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This article was co-written by Michael R. Lewis. Michael R. Lewis is a retired Texas executive, entrepreneur and investment advisor. He has over 40 years of experience in Business & Finance, including the position of Vice President of Blue Cross Blue Shield of Texas. He holds a BBA in Industrial Management from the University of Texas at Austin.
There are 7 references cited in this article that you can see at the bottom of the page.
This article has been viewed 24,234 times.
Making a successful market demand forecast will help you stock enough for the upcoming sale. Demand forecasting is the use of past sales data to determine future consumer demand. With accurate demand forecasting, business operations will be more efficient, customer service will be better, and production times will be reduced. Thanks to it, businesses can avoid high operating costs, lousy customer service and stock shortages. [1] X Research Source
Steps
Collect information
- Focus on the product that generates the most revenue. For example, many businesses uphold the 80/20 rule, which means that in general, 20% of the product or service a business provides generates 80% of the business’s revenue. [3] X Research Resources Identify and track their needs.
- You may have to forecast demand for every existing product. However, each time forecasting a group of several similar products such as gloves, boots and winter hats will be easier and more accurate.
- Consider creating a Sales and Operations Planning team, which includes representatives from each department and is tasked with preparing product demand forecasts.
- If buying from another company, delivery time starts from the time you place the order and ends at the time the item is delivered to your place.
- You can also determine the delivery time by calculating the materials and components of the product. Knowing the lead time required will help you forecast demand more accurately. Focusing on a specific item will help you estimate the amount of materials needed and the product’s lead time.
- Once you have a forecasted output, consider the demand for each product. For example, if manufacturing pencils, you will need to know the amount of wood, rubber and other necessary information based on your estimate. [9] X Research Source
Decide on a market approach
- You can combine multiple methods for more accurate demand forecasting.
- There are several different implementations, mainly depending on the staff. However, you don’t need to use all of the people on the list. Any combination can be chosen to achieve the goal, depending on which group of experts, in your opinion, will provide the most accurate judgment.
- If a small group of target customers love a new technology and respond well to test marketing, you can conclude that that number also predicts national demand. The problem with this approach is that it often collects information about customer opinions rather than demand data.
- This group of methods also includes product life cycles and simulation models.
Using the method of judgment
- Compared to the sales team, these individuals can provide a more in-depth and quality understanding of the market. However, as an outsider, they will not understand the needs for your particular product as well as the company’s employees. You should use these people to forecast market demand and then use insider judgment to estimate the company’s likelihood of success in that market.
- Pre-determine a breakpoint, such as a specific number of rounds, consensus score, or consistency in results.
Use the experimental method
- Customers are the ones who best understand the demand for a certain product. The danger of these investigations is that they often exaggerate real demand. While a person may be interested in a product, actually buying it is another matter.
- Remember that conducting an investigation can be expensive, difficult, and time consuming. Surveys rarely provide a foundation for successful demand forecasting.
- As with other types of experiments, it can be difficult to forecast demand from these results.
Use the contact/cause-and-effect method
- For example, if you sell boots, your sales may have been especially high during the cold winters. If this year is forecast to have such a cold winter, you should increase your demand forecast accordingly.
- This model is most commonly used in some industries such as high technology, fashion and short life products. What makes it special is that the source of demand is directly related to the product life cycle.
- These models are known for being difficult and slow to build and maintain.
Using the timeline method
- For example, forecast = (4,000 (January) + 6,000 (February) + 8,000 (March)) /4 = 4,500.
- For example, WMA = (4 * 100) + (4 * 250) + (4 * 300) = 2,600.
- Use a larger density constant for new data and smaller for older data. That’s because new data has a stronger influence on forecast results.
- Find forecasts for previous periods. In the formula, it is denoted by (Ft). Next, find the actual demand in that period, denoted by (At-1).
- Decide on the weights to be used. It is (W) in the formula, with a value between 1 and 10. Use a smaller number for older data.
- Substitute data into the formula: Ft = Ft-1 + W * (At-1 – Ft-1) or for example: Ft = 500 + 4(W) * (590 – 500) = 504 * 90 = 45,360.
Demand forecast
- Also, go back and determine exactly how you believe the prediction will be. Are you overly optimistic with your own forecasts? How big is your expected margin of error?
This article was co-written by Michael R. Lewis. Michael R. Lewis is a retired Texas executive, entrepreneur and investment advisor. He has over 40 years of experience in Business & Finance, including the position of Vice President of Blue Cross Blue Shield of Texas. He holds a BBA in Industrial Management from the University of Texas at Austin.
There are 7 references cited in this article that you can see at the bottom of the page.
This article has been viewed 24,234 times.
Making a successful market demand forecast will help you stock enough for the upcoming sale. Demand forecasting is the use of past sales data to determine future consumer demand. With accurate demand forecasting, business operations will be more efficient, customer service will be better, and production times will be reduced. Thanks to it, businesses can avoid high operating costs, lousy customer service and stock shortages. [1] X Research Source
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