Different Types of Demand Forecasting

It's difficult to run a business, isn't it? You never know how things will turn out, but you must be able to answer questions like these:

 

• How many inventory units do you need to keep on hand for each SKU to be fully stocked?

 

• How frequently do you expect to replenish inventory?

 

• How will those forecasts evolve over time?

 

• Where do you see yourself in a year?

 

Okay, so you may only have a hazy understanding of product demand. That is perfectly acceptable! Forecasting projections is one of the most difficult tasks to master.

 

Demand forecasting is a combination of two words, the first of which is demand and the second of which is forecasting. Forecasting, in general, means making an approximation in the present for an event that will occur in the future.

 

These forecasts are used by all companies to shape their marketing and sales strategies. It makes a significant contribution to their profit margins.  Even if you've been doing it for a while and are getting the hang of it, your projections will shift again. We've got you covered in this article, whether you know everything or very little about it.

 

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What is Demand Forecasting?

 

The process of estimating future customer demand based on available historical sales data is referred to as demand forecasting. Demand forecasting, like sales forecasting, is an important business management process that provides numerous benefits to a company.

 

Business professionals frequently employ both qualitative and quantitative forecasting methods. The best forecasting method, or a combination of forecasting methods, is determined by specific business objectives and deadlines.

 

Demand forecasting has a significant impact on both strategic planning and business management. Demand forecasting has an impact on both short and long-term business objectives, ranging from supply chain management to capacity planning.

 

Demand forecasting methods developed by modern technology are more advanced and accurate than ever before. Large corporations that recognize the incredible value of proper demand forecasting are embracing automated machine learning and algorithmic predictions.

 

Types of Demand Forecasting

 

Demand forecasting can be done in a variety of ways. Depending on the forecasting model you use, your forecast may differ. It is best practice to conduct multiple demand forecasts. This will provide you with a more complete picture of your future sales.

 

Using multiple forecasting models can also highlight discrepancies in predictions. These differences may indicate a need for additional research or better data inputs. below are types of demand forecasting

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Types of demand forecasting

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1. Passive demand forecasting

 

The most basic type is passive demand forecasting. In this model, you use past sales data to forecast the future. This is especially true if your business experiences seasonal fluctuations.

 

If you have solid sales data to work with, the passive forecasting model works well. Furthermore, this is a good model for businesses that prefer stability overgrowth. It's a strategy that assumes this year's sales will be roughly the same as last year's sales. And it is easy to use than others

 

2. Active demand forecasting

 

Active demand forecasting is a good option if your company is growing or if it is just getting started. Your market research, marketing campaigns, and expansion plans are all taken into account by an active forecasting model.

 

Externals are frequently factored into active projections. The economic outlook, growth projections for your market sector, and projected cost savings from supply chain efficiencies are all factors to consider. Startups with less historical data to draw on will have to make assumptions based on external data.

 

3. Short term projection
    

Short-term demand forecasting is limited to the next three to twelve months. This can help you manage your just-in-time supply chain. When you look at short-term demand, you can adjust your projections based on real-time sales data. It enables you to react quickly to changes in customer demand. 

 

Understanding short-term demand is critical if you manage a product lineup that changes frequently. However, for most businesses, a short-term forecast is only one piece of a larger puzzle. With medium- or long-term demand forecasting, you'll probably want to look further out.

 

4. Long-term project

 

Your long-term forecast will make predictions one to four years in advance. This forecasting model is concerned with shaping your company's growth trajectory.  While your long-term strategy will be influenced by sales data and market research, it will also be aspirational.

 

Consider a long-term demand forecast to be a road map. You can plan your marketing, capital investments, and supply chain operations using this forecasting technique. This will assist you in preparing for future demand. Being prepared for your company's growth is critical to its success.

 

5. External Macro Forecasting

 

External macro forecasting takes into account broader economic trends. This forecast considers how those trends will affect your objectives. An external macro demand forecast can also point you in the right direction for achieving your objectives.

 

Your company might be more concerned with stability than with expansion. However, taking into account external market forces is still necessary for your sales projections. External macro forecasts can also include information about the availability of raw materials and other factors that will have a direct impact on your supply chain.

 

6. Internal Macro Forecasting

 

Internal capacity is one of the factors limiting your company's growth. Does your company have the capacity to meet the demand if you predict that customer demand will double? Forecasts of internal business demand examine your operations.

 

Internal business forecasting will reveal constraints that may stifle your growth. It can also point out untapped opportunities within the organization. This forecasting model takes your company's financing, cash on hand, profit margins, supply chain operations, and personnel into account.

 

Internal business demand forecasting is a valuable tool for making accurate projections. It can also point you in the direction of areas where you need to build capacity in order to meet your expansion objectives.

 

Also Read | An Essential Guide to Inventory Management

 

 

Need for Demand Forecasting

 

Demand is critical in business decision-making. In a competitive market, it is critical to make sound business decisions and plan for future events such as sales, production, and so on. The accuracy of a decision made by a business manager determines its effectiveness.

 

Demand is the most important factor in a business's ability to achieve its goals. Many business decisions, such as production, sales, and staffing requirements, are influenced by demand. Forecasting is a requirement of business on both an international and domestic scale.

 

Demand forecasting lowers the risk associated with business activities and enables it to make more informed decisions. Forecasting has become increasingly important for firms that produce in large quantities. A good forecasting system aids a company in better planning for its business objectives.

 

Forecasting plays an important role in many functional areas of accounting. A good forecast aids inappropriate production planning, process selection, capacity planning, facility layout planning, and inventory management, among other things.

 

Demand forecasting provides useful information for capital investment and expansion decisions within an organization. It also allows for the development of appropriate pricing and advertising strategies.

 

 

Examples of Demand Forecasting

 

Example 1: A major automaker refers to the previous 12 months of actual sales of its vehicles at the model, engine type, and color level, and forecasts the short-term demand for the next 12 months for purchase, production, and inventory planning purposes based on the expected growth.

 

A leading food manufacturing company refers to the last 24 months of actual sales of its highly seasonal products such as soups and mashed potatoes. A flavor and packaging size analysis is performed. 

 

Then, based on market potential, demand is forecasted for the next 12 to 24 months for sourcing key ingredients such as tomatoes, potatoes, and so on, as well as capacity planning and evaluating the need for external co-packing.

 

Example 2: A new direct-to-consumer cosmetics brand is rapidly expanding. Currently, 10,000 orders are sold per month. Based on previous sales data, upcoming ad campaigns, and general industry market conditions, they anticipate exceeding 30,000 orders per month by this time next year.

 

Currently, they have 75,000 units in stock at various levels across their five SKUs. Their order volume varies greatly depending on their replenishment cycle, and they restock inventory at the SKU level every 90 days.

 

The average number of units they store will increase rapidly while the cadence will remain constant. Their main SKU's last run was 30,000 units. They're about to ship another 50,000 units, and the next batch will be 75,000.

 

They intend to keep growing at that rate, so they are investigating whether they should buy land, lease a warehouse, or outsource fulfillment to keep up with demand.

 

Example 3: A grocery store examines sales trends from the previous Thanksgiving week in order to plan adequate inventory levels for the upcoming season. They look at sales for seasonal products like turkeys, cranberries, and mashed potatoes in the weeks leading up to that week last year.

 

For them, it was a fantastic holiday sale. However, a competing grocery store opened four blocks away eight months ago, so they are unsure how Thanksgiving demand will be affected and whether local customers will buy ingredients from their competitor.

 

At the same time, a lot of families are still moving into the neighborhood, and it has grown by an average of 1% month over month since the competing chain opened.

 

They intend to run a few more ads than last year through channels that have previously yielded a good ROI for them, as well as offer some new deals, in order to position themselves as the go-to Thanksgiving destination. Sales are expected to increase by 5% over last year, according to their calculations.

 

Also Read | A Guide to Demand and Supply Analysis

 

Demand Forecasting Methods

 

Below are methods of demand forecasting :

 

1. Predictive Analysis

 

The predictive analysis goes beyond traditional demand forecasting by examining why people buy. Predictive analysis, like traditional forecasting, will determine future demand but will also identify the reason for this.

 

This analysis is then used as a framework to identify the factors that influence consumer purchases and provide insights into why these people buy. Simulation and predictive analytics capabilities may be available in advanced planning and scheduling software (APS) systems.

 

These solid demand planning and forecasting components can predict with a high degree of certainty, allowing schedules, production plans, inventory, and staffing to be secured and allocated for production.

 

2. Conjoint Analysis

 

The conjoint analysis uses surveys to gather consumer feedback on the most appealing features of their products. These surveys ask consumers how they would use and respond to specific product attributes.

 

When selling a product, it is critical to recognize the most important features that customers consider when purchasing. Conjoint analysis can help the company go beyond demand forecasting by identifying the products that are most appealing to consumers.

 

This is accomplished by having customers rank their preferences for features, which is then translated by analysis into a report that shows what customers prefer. The technique provides a forecast of market preferences in order to investigate the market potential for new products or features.

 

3. Client Intent Survey

 

A buyer's intentions survey asks the consumer what they intend to buy in the future. This technique is used to determine what motivates a customer to purchase a product that they are interested in.

 

It is important to note that while client intent surveys can help predict the likelihood of purchasing, they do not always accurately reflect actual purchasing behavior.

 

Purchase intent, however, is a better predictor of actual purchase for existing vs. new products, for durable products, and for short-term forecasting horizons rather than long-term forecasting horizons, according to research.

 

This technique is still a useful component of demand forecasting because it takes into account input from the people who will actually buy the product - the customers.

 

4. Delphi Method

 

The Delphi method was created on the premise that group forecasts are generally more accurate than individual forecasts. A panel of experts is tasked with creating a Demand Forecast.

 

Each expert is tasked with developing a forecast for their assigned segment. Following the initial forecasting round, each expert reads out their forecast, and each expert is influenced by other experts in the process. All experts then make a subsequent forecast, and the process is repeated until all experts have reached a near-consensus scenario.

 

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Forecasting is useful to businesses because it allows them to make more informed business decisions and develop data-driven strategies. Financial and operational decisions are made in light of current market conditions and projections for the future.