Forecasting in Manufacturing: How to Do It Right

Published on Tuesday, January 3, 2023

Whether you’re an industry veteran or manufacturing novice, you know how challenging it can be to maintain proper stock levels to meet ongoing customer demand.

Seasonality of sales, unexpected customer demands, available personnel, and access to equipment all have a big impact on manufacturing decisions. Fortunately, with the correct manufacturing forecasting techniques, you can automate your operations to better anticipate and meet ongoing consumer demand.

This guide will help you understand the importance of forecasting in manufacturing, how to forecast production properly, and what manufacturing forecasting methods you should be using in the manufacturing industry.

Related article: Demand Planning: Everything You Need to Know

Why Manufacturing Forecasting Is Critical

Demand forecasting in the manufacturing industry allows managers to ensure that product inventory neither greatly surpasses forecasted demand nor goes out of stock. Inventory forecasting methods help manufacturing businesses meet their goals by saving on operational costs while ensuring customer demand is met.

Forecasting production additionally helps businesses better identify and respond to budget variances that can be brought on by manufacturing costs, business climate, and labor variances. Combining current budget variances with different demand forecasting techniques allows managers to remain increasingly accurate with calculations and efficiently respond to unexpected impacts.

What are the Benefits of Forecast Production Planning?

Conducting manufacturing forecasting will benefit a business’s operations in many different ways. In fact, manufacturing demand forecasting plays a significant role in the push and pull components of supply chain management, which is at the heart of multiple manufacturing processes.

Specifically, manufacturing forecasting:

  • Ensures optimal inventory levels and peak usage of factory capacity
  • Streamlines outgoing distribution efforts to support customer satisfaction
  • Cuts unnecessary product costs and increases return on investment (ROI)
  • Reduces overstocking of raw materials and/or finished products
  • Supports customer management operations by allowing companies to better adhere to delivery commitments by determining the operational capacity of their factory

Related article: Dynamic revenue forecasting for manufacturing

How Do Manufacturers Forecast Demand?

To conduct accurate forecasting in manufacturing, you must first understand the types of quantitative and qualitative factors that dictate forecasting methods.

Factor 1: Manufacturing Method

One of the largest influences on forecasting is the method of manufacturing being used. Depending on the specific operation, a product will be either made to order or made to stock (made-to-stock relies on historical data for forecasting, whereas made-to-order relies on current order data).

Factor 2: Production Timeline

Another factor that influences manufacturing forecasts is the multiple timelines that accompany operations; the average timeline of production can significantly sway forecasting outcomes. If a business experiences an increased demand for a product, but the manufacturer only has certain production capacity over a set forecasting period, these timeline factors must be considered for accurate forecasting.

Factor 3: Historical Factors

Similarly, many manufacturing operations will leverage historical factors — such as past trends, sales cycles, and seasonality — to better conduct production forecasting. While such quantitative factors can’t provide full accuracy in a forecast outcome, combining qualitative data like previous sales and production helps create a more targeted and broad angle of necessary future production.

Related article: Problems With Forecasting

What Are the Demand Forecasting Methods in the Manufacturing Industry?

With the right data in hand, you should now be ready to conduct manufacturing forecasting. There are four general manufacturing demand forecasting techniques that are used by managers. Understanding each one helps you understand 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, a manufacturing business will predict which of its products are expected to be purchased and in what capacity.

Bear in mind, there is a high risk of solely leveraging demand data for forecasting, as demand can vary significantly from year to year for a multitude of reasons.

2. Sales Driven Forecasts

Compared to push system type forecasting, sales-driven manufacturing forecasts offer a much safer and calculated result. Instead of relying solely on current demand data, a sales-driven forecast uses pipeline data to gain an expectation of what manufacturing needs must be met over a set period of time. Current sales pipeline data will be 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. Forecasting solutions with Salesforce integrations, like revVana, provide great insight into pipeline and customer data for all-around enhanced support.

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-to-year production data to determine the expected manufacturing needs over an upcoming period of time

As with the above demand forecasting types, production-driven forecasting techniques have 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, a pull system forecasting method uses data only from what has been sold to conduct production forecasting needs.

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.

However, this method can be difficult, as it requires proper planning and ongoing system support. A lack of either could result in a forecast being thrown off balance, which creates negative impacts across a manufacturing operation.

Forecasting Revenue in Manufacturing with revVana

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

revVana’s approach to revenue forecasting incorporates run-rate revenue, expansion, and seasonally-adjusted revenue, along with the ability of those closest to the customer to inform changes that they see and that no financial model could uncover.

With increasing variance in demand, this customer-direct input increases accuracy. revVana provides organizations with the power to model revenue and operational forecasts at multiple levels, analyze gaps that help refine assumptions and continually increase forecast accuracy.

Learn more about revVana and how it can help your forecasting accuracy today.

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

Featuring executives from Salesforce and revVana