Inventory forecasting is a critical task for any ecommerce business. This is also one of the most difficult aspects of inventory management to get right.
If you don't have enough inventory, you'll run out of stock and lose sales. But if you have too much inventory, you'll be wasting money on storage and may end up selling products at a loss.
That's why we've put together this guide on inventory forecasting for beginners. We'll cover everything you need to know about forecasting, including:
What is inventory planning?
What is inventory forecasting??
The future of inventory forecasting: predictive analytics
Key types of inventory forecasting
Importance of inventory forecasting for retail owners
How does sales forecasting correlate with inventory forecasting?
How does forecasting help with inventory management?
The Key Advantages of Inventory Forecasting
Key features of effective forecasting software.
What is inventory planning?
What is inventory forecasting?
Inventory forecasting determines the amount of inventory needed to satisfy future customer demand based on the sales forecast over a certain period. It’s a practical solution to manage your purchases better, increase your revenue, and reduce unnecessary costs.
With accurate inventory forecasting, you can keep enough inventory on hand without draining your cash reserves.
Forecasting inventory is critical to the financial viability of any retail business. It assists in finding a balance between putting too much cash into inventory at once and ensuring demand is constantly met without running out of supplies.
This, however, is one of the most challenging components of inventory management to master.
Inventory forecasting software, or demand planning software, provides tools to improve and stabilise the supply chain process, providing businesses with a better idea of what inventory is or will be needed, when reorders should occur, and assists with reducing both out of stock and overstocking occurrences.
Combining historical trend analysis with anticipated season fluctuations and promotional events, inventory forecasting software enables purchasing managers with the ability for better spend management planning and improved collaboration with vendors.
The most important inventory management practices are forecasting (61.3%), warehouse management (50%), logistics (46.8%), and back-end technology (32.3%). These are closely followed by training data scientists (21%), returns management (21%), and data interchange technology (17.7%). In addition, some prioritise investing in sensor technology (12.9%), training retail staff in eCommerce (11.3%), retooling DCs (9.7%), and refitting stores to have warehouse capabilities (3.2%). (Source)
Inventory management practices
Inventory forecasting vs replenishment
With inventory forecasting, you calculate the amount of the different types of inventory necessary for future periods. Factors include replenishment data such as timing, availability and delivery speed — also known as lead time.
Replenishment is the stock required to meet inventory forecasts based on inventory goals, supply and demand.
Sales and demand forecasting is one thing. But true inventory forecasting needs to go a step further and actually plan out how you’ll replenish stock for the upcoming period. This means considering: current stock levels, pipeline inventory, and lead time.
Example: There's no point purchasing 40 units to cover 40 forecasted sales if you already have 27 units on-hand. You also don't want to double buy stock that's already en route.
Forecasting inventory needs to be a strategic process that considers all relevant factors in order to avoid any disruptions in the supply chain.
Key types of inventory forecasting
The most successful businesses can reduce risks, meet future demands, and avoid future losses—and inventory forecasting is one way to achieve this.
However, forecasts don’t have a one-size-fits-all formula. There are different methods and approaches to these formulas.
The most prevalent formulaic strategies for successful inventory forecasting are trend, graphical, qualitative, and quantitative. Choose the optimal strategy based on known stocking limitations, personal insights, sales feedback, customer input, quantitative analysis, and market research.
Importance of inventory forecasting for eCommerce companies
Inventory Forecasting Benefits
Everything boils down to efficiency. You may take advantage of bulk buying without tying up money in unneeded inventory by ordering the optimal amount of product.
Unused supplies or components need warehousing space, which raises expenses.
Inventory and supply chain are strongly intertwined. Improved inventory forecasting helps supply chain management by allowing you to plan ahead of time to ensure you have the proper quantity of stock.
It can also reduce the amount of manual labour involved in inventory and supply chain management. Other procedures, such as reordering points, can be automated.
Customer and supplier satisfaction
Having a product on hand keeps consumers satisfied and increases the probability of repeat business.
Understanding supplier procedures and timeframes also helps you prevent stock-outs and maintain strong relationships with them by reducing emergency orders and improving communication.
Improved business communication may help you reach your goals, and inventory forecasting can play a major part in driving such communication.
For example, by analysing historical performance and predicted consequences of a marketing campaign, your inventory managers may guarantee there is enough goods on hand to fulfil client demand while potentially saving money through buying in bulk.
12 Steps to succeed at inventory forecasting
A better forecast will lead to higher profits and lower costs. So take note of these demand forecasting tips to make it more accurate and effective.
Evaluate the period's basic demand. For example, if the company sold 500 units in the previous quarter, the forecasting model's beginning data point will be 500 units.
Determine patterns and factors, as well as their impact on an increase or drop in sales, such as any promotions or other outside marketing activities that may have influenced baseline demand.
Analyse the sales velocity. Sales velocity is the rate at which sales flow through a company's pipeline. It is determined by the amount of leads, the average transaction value, the conversion rate, and the length of the sales cycle.
Analyse any relevant industry dynamics, such as new market rivals, supplier concerns, commercial buyer behaviour, risks of less costly product alternatives, and other competitive rivalries.
Consider seasonality as it relates to each product. Seasonality may be determined in a variety of ways, including computing a seasonal index for each month, distributing demand across a 12-month period, or employing more advanced statistical approaches.
Build models. This science is more of an art that is built on all of the collected trends and historical information. This data will be used to create forecasting models. There are several statistical approaches available. Which option you select is determined on the consistency of product demand.
Remove irregular or abnormal data points and look for and fill in missing information to clean the data.
Choose between a parametric and a nonparametric statistical technique. Nonparametric does not always indicate that the data has no parameters; rather, the parameters are flexible. Histograms and ranked-choice surveys are examples of nonparametric data.
Import or structure the data in a way suited for the algorithm to process it.
Calculate the model parameters: what is the best and worst case scenario for the data points?
Validation of the model (s). Use a different set of data than the one you used to calibrate the model.
Adjust the model on a regular basis or as events need it. Keep in mind that this is a projection based on assumptions. Real-world experience may reveal that it is incorrect, thus you may need to revise the settings.
The CommerceCore™ Inventory module
An eCommerce business typically has numerous systems for Finance, Purchasing, Inventory, maintenance operations, production and manufacturing, sales and distribution, projects, and so on. Many of them have successfully replaced all of those old systems with a single integrated Merchant Operating System that manages the operations more effectively.
The CommerceCore™ Merchant Operating System avoids data duplication and offers data integrity with a single source of truth by linking Odoo to a growing number of online store systems and marketplaces.
The CommerceCore™ inventory module has several features that set it apart from its competitors. Here are some of them:
Low processing time
Inventory processes are simplified
Rule of routing
Operations based on lead times
Automate your inventory forecasting with CommerceCore™
Striking a balance between having enough but not too much inventory might be the difference between a business's success and failure.
CommerceCore™ inventory forecast refers to the quantity of products you can sell for a specific warehouse or location.
The CommerceCore™ inventory management module has a set of native features for tracking inventory in many locations, calculating reorder points, maintaining safety stock and cycle counts, and forecasting.
By using the demand planning tools of the CommerceCore™ Merchant Operating System's inventory module, you can create an inventory prediction for your eCommerce company.
Forecasting is an important part of business, and making accurate predictions is essential to success.
The forecasts you create are based on data and logic, as well as the refined models you use. Technology can also play a role in helping with forecasting accuracy.
The CommerceCore™ inventory management module can be a key component to your company’s success by making sure you have the right amount of product to meet customer demand while not unnecessarily tying up funds in unneeded inventory.
If you would like more information about how our software can help your business or if you want to discuss your specific needs, please contact us.