Types, Examples, and Methods of Demand Forecasting

Types, Examples, and Methods of Demand Forecasting

It is impossible to predict the future that too with certainty. But you can use different techniques, and one of them is demand forecasting. Using a forecasting model, it becomes easy to make sound business decisions.

What is Demand Forecasting?

Demand forecasting predicts future sales using historical data to make informed business decisions. It helps businesses anticipate customer demand and plan for the future, allowing them better to manage inventory, production, and staffing levels.

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By understanding customer demand trends, businesses can adjust their strategies accordingly and ensure they are meeting their customers' needs. Demand forecasting also helps businesses identify opportunities for growth and expansion. With accurate forecasts, companies can better allocate resources and increase efficiency to maximize profits.

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Related: What is Production Forecasting

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Types of Demand Forecasting

There are different types of demand forecasting. However, it is necessary to understand that the forecast differs depending on the various forecasting model. One of the best practices includes multiple demand forecasts. It helps to provide a clear picture of future sales.

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Besides, you can use multiple forecasting models to highlight the prediction difference. Such differences point to a need for better research and data inputs. Let us check out the different types of demand forecasting.

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Passive demand forecasting

It is the simplest type of demand forecasting. For this model, you must use past sales data to predict the future. Besides, using the data from the same season to project future sales is vital.

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Therefore, you are comparing apples to apples. Besides, it is true if your business faces seasonal fluctuations. A passive forecasting model works if you want to build solid data. Also, it is a perfect model for companies that target stability instead of growth.

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Moreover, passive demand forecasting is much easier than other different types. It is because passive demand forecasting does not require statistical methods or study economic trends.

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Related: Backorders vs out of stock: Things to know about keeping item available

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Active demand forecasting

In case your business is going through the growth phase or is a startup. Then active demand forecasting is a great choice. This model considers market research, expansion plans, and marketing campaigns.

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Moreover, the active projections often factor in externals. Some considerations include economic outlook, growth projections for the market sector, etc. Startups with insufficient historical data must keep their assumptions depending on external data.

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Short-term projections

Short-term demand forecasting considers the next three to twelve months. It is useful when it comes to managing the just-in-time supply chain. Besides, the short-term demand helps adjust the projections depending on the real-time sales data.

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For example, if you run a product lineup facing frequent changes, you must know short-term demand. Regarding businesses, the short-term forecast is a piece of a giant puzzle.

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Demand Forecasting Methods

Different methods are there for creating demand forecasts. Listed below are some of the demand forecasting methods to know about.

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Trend projection

It uses past sales data to find out future sales. Trend projection is the most straightforward demand forecasting method. Besides, it is necessary to adjust to future estimates for historical anomalies. For example, you saw a sudden increase in demand last year. But, it happened after your product features on any popular TV show.

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Market research

This method is based on the various data from the customer surveys. Market research takes time as well as effort to send out surveys as well as tabulated data. Moreover, this method provides the valuable insight you cannot get from internal sales data.

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Examples of Demand Forecasting

Almost every business gets a lot of benefits from demand forecasting. Here are a few examples of demand forecasting and the benefits eCommerce companies get from it.

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Passive projection

Suppose a couple sells costumes, decorations, and party favors for kids. They have been doing this business for years. The average last three years of sales are used for projecting the upcoming year's trends. From the historical data, they understood that May and October are the best years and December and August is the worst month,

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Therefore, you must know a few things about demand forecasting. If you want to use it for business, it is vital to know about demand forecasting.

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Benefits of Accurate Demand Forecasting

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Here are some of the benefits of having accurate demand forecasting:

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Improved Inventory Management

Accurate demand forecasts help businesses manage their inventory levels more efficiently by ensuring they always have the right stock. It can help reduce costs associated with overstocking or understocking and minimize the risk of lost sales due to out-of-stock items.

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Related: eCommerce Inventory Management Tips & Tricks

Enhanced Production Planning

It enables businesses to plan their production schedules better to meet customer demands promptly. It can reduce costs associated with overproduction or underproduction and ensure that customers receive their orders when needed.

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Increased Revenue

It allows businesses to anticipate customer needs better and adjust their pricing strategies accordingly. It can increase revenue by ensuring customers are willing to pay a fair price for products and services.

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Reduced Costs

It enables businesses to optimize their operations by reducing costs associated with overproduction or underproduction and minimizing the risk of lost sales due to out-of-stock items or delayed orders.

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Challenges of Demand Forecasting

The significant challenges in demand forecasting include the following:

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The dynamic nature of retail

As the retail industry constantly changes, it can take time to predict customer demand accurately.

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Use past sales and trends data to inform their forecasts to combat this problem.

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Identifying and accounting for relevant factors

When making a forecast, it is vital to identify all the relevant factors that could affect customer demand. It includes external factors such as economic conditions or weather patterns and internal factors such as changes in product offerings or marketing campaigns.

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Use predictive analytics tools considering multiple variables when making forecasts.

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Outdated purchasing solutions

Many businesses must rely on updated purchasing solutions, leading to inaccurate forecasts.

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Businesses should invest in modern technology to provide more accurate data and insights into customer demand.

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Related: What are Stockout?

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Lack of standard business processes & miscommunication

Clear communication between departments and standard business processes makes it easier to forecast customer demand accurately.

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Clearly understand their customer's needs and expectations and ensure all departments are working together towards the same goal to solve this issue.

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Supply chain dependencies causing last-minute disruptions

Supply chain disruptions can cause last-minute changes in customer demand, throwing off forecasts if not accounted for properly.

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Work with their suppliers to ensure they have visibility into any potential disruptions so they can adjust their forecasts accordingly to combat this issue.

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Forecasting too low or too high

If businesses are not careful when making their forecasts, they may either underestimate or overestimate customer demand, which could lead to lost revenue or excess inventory costs.

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Use historical data and predictive analytics tools to predict future customer demand accurately before deciding inventory levels or pricing strategies to avoid this.

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Related: How Does Pre-order work: 5 Strategies To Sell More with Pre-orders.

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Conclusion

Demand forecasting is essential for businesses to have in their arsenal when making sound business decisions. By using suitable methods, tools, and processes, companies can ensure they accurately predict customer demand and plan accordingly. It will help them maximize efficiencies, minimize costs associated with overproduction or underproduction, and reduce the risk of lost sales due to out-of-stock items or delayed orders.

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Finally, businesses must remember that demand forecasting is an ongoing process and should regularly adjust their forecasts to remain competitive. It may require investing in better tools and technology, creating standard business processes, or working more closely with suppliers. With the right approach, businesses can make accurate forecasts that will help them stay ahead of the competition.

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Recommended: Best Ways to Reduce Amazon Seller Fees and Increase Profitability

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