What is Inventory Forecasting and How Will It Help Your Business?Time to read: 4 minutes
eCommerce is a highly competitive industry. The sector now has more than 12 – 24 million across the globe, following the eCommerce boom of 2020. Online sellers need to stand out strategically from the pack with many competitors. Companies can no longer afford to employ guesswork for their operation. This statement rings especially true with inventory management and planning.
Forecasting inventory trends is essential in improving cash flows and increasing profit margins. That said, retailers must have a working knowledge of inventory forecasting to remain competitive.
This blog post covers inventory forecasting basics, including its benefits, key components, basic types, and best practices.
What is Inventory Forecasting?
Inventory forecasting refers to various methods to predict the inventory needed to fulfill current and future orders. Balancing healthy cash flow and robust stock levels is necessary for the inventory management process to flow smoothly.
Several factors, including historical sales data, current inventory numbers, and upcoming promotions, play critical roles in inventory forecasting. Therefore, considering all aspects is crucial in gaining accurate inventory estimates.
What are the Benefits of Inventory Forecasting?
Inventory Forecasting is one of the most critical business processes in eCommerce. It provides a big picture snapshot of inventory needs over some time. Having an effective inventory forecasting strategy has plenty of benefits, including:
- Fewer Instances of Stockout and Backorders
A retailer can lose an average of 4% in sales every year due to stockouts and backorders. With hundreds (and even thousands of competitors), it is easy for consumers to choose a brand over the other when they see their products aren’t available at one store. Inventory forecasting minimizes instances of stockouts and backorders. The process, which should involve the entire company, enables the operator to prepare for fluctuations in demand and supply.
- Reduced Inventory Carrying Costs
On the other hand, keeping an operation fluid is crucial to its growth. But it’s not easy to accomplish with too much slow-moving inventory. Data-driven predictions can safely suggest optimal stock levels to a retailer. In addition, the information from various forecasting methods helps prevent merchandise from losing its value.
- Better Relationships with Manufacturers and Suppliers
Accurately forecasting inventory needs can positively influence a retailer’s relationship with its suppliers and manufacturers. For example, a company provides its manufacturers more lead time if it can precisely predict its demands for a given period. Likewise, the better a retailer’s relationship with their suppliers, the better deals they can enjoy.
- Clearer Insight on Business Operations
An eCommerce operation is fragile. There are plenty of factors that can influence supply and demand. Inventory forecasting provides a means for online sellers to remain competitive in such a cutthroat field. Because predictions are accurate and data-driven, any changes in the market would not wholly impact the operation.
Common Forecasting Methods
In general, there are four common types of forecasting methods. A company’s goals and the amount of data available determine the suitable forecasting method to employ. Often, online sellers mix and match these methods to get a better snapshot of their operations.
The quantitative methods use numerical data to construct a model that forecasts future demand. As a general rule of thumb, the more numerical data available, the more accurate the model.
The graphical method is similar to the quantitative approach in that it uses numerical data to predict future demand. The only difference lies in the presentation of the report. As the name suggests, this method conveys information in graphical form.
Trend forecasting involves studying current market trends against historical sales data to project future trends in demand and supply. Once a trend gets identified, strategists within the company can work around the movements to increase potential sales.
The qualitative method is the perfect choice for companies that lack historical numerical data. This method utilizes insights gathered from surveys, focus groups, and market research to formulate an educated demand prediction.
Best Practices in Inventory Forecasting
Inventory forecasting is a lengthy affair. It is essential to employ best practices to make the most out of the process. Here is how to do it:
- Involve the Entire Company
Retailers shouldn’t do inventory forecasting in a vacuum. It is always a good idea to take the input of every key player in the company. It’ll provide new perspectives in doing business and even offer new customer approaches. The more data a company has, the better the predictions would be.
- Invest in the Right Tools
There are plenty of inventory forecasting tools available today. Retailers can even look at the sales spreadsheet to accurately predict the ebbs and market flows. But manual tools can be time-consuming. Investing in real-time forecasting applications provides a dynamic look at a company’s inventory needs. Other applications can automate specific supply chain steps through real-time inventory information, including inventory procurement.
- Take Data Seriously
Numbers don’t lie. When it comes to inventory forecasting, data is invaluable. The more information you have, the better predictions your company would enjoy. For retailers who haven’t looked at data management, it is high time to do so. Historical sales trends and data should be at the center of future inventory decisions.
- Take Note of Interesting Trends
While numbers don’t lie, they don’t paint the whole picture. Adding context to spikes and valleys also influences inventory forecasting. Retailers can take note of this for strategic inventory planning in the years to come.
Supply chains are finicky and fragile. One small mistake across the multiple parts of the supply chain can cause a domino effect impacting the entire operation. Inventory forecasting might not be an exact science, but intelligent estimates grounded on quantifiable data can prevent operational issues.
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