with available stock among all SKUs currently listed for sale. Physical Inventory In-Stock Rate = Number of SKUs with stock in shelf status ÷ Total number of SKUs in shelf status × 100% In practice, one often encounters scenarios like this: Top-performing salespeople frequently insist: “To avoid impacting sales, I require 100% in-stock rate for all operational SKUs.” However, there exists a trade-off relationship between in-stock rate and inventory turnover: relentlessly pursuing higher in-stock rates inevitably drives up inventory levels—and thus lowers turnover.

After Five Years Managing WMS, I Finally Understood: Miscalculating "Inventory Turnover Rate" Equals Working in Vain

After that day, I broke down for Old Zheng the three most common types of 'inventory turnover calculation errors' found in warehouses. Compare them against your own operation—you’ll likely recognize at least one. The first type of error is called 'Numerator and Denominator Speaking Different Languages.' This is an especially easy mistake to make. Many people calculate turnover using 'sales revenue' as the numerator and 'inventory value' as the denominator—or even worse, plug in 'procurement amount' as the denominator. But sales revenue includes gross profit, whereas inventory is recorded at cost; mixing these two fundamentally different concepts into one formula creates inherent inconsistency. There is only one correct definition: Turnover Frequency = Cost of Goods Sold (COGS) ÷ Average Inventory Cost; Turnover Days = Number of Days ÷ Turnover Frequency. Note: It must be 'Cost of Goods Sold,' not 'Sales Revenue' nor 'Procurement Amount.' I once worked with a client in the daily chemical industry who used procurement amount as the denominator. During peak season, they placed three separate orders within one month—making their calculated turnover rate look 'exceptionally impressive,' delighting their CEO. Yet, their warehouse was stacked with two large piles of near-expiry goods that simply wouldn’t move. That 'impressive' turnover rate was inflated by purchasing activity—not actual sales. The second type of error is called 'Averages Masking Structural Imbalances.' This is highly insidious. Overall turnover may appear healthy—for example, 60 days—and the boss feels satisfied. But when you drill down by SKU, you find that 20% of fast-moving items turn every 20 days, propping up the average; while 30% of slow-moving or obsolete items haven’t moved in three years—effectively zero turnover. It’s like a class with an average score of 80: you assume everyone is doing fine, yet half the students scored below passing—and their scores were lifted by top performers. Similarly, a warehouse with a seemingly good average turnover often hides a whole warehouse full of unsellable 'zombie inventory.' When I performed structural analysis for Old Zheng, he saw for the first time that among his 4,000 SKUs, fewer than 70% were actually turning; the remaining 1,000+ SKUs were merely occupying space in the system. These items tie up shelf space and capital, yet they’re never counted among 'slow-turning' inventory—because averaging methods conceal them. Therefore, never rely solely on a single turnover figure. Instead, generate a 'turnover distribution by SKU' report and examine what percentage of inventory sits at the tail end—those that never move. If this tail accounts for more than 20%, that warehouse’s turnover rate cannot be trusted. The third type of error is called 'Focusing Only on Frequency While Ignoring Days—and Calculating Only During Favorable Periods.' Some warehouses proudly announce, 'We turned inventory six times last year!' Sounds impressive. But when you ask, 'Which year?', they reply, 'Oh, just during last year’s Singles’ Day period.' Using peak season as a proxy for the full year naturally yields an artificially attractive turnover rate. Others report only frequency—not days. Frequency is easier to grasp, but days matter far more to leadership: they directly reflect how long capital remains tied up. A difference between six turns and four turns translates to two or three months of additional cash flow strain—not something a vague claim like 'we turn quickly' can erase. I generally advise clients to calculate turnover using a 'rolling 12-month' window—never a single month, never just peak season. Numbers derived this way may look less flattering, but they’re genuinely accurate—and far more useful than misleadingly pretty ones. By this point, Old Zheng sighed deeply: 'So… have I been working in vain all along?' I replied: Yes and no. What’s truly been in vain is the period during which he *thought* his inventory was turning quickly—while in reality, capital had been tied up twice as long as assumed.