Forecasting in Manufacturing: How to do it

Last updated on Friday, May 24, 2024

Seasonal sales. Unexpected customer order changes. Labor and equipment shortages. Maintaining the stock you need to meet ongoing customer demand is difficult for the manufacturing space.

Fortunately, with the correct manufacturing forecasting techniques and software, you can automate your operations to more accurately anticipate demand and make the necessary adjustments to meet it.

Read this guide to learn:

  • The importance and benefits of forecasting in manufacturing
  • Factors that influence manufacturing forecasting methods
  • Four common demand forecasting methods in manufacturing
  • How to forecast in the manufacturing space

Related article: Demand Planning: Everything You Need to Know

Why Forecasting is Critical in Manufacturing

For businesses in the manufacturing industry, demand forecasting is like a barometer. It helps you know that your product inventory is sitting in the sweet spot. You aren’t overstocking above demand, but you aren’t at risk of going out of stock. Effective inventory forecasting empowers your business to achieve revenue goals while optimizing operational costs.

Forecasting also helps your organization better identify and respond to budget variances (e.g. material cost fluctuations, labor market conditions, etc.). When you consider budget variances when forecasting demand, you increase forecast accuracy and can respond to unexpected changes before your business is impacted.

Benefits of Forecast Production in Manufacturing

Accurate forecasting in manufacturing has a ripple effect. By taking the time to forecast demand, you set your business up to:

  • Ensure optimal inventory levels and peak usage of factory capacity
  • Streamline outgoing distribution efforts
  • Optimize personnel and seasonal hiring
  • Boost customer satisfaction
  • Eliminate unnecessary product costs
  • Reduce overstocking of raw materials and/or finished products
  • Support customer management operations

Related article: Dynamic revenue forecasting for manufacturing

Factors to consider when forecasting in manufacturing

So, you know you need to forecast demand in your manufacturing business. But how do you decide which method to adopt? Here are a few key factors to consider.

Type of Manufacturing

Is your business primarily made-to-order (MTO) or made-to-stock (MTS)?

Made-to-order manufacturing means that production begins after a customer has placed an order. These products are typically customized to customer requirements and therefore have a longer lead time. If your products are made-to-order, you typically have lower inventory carrying costs and rely less on demand forecasting than on order confirmations.

Made-to-stock manufacturing means that products are produced in advance of orders and are stored as inventory. These products are typically more standardized, with fewer options for customization. Inventory carrying costs are higher (e.g. you need a warehouse to store your stock), and demand forecasting plays an important role in inventory optimization.

Most businesses engage in both made-to-order and made-to-stock manufacturing, which requires an agile approach to demand planning.

Production Timelines

Your production timelines can greatly influence your forecasting efficiency and accuracy. And if you, like many manufacturing businesses, operate on multiple production timelines, it can be challenging to forecast your future capacity. Your forecasts must take into consideration each unique production timeline and aggregate the data to spot excess or insufficient capacity.

Historical Factors

Many manufacturing operations will leverage historical factors — such as past trends, sales cycles, and seasonality — to conduct accurate production forecasting. These data points can’t tell the whole story, but when combined with qualitative data like previous sales and production, you can create a more detailed picture of what’s needed for future production.

Related article: Problems With Forecasting

How to Forecast in the Manufacturing Industry

There are four common demand forecasting techniques used by managers in the manufacturing industry. See which forecasting method(s) will work best for you.

1. Push Systems

The push-based manufacturing forecasting method works to predict inventory requirements over a set amount of time using demand data. By assessing current demand, your manufacturing business can predict which products are expected to be purchased and in what capacity.

Keep in mind that it can be risky to get tunnel vision with demand data when forecasting. Demand can vary significantly from year to year for a multitude of reasons. Keep historical data in mind and always keep a pulse on customer and market conditions.

2. Sales-Driven Forecasts

Compared to push system type forecasting, sales-driven manufacturing forecasts offer a much safer and more calculated result. Instead of relying solely on current demand data, sales-driven forecasts use pipeline data to understand what manufacturing needs must be met over a set period of time. Current sales pipeline data is analyzed to understand the likelihood of closing different opportunities and determine future manufacturing needs.

When conducting sales-driven manufacturing forecasting techniques, it’s important to use a strong revenue realization management solution. If you are a Salesforce organization, look for a solution that integrates with or is built natively in Salesforce. This will not only streamline the application of pipeline insights to forecasts but will also simplify your forecast configuration and analysis.

3. Production-Driven Forecasts

Rather than use sales pipeline data to conduct forecasting in manufacturing, some managers opt to focus on production data. A production-driven forecast relies on year-over-year production data to determine future manufacturing needs.

Production-driven forecasting techniques do carry operational risks due to a lack of sales funnel visibility and yearly changes to market and consumer conditions and behaviors.

4. Pull Systems

Compared to a sales-driven forecast, which focuses on potential deal closings, the pull system forecasts production needs using only data from what has already been sold.

With the addition of previous sales data, a well-constructed pull-based forecasting system uses previous consumer data to lower excess inventory while simultaneously improving cash flow.

This method requires proactive planning and ongoing system support to ensure sales data is meticulously tracked and updated. A lack of attention to detail or buy-in from Sales can quickly throw forecasts off balance.

Forecasting in Manufacturing with revVana

The forecasting methods described above are designed to increase your confidence in expected demand. Some methods are more time-intensive than others, but what matters most is the accuracy. The more accurate the forecast, the more accurate the downstream operational forecasts.

If you’re looking to automate your forecasting in manufacturing, check out revVana. The Salesforce-native platform incorporates run-rate revenue, expansion, and seasonally-adjusted revenue, and makes it easy for individuals closest to the customer to make adjustments when details change. With increasingly unpredictable demand in manufacturing, this customer-direct input increases accuracy and can save your business an enormous amount of time and money.

revVana empowers you to model revenue and operational forecasts at multiple levels, analyze gaps that help refine assumptions, and continually improve your forecast accuracy.

Contact our team to learn more about revVana and the results manufacturing organizations have achieved with revVana and Salesforce.

Watch this 30-minute recorded webinar about revenue forecasting in manufacturing

Presented by experienced executives from Salesforce and revVana