Inventory forecasting methods to improve planning processes

Accurate inventory forecasts give you data to track your sales and help place optimal orders. What inventory forecasting method and activities are you using to optimize your supply chain? 

It's not easy to predict future demands, given the erratic nature of customers and the increase in supply chain disruptions. As an inventory planner, your forecasting process needs to factor in a lot more than just relying on past sales data to predict the inventory you need for tomorrow. Your forecasting methods should draw from various data points to accurately forecast future sales and determine the right amount of inventory needed to avoid incurring excess stock or experiencing stock-outs.

A US consulting firm, Ernst & Young recently reported, “companies that do not change their forecasting methods to meet changing demand, scenario planning for both near-term operations and long-term capital allocation will be fatally flawed.

During a recent EY webcast on forecasting for recovery scenarios, only 9% of participants said they were “very confident” in their company’s ability to forecast demand for products or services. In fact, 35% said they were either “not at all confident” or “not very confident.”

This article explores: 

What is inventory forecasting? 
The reason your inventory forecast is not accurate 
Inventory forecasting methods
Essential processes to improve inventory forecasting
5 Long-term benefits of an effective forecasting process 

What is inventory forecasting?

A great sentence that sums up forecasting:

“If you don’t know what you will sell tomorrow, how will you know what to buy today?” - Barry Kukkuk, CTO NETSTOCK.

Achieving an accurate forecast is one of the most vital aspects of managing inventory effectively. The purpose of an inventory forecast or demand planning is to use historical sales forecasts and other data points to predict demands. This will help the inventory planner allocate the necessary resources to ensure enough stock is available to meet demand. An accurate forecast also helps to reduce your excess inventory and in turn, you increase your profit margins. 

As an inventory planner, for each stock item, or SKU [stock keeping unit], you need to be able to answer the following questions:   

• How many items must I order? 
• How much safety stock is required? 
• How often do I need to place an order? 
• What is the reorder level? 
• How will the minimum order quantity affect future orders? 
• What inventory do we need in three or six months to improve your fill rate? 

Your forecast requires data points from various sources:  

• Current inventory levels 
• All open purchase orders 
• Historical sales information
• Supplier lead time 
• Customer trends 
• Seasonality 
• Input from your sales and marketing departments 
• Insights from previous marketing and promotional campaigns

Regular team collaboration is another essential input to ensure your forecast is accurate. Your inventory planners, sales team, operations, and marketing team should meet monthly to discuss planned promotions, upcoming marketing campaigns, or even feedback from previous campaigns. The inventory planner will know if they need more of a particular stock item. Sales teams should always share market intel about their suppliers or customers, again, critical information for the inventory planner to factor into their forecasting. 

The reason your inventory forecast is not accurate 

Many demand planners think that if their forecast is accurate, they won’t experience any challenges in their supply chain. Sadly, this is not the case because no forecast engine will deliver perfect forecasts for all your stock items all of the time. Firstly, importing data from your ERP into a spreadsheet isn’t going to give you a forecast. Even though there are varying forecasting formulas in Excel, these are designed for single data sets and are not optimal for hundreds or thousands of items. By the time you have checked and updated every single record one by one in your spreadsheet, the data is most likely outdated and prone to human error.

A recent post in The Manufacturer highlighted, “spreadsheets are often used to monitor a manufacturer’s supply chain, today companies need a real-time, big-picture outlook. One international organization previously coordinated its global supply chain via spreadsheets. It cut and pasted requisitions into individual supplier spreadsheets and emailed them out. A master spreadsheet tracked overall supplier performance. The problem was this process was tedious, prone to error, and often related outdated information.”

Watch how NETSTOCK's forecasting engine can create accurate forecasts.

Inventory forecasting methods

Four main forecasting methods 

To help you achieve an accurate inventory forecast, you need to select the right forecasting method that will best support your business strategy, goals, and timings.  

According to the software review platform, g2.com, the main difference between quantitative and qualitative data is, “quantitative data can be counted, measured, and expressed using numbers. Qualitative data is descriptive and conceptual. Qualitative data can be categorized based on traits and characteristics.” 

1)  Qualitative forecasting

When historical data is not available, the forecasting is largely based on “gut feeling,” market intel, and insights on the existing customer base. This is often the case when you stock a new product. The method will draw on insights from the sales team, marketing team, or other market research. Some businesses will also utilize the Delphi method. According to invenstopedia.com, the “Delphi method is a process used to arrive at a group opinion or decision by surveying a panel of experts.”  Other examples of qualitative methods are using surveys and scenario building. 

2)  Quantitative forecasting

This method uses data and collates information from various data points to provide a prediction of future demand. 

This method draws on data from: 

• Previous sales and past revenue for the last 12 months.
• Historical inventory trends. 
• Surplus stock volumes trends. 
• Seasonality trends.

Alternative methods that demand planners can use: 

3)  Trend forecasting 

With changes in customer demand, this forecasting method reviews stock trends over a period of time. While this method will predict trends, it does not factor in seasonality or sudden spikes or declines. This method is generally used to showcase the kinds of stock items the customer is interested in, and this data will help sales and marketing teams with potential sales campaigns. 

4)  Graphical forecasting 

This method of forecasting is visual, and often, this method is easier to understand. Graphical forecasting will use the same data as you would for trend forecasting and merely creating a visual representation of the data. This method will show you your stock’s general upward or downward sales movement without going into too much detail. 

Essential activities to improve inventory forecasting 

Since each stock item will have its demand, no sales forecast will be the same. Ideally, you need to independently capture the monthly sales history for each item in each location and perform monthly and weekly activities. However, before you do that, you should first classify your inventory. 

1)  Inventory classification 

An inventory holding business will typically have hundreds or even thousands of different stock items, and you must identify your high-moving and slow-moving items. A vital step to improving your forecasting process is to classify your inventory to focus on the right stock items that make you the most profit.

When you classify your inventory, you will immediately know: 

• Your fast-moving items,
• your slow-moving items and,
• what items need to become obsolete or non-stocked. 

2)  Monthly forecasting activities 

• Use a forecast engine to create computer-generated forecasts for all of your items.
  • Use sales or demand history to generate a forecast.
  • Pick up on trends, seasonality, intermittent demand, one-off sales spikes, and factors in data such as lost sales. 
    
    
• Any worthy forecast engine will generate forecasts by using several different algorithms. Once done, it should compare all of the generated forecasts with the sales, or demand history to determine the “best fit” forecast. This results in accurate forecasts for the bulk of your items. 

• A small percentage of your items will need manual intervention, as no forecast engine will get every forecast right. Monitor those items with consistent variances between sales and forecast:
• Adjust the forecast up where sales have consistently exceeded the forecast.
• Adjust the forecast down where sales have consistently been lower than the forecast.
• Aligning sales and forecasts means there is less risk of generating excess inventory or experiencing costly stock-outs.
   
• Adjust your forecast for new or lost customers as soon as you are aware of the change. Use the computer forecast, but:
• Subtract a lost customer’s monthly demand.
• Add in new customer’s expected monthly demand. 
  
  
• Since new items will have no sales history, these need to be manually forecasted for the first few months. Check to make sure that the “new” item is not a replacement for a product, where a cheaper or better quality product has been sourced and will now be sold instead of the old product. In this instance, you would link the “new” item to the “old” item, which results in the sales history of the old item being used to generate the forecast for the new item. This has the benefit of getting an earlier indication of forecast accuracy, which is vital to getting the right safety stock in place sooner. 
  
  
• Adjust forecasts to include additional promotional demand on top of the expected regular sales. Use team discussions and inputs to help guide these adjustments. The better the input, the better the forecast result, the better the stock position and success of the promotion! 
  
  
• Report on forecasting performance and make sure your measure also distills the bias between over-and-under forecasting. Measuring the difference between your system-generated forecast and the manually adjusted forecast is helpful to establish whether the manual intervention improved the result.  
  
  
• Conduct a sanity check at a macro level. After making changes to individual item forecasts on an exception basis, review overall sales to forecast to ensure that the overall growth is not too extreme or too conservative. Most forecasting applications will enable macro forecast adjustments to be made, should they be required. 

3)  Weekly forecasting activities: 

Weekly activities highlight exceptions between the pro-rated forecast and the actual sales. Here any severe deviations between sales and pro-rated forecasts highlight potential issues with the forecast on individual items. Reviewing these alerts enables prompt response to possible changes in demand. 

• Review forecasts for the top 5-10 sales versus forecast exceptions:

• Increase your forecast - if you are selling more
• Reduce your forecast - if you are selling less
• Consider that you may be selling less due to stock-outs

5 Long-term benefits of an effective forecasting process 

When you have a structured process in place, you will start to see improvements in your forecast, and more specifically, you will notice: 

• Happy customers - who receive the right stock on time and in full.  
• Reduced stock-outs - you won’t miss out on any potential sales.  
• Less safety stock - your order recommendations will be accurate. 
• Reduction of your slow-moving and obsolete stock - you won't order more of these items by classifying your stock items.
• A focused sales strategy -  accurate forecasts are useful for sales and marketing when planning their promotional campaigns. 

Supply chains are under pressure daily. To stay competitive in today’s market, invest in demand planning software that will unlock your data and give you the visibility needed to generate reliable sales forecasts that factor in seasonality, trends and identify problem areas. 

How accurate is your inventory forecast? Are you sitting with too much safety stock?

Watch your personalized demo to learn how NETSTOCK can help solve your forecasting challenges.