Stockouts are consistently a dread for retailers and CPG companies. It isn’t just that they lead to lost sales, but they also increase operations costs and result in reduced customer satisfaction and loyalty. Customers obviously feel rather annoyed and disappointed when they can’t find the item they’re looking for – this is a shopper emotion every retailer or CPG company works very hard to avoid.
So, the question on every business’ mind is, how can they fix this? How can they ensure that they are able to drive out out-of-stock nightmares and ensure that their customers are delighted with their shopping adventures?
Fortunately for retailers and CPG companies, there are quite a few solutions available to help avoid the dreaded stockout scenario. Many causes of stock-outs can be avoided simply by taking steps to get a better understanding of your business and products, and by working towards enhancing existing processes at the store.
While there are plenty of causes of stock-outs to happen in general, for the scope of this blog, we will be addresses two of the most common ones and if you continue reading, you’ll also find strategies you can implement to avoid stock-outs and subsequent stock loss. We’ll also talk about our experience with helping major fortune 500 companies like Unilever, RB, Britvic and so on, fix their stockout woes.
Two Common Reasons for Out-Of-Stock Situations
#1 Inaccurate Demand Forecasting
“47% of OOS occurs due to inaccurate demand forecasting” – P&G
Decision-makers typically make inaccurate demand forecasting due to their inability to analyze data from various external data sources, all of which impact a product’s demand and buyer’s behaviour.
Some key data sources can include:
According to the P&G report: “Whenever a shopper shifts their buying pattern due to an OOS, it adjusts the demand history away from the sales history and no one can see the true demand history.”
Demand, essentially is sales combined with lost sales. However, lost sales are exactly that: lost. Sometimes shoppers do inform the store about the products they didn’t find so they can be informed when it does come back in stock. However, this doesn’t happen as often as the stores would like, which means, it becomes practically impossible to measure demand accurately.
However, if stores can manage their POS data efficiently, they can better gauge how quickly certain items are moving. This requires drawing careful comparisons and assessments between historical data and real-time data, in order to predict the impact of lost sales from unexpected out of stock situations. These figures should then be used for better demand forecasting.
Weather has an immense impact on the consumer psychology, habits, preference for products and overall behavior. Obviously, products that are required for specific weathers only will have varying demand throughout the year. For example, raincoats, umbrellas, gumboots, etc., will only have high demand during monsoons. If there is a sudden outbreak of a diseases, the demand for certain health related products such as face masks and sanitization products would go drastically up.
These are situations that companies should extra data for, in order to ensure that they’re able to have enough stock to meet consumer demand. Assessing historical data in combination with future weather predictions, as well as past weather patterns, stores will be better able to forecast the levels of demand and supply.
When big events happen, such a music concert or a sports tournament, there’s obviously going to be a massive influx of consumers and subsequent increase in demand for certain types of products – these could be beverages, novelty items, etc.
This may be an obvious one but data on past sales provides invaluable inputs on demand and sales for different products at different times and locations, throughout the year.
#2 Field Sales Use Excel Sheets For Tracking KPIs
As part of their jobs, field sales personnel track certain key metrics and KPIs around primary and secondary sales. These metrics enable them to gauge if there are sufficient products available across different outlets. These metrics include
- MSL compliance: MSL is the Must Stock List which represents the number of SKUs that must be present in a particular class/category of an outlet.
- OTIF losses: CPG companies and distributors are aware that all orders have to be received on time and in full. As much as companies strive to achieve this ideal situation, they encounter various bottlenecks, such as required stock being unavailable at the warehouse, trucks not being available, or inefficient truck loading, etc. All of these cause orders to not be filled on time and in the required quantity.
In most companies, the field sales personnel use Excel sheets to track these KPIs and generate reports. The data is also consolidated manually, making the entire process inefficient, unnecessarily time consuming and prone to error.
This results in diminished accuracy and slow decision making, which further impacts overall sales and revenue. As a result, the accuracy and speed in decision-making decrease – impacting the overall sales and revenue. Sales teams are essentially rendered incapable of properly analyzing store performance and identifying products which require restocking.
Prevent Out-Of-Stock Situations With Acuvate’s Compass
Compass is an AI-Powered Trade Promotion Optimization Software for CPG and Retail companies which not helps you forecast product demand and sales but also optimize your trade promotions based on it.
Compass is fed with data from various internal and external sources and leverages advanced analytics to effectively harness this data. This helps decision-makers to factor-in data from various sources and take much informed decisions.
You can prevent out-of-stock situations by monitoring key reports and metrics around MSL compliance, Vision Score, Off-the-Shelf availability etc. Advanced analytics also send alerts around these metrics to keep you updated instead of you going through the data and analyzing it.
We have helped a major CPG company prevent stock out situations and increase the overall revenue by 3%. The field sales teams used excel sheets to monitor key metrics, tracking the KPIs and reporting. Data was consolidated manually.
If you’d like to see Compass and our Business Intelligence capabilities in action, we’d love to show you a demo.