What is stock-out risk and why it matters
Imagine going to your favorite store to buy a product you’ve wanted for weeks. You get to the store only to find no stock. The store has lost a sale and quite possibly your loyalty. This scenario captures the danger of running out of inventory when customers need it most.
A stock-out happens when a business can’t meet customer demand as all the inventory has been sold or used. stock-out implications can ripple throughout the organization, from loss of sales and revenue to dissatisfied customers and damaged brand reputation. Ultimately, the company can lose market share.
In this blog, we’ll explore quantitative approaches to cutting the stock-out risk and strategic measures to overcome challenges and reduce stock-out risk using advanced technologies.
Table of contents
- The stock-out probability formula
- Why calculating stock-out probability matters
- Common causes of stock-outs
- How to reduce stock-out probability: data-driven and strategic solutions
- Advanced techniques for reducing stock-out risk
- Stock-out probability formula in action: a case study
- Handling stock-outs when they occur
- The role of technology in reducing stock-outs
- Reducing stock-out risk as a competitive advantage
1. The stock-out probability formula
Here’s the formula for calculating the probability of stock-out:
Formula: PS = ES / ED * 100
Where:
PS = Probability of stock-out (%).
ES = Number of expected stock-outs.
ED = Number of expected demand requests.
Example calculationLet’s consider an example. Based on historical data and other forecast inputs, the company predicts running out of stock 20 times (ES) over the period. The business expects 750 demand requests (ED) for an item monthly. Using the stock-out formula, we can calculate the probability of stock-out as follows:
Substitute the numbers in the formula:
PS = 20/750×100 = 2.67%
The probability of stock-out is 2.67%.
2. Why calculating stock-out probability matters
You may wonder what the point of calculating the stock-out is. Here’s why it matters:
- Enhances customer satisfaction: A high stock-out probability may lead to disappointed customers, lost sales, and reputational damage. When the stock-out risk is known, managers can adjust inventory levels to meet customer demand.
- Data-driven decisions: Managers can make better decisions based on the stock-out probability. They can use this knowledge to plan order placements and deliveries. The importance of accurate forecasting cannot be overstated, as it enables decisions on safety stock holding and forecast model adjustments.
- Optimizes costs: Balancing stock-out risk with holding costs ensures efficient inventory management. A lower stock-out probability reduces lost sales but may increase carrying costs.
- Supports demand planning: stock-out probability provides demand planners with valuable insights. Planners can use this data to refine forecasts, matching them more closely with actual demand. Better stock alignment reduces the likelihood of overstocking and understocking.
3. Common Causes of stock-outs
- Supply chain disruptions: These may be caused by delayed transport or production problems like machine breakdowns or material shortages.
- Inaccurate demand forecasting: Manufacturing and purchase orders are all placed according to the demand forecast. If the forecast is incorrect, stock-outs may occur.
- Lead time variability: Reorder points are calculated according to the demand during lead time. If the lead time fluctuates, the stock may run out before it is replenished.
- Insufficient safety stock: Safety stock must cover demand spikes, or a stock-out is likely.
4. How to reduce stock-out probability: data-driven and strategic solutions
Regular stock-outs are a disaster for businesses. stock-outs cause lost sales, upset customers, and reputational damage. Companies must find solutions to reduce disruptions and optimize stocks.
Improve demand forecasting
All planning is based on demand forecasts. A poor forecast will upset all subsequent plans for procurement and production.
Advanced machine learning technologies analyze historical data and market trends. This software integrates sales data with market conditions and exogenous factors, producing more accurate forecasts.
The formula used to calculate the probability of stock-out typically factors in demand variability by including safety stock. More accurate forecasts reduce the need for safety stock, cutting unnecessary inventories.
Set appropriate safety stock levels
Safety stock is a buffer. It is set to absorb unexpected demand spikes and supply chain delays. Lead time, demand variability, and product criticality all influence the size of the safety stock, as does the desired service level.
The goal is to set safety stock levels that balance the desire to supply a particular service level with the cost of holding excess stock. Sufficient safety stock reduces the ES (expected stock-outs) in the formula, lowering the stock-out probability.
The ideal safety stocks balance the desired service level with the cost of holding excess stock. Sufficient safety stock reduces the ES (expected stock-outs) in the formula, lowering the stock-out probability.
Optimize reorder points
Ensure your business has enough stock to meet customer demand without overstocking by optimizing the reorder point (ROP). Automated systems can set and adjust the ROPs using real-time data and predictive analytics. These systems track inventory, sales, and lead times in real-time and then immediately update information based on the trends. They use predictive analytics to forecast future demand accurately.
Automated systems trigger reorder points in good time. Your system is not subject to human error, so that you can depend on regular, reliable stock replenishment. The system ensures that stock is always available by matching orders to actual demand.
A precise reorder strategy helps your business to meet demand without dipping into safety stock too often. It reduces ES through lower safety stock requirements.
Diversify your supply chain
Dependence on a single supplier increases your vulnerability to disruptions, like geopolitical circumstances and natural disasters. Supply diversification reduces this risk. Risk spread across two or more suppliers promotes a more robust supply chain and reduces expected stock-out frequency, ES in the formula.
Strategically selecting several suppliers locally and abroad helps businesses achieve a more flexible, cost-efficient supply chain and improved service levels.
Leverage real-time inventory tracking
You can achieve inventory transparency across locations with real-time inventory tracking. Inventory visibility reduces oversights and stock calculation errors. Real-time systems can quickly alert you and your team to pending stock problems as they become evident. Integrated with predictive analytics, these systems forecast demand and can raise potential stock-out alerts before you run out of stock.
Radio Frequency Identification (RFID) facilitates real-time tracking. RFID tags attached to items transmit inventory data to a central database, tracking inventory movements as they happen.
Cloud-based inventory systems gather information from various locations and warehouses to create a central database from which all employees work.
5. Advanced techniques for reducing stock-out risk
stock-outs disrupt operations, upsetting the supply chain and impacting sales. However, modern technologies can help your business install advanced techniques to reduce stock-out risk and optimize inventories. The role of technology in this process is significant, providing reassurance and confidence that these disruptions can be effectively managed.
Use a stock-out risk report
stock-out risk reports track items at risk of stock-out. They can calculate the stock-out probability for each item so you can focus on critical items before they cause a problem.
These reports highlight the items that are most likely to cause a problem. Use them to adjust the ROPs of high-risk products.
Vendor-Managed Inventory (VMI)
VMI is a popular strategy that allows suppliers to manage inventories and ensure that stocks are always available. The most common VMI use is merchandising in stores. The supplier sends a representative to check the stock levels regularly, topping up stock at a pre-set level.
VMI reduces administration, improves stock accuracy, and reduces inventory stock-out risk.
Implement Just-In-Time (JIT) Inventory Management
JIT is famously used in the automotive industry as well as several other sectors. The strategy seeks to keep stocks at the lowest possible level by arranging regular deliveries as goods are needed. JIT ensures low stocks, cutting holding costs, but your suppliers must be reliable since there is a tiny margin for error.
6. Stock-out probability formula in action: case study
Formula: PS = ES / ED * 100
Where:
PS = Probability of stock-out (%).
ES = Number of expected stock-outs.
ED = Number of expected demand requests.
Based on historical data and other forecast inputs, the company predicts running out of stock 20 times (ES) over the period. The business expects 750 demand requests (ED) for an item monthly.
Using the formula:
PS = 20/750×100 = 2.67%
The probability of stock-out is 2.67%, so there is a 2.67% chance that the item will not be out of stock when a customer wants to buy it.
The business can reduce the probability of stock-out in several ways.
It can increase safety stock. This reduces ES in the following way. Let’s assume the number of stock-outs ES drops to 10.
Then:
PS = 10/750×100 = 1.33%
The probability of stock-out has halved, but the stock will have risen by the appropriate amount of safety stock, increasing holding costs.
Improving forecasting accuracy has a similar effect, as it reduces demand variability. Let’s assume that an improved forecast shows that demand is likely to be closer to 825 than 750. Greater accuracy also reduces expected stock-outs and improves overall supply performance.
PS = 15/825×100 = 1.82%
“Being able to adjust safety stock based on statistical modeling using history and forecast deviation instead of just several days coverage has improved our inventory fill rate from 90.9 to 98%.“ Philip Yu, Senior Sales and Operations Manager – The Little Potato Company
7. Handling stock-outs when they occur
No matter how good your planning is, stock-outs will occur from time to time. How you handle the problem can enormously affect how quickly you recover.
- Communicate proactively with customers: Transparency will maintain trust and loyalty.
- Offer alternatives or backorders: Provide options to keep customers happy.
- Emergency replenishment strategies: Fast-track orders, move inventory from other locations, or find alternate suppliers.
8. The Role of technology in reducing stock-out probability
Modern technologies like Netstock can produce stock-out probability reports and improve stock management, reducing the probability of stock-outs. Managers can use the available tools to predict stock shortfalls, reducing the risk of lost sales.
Artificial intelligence analyzes vast data sets, including real-time and historical sales, actual supplier lead times, and external factors like economic indicators. AI and predictive analytics in stock management produce highly accurate forecasts and reduce the need for safety stocks.
“If we want 120 days of forecast on our shelf, Netstock lets us do that easily. If we have limitations in capacity, the planners can see that right away and adjust the safety stocks downward, reducing the order across all sizes. It helps us to balance sales, financial, operational, and service requirements.” Steven Allgood, Director of Inventory Management” – Edwards Garments
9. Reducing stock-out risk as a competitive advantage
Modern businesses compete in increasingly complex markets. Intricate supply chains and demanding customers don’t make the task any easier.
With Netstock, you can reduce stock-out risk and gain a competitive edge. Advanced demand and supply planning technology will help you optimize inventory and improve forecasting. Leverage real-time data and cloud-based tools to streamline efficiency.
