Inventory analytics: beyond just stock levels

Inventory is frozen cash

Every dollar sitting in inventory is a dollar not available for marketing, operations, or growth. Inventory analytics goes beyond knowing what’s in stock—it reveals whether your inventory is working for you or trapping your capital.

Smart inventory analysis helps you stock the right products, in the right quantities, at the right time.

Inventory turnover: the fundamental metric

Inventory turnover measures how quickly you sell through your stock.

The calculation:

Cost of goods sold divided by average inventory value. If COGS is $500,000 annually and average inventory is $100,000, turnover is 5x per year.

What turnover tells you:

Higher turnover means you’re selling through inventory faster. Cash cycles back more quickly. Less risk of obsolescence. Lower storage costs.

Benchmarks vary by category:

Fashion might target 4-6 turns. Consumables might achieve 8-12 turns. Durable goods might be 2-4 turns. Compare to your industry, not generic benchmarks.

Days of inventory

Days of inventory translates turnover into time.

The calculation:

365 divided by turnover ratio. Turnover of 5x means approximately 73 days of inventory on hand.

Why days matter:

Days of inventory is more intuitive. It tells you how long your current inventory will last at current sales rates. Rising days of inventory means you’re accumulating stock faster than you’re selling it.

Turnover by product and category

Aggregate turnover hides important variation.

Fast movers versus slow movers:

Some products turn 12x per year. Others turn once. Managing them identically doesn’t make sense.

Category-level turnover:

Different categories have different natural turn rates. Analyze turnover at the category level to understand performance relative to category norms.

Identifying problems:

Products with dramatically below-average turnover for their category are candidates for markdown, discontinuation, or reduced reorder quantities.

Sell-through rate

Sell-through measures what percentage of received inventory sells within a period.

The calculation:

Units sold divided by units received (plus beginning inventory) over a period. If you had 100 units available and sold 70, sell-through is 70%.

Why sell-through matters:

Sell-through reveals how well new inventory performs. Low sell-through on new products indicates potential demand forecasting problems or product-market fit issues.

Tracking over time:

Compare sell-through rates for similar products. Products consistently underperforming their category need investigation.

Stock-to-sales ratio

Stock-to-sales shows how much inventory you hold relative to sales velocity.

The calculation:

Inventory value divided by monthly (or weekly) sales value. If you hold $200,000 inventory and sell $50,000 monthly, ratio is 4.0.

Interpreting the ratio:

Higher ratios mean more inventory relative to sales—more capital tied up, more risk. Lower ratios mean leaner inventory but potential stockout risk.

Target ratio:

Optimal ratio depends on lead times, demand variability, and risk tolerance. Track your ratio over time and understand what drives changes.

Identifying dead and slow stock

Some inventory isn’t working at all.

Dead stock definition:

Products with zero or near-zero sales over an extended period. These are tying up capital with no return.

Slow stock definition:

Products selling far below their category average. They move, but slowly, consuming disproportionate capital.

The cost of dead stock:

Storage costs. Insurance costs. Obsolescence risk. Opportunity cost of capital. Eventual markdown or write-off. Dead stock is expensive even before you discount it.

Aging analysis

Track how long inventory has been on hand.

Age buckets:

0-30 days: Fresh inventory. 31-90 days: Normal. 91-180 days: Aging. 180+ days: Concerning.

Why aging matters:

Older inventory is more likely to need markdowns. Fashion items become dated. Perishables approach expiration. Technology becomes obsolete.

Action triggers:

Set thresholds for action. Products aging into concerning buckets should be evaluated for markdown or promotion.

Stockout analysis

Stockouts are the flip side of overstocking.

Tracking stockouts:

How often are products out of stock? How long are they out? Which products have frequent stockouts?

Stockout cost:

Lost sales. Lost customers who might not return. Customer frustration. These costs are real but harder to measure than overstock costs.

Stockout patterns:

Are certain products or categories chronically stocking out? This suggests systematic underordering or demand forecasting problems.

Inventory investment return

Inventory is an investment. Analyze its return.

Gross margin return on investment (GMROI):

Gross margin dollars divided by average inventory cost. If you generate $200,000 gross margin on $100,000 average inventory, GMROI is 2.0.

What GMROI tells you:

Higher GMROI means better return on your inventory investment. Products with high GMROI deserve more inventory investment. Products with low GMROI might need less.

Lead time and safety stock

Inventory levels should account for replenishment realities.

Lead time consideration:

Longer lead times require more inventory to avoid stockouts. Track lead times by supplier and adjust inventory levels accordingly.

Safety stock calculation:

Safety stock buffers against demand variability and lead time variability. Products with unpredictable demand need more safety stock. Stable products need less.

Seasonal inventory planning

Many businesses need different inventory levels by season.

Pre-season buildup:

Building inventory before peak seasons ties up cash but ensures availability. Time this buildup carefully.

Post-season reduction:

After peak season, reduce inventory to free cash. Markdowns might be necessary to clear seasonal excess.

Year-over-year comparison:

Compare inventory levels to the same time last year. Are you carrying more or less? Is that intentional?

Metrics for inventory analytics

Focus on these inventory metrics:

Inventory turnover (overall and by category). Days of inventory. Sell-through rate by product and category. Stock-to-sales ratio. Dead and slow stock percentage. Inventory age distribution. Stockout frequency and duration. GMROI by product and category. Lead time by supplier. Seasonal inventory patterns.

Inventory analytics reveals whether your capital is working hard or sitting idle. Use these metrics to optimize your inventory investment for profitability and cash flow.