How to Forecast Demand
Demand forecasting is the process that uses historical sales data in order to predict future sales. Often times, demand forecasts are performed as a single component of much larger demand planning initiatives.
The information provided by a demand forecast influences a variety of business operations ranging from supply chain management to inventory management processes.
There are crucial decisions that businesses must make that will have significant short term and long term effects on their entire company.
Gaining a better understanding of future customer demand and estimated sales assists business professionals with making more confident choices about anything from budgeting plans to marketing techniques.
While the results of demand forecasts are not perfect, there are specific ways to increase their reliability. Utilizing historical data and executing a combination of forecasting techniques helps demand forecasting results to be as close to accurate as possible.
Thankfully, there are also many best practice tips available to help businesses undertake demand forecasting processes with greater confidence These best practice tips for how to forecast demand more accurately include-
1. Variable Adjustments
Savvy business professionals know that causation does not always equal correlation. Unfortunately, it is oftentimes much too easy to make a wrong assumption about the relationship between two variables.
Experts recommend staying both curious and vigilant during demand forecasting processes. It is smart to interrogate what variables are influencing your demand planning but it is unwise to rush to unfounded conclusions.
For instance, a business forecasting demand based on historical sales data may not take into consideration significant variations in weather patterns from the previous year. However, if the demand forecasters are inquisitive, they may access historical data on the prior year's weather conditions.
Perhaps the forecasters then discovered that bad weather caused supply chain issues that resulted in an unprecedented inventory management crisis for their business. If the business then forecasts customer demand using that historical data the results of the demand forecast would likely be much more accurate.
2. Intuition and Expertise
While historical data and time series predictions are great tools, sometimes human intuition supersedes even the most advanced forecasting techniques available. Individuals who have been employed at a business long term or are very experienced at demand forecasting are invaluable resources for the demand forecasting process.
However, intuition should be supplemented with sales data and other data points whenever possible. Human bias can be dangerous for businesses, for example, an overly optimistic sales representative or an unrealistic business owner.
While an optimistic and positive employee may be a top talent asset to their business, their attitude can harm the accuracy of forecasting results. Ideally, businesses can find a balance between intuition and more traditional forecasting techniques when predicting future customer demand and estimated sales.
3. Data Reliability
From real time sales data to long term market research forecasting techniques, there are seamlessly endless data sources for demand forecasters to analyze. As demand forecasting techniques become more and more technologically advanced it is more crucial than ever before to utilize data effectively.
Remember, data is only useful to demand forecasts when it is intelligently and appropriately used. Even more crucial than how data is used is the reliability of the data itself.
A simple error in historical data or real time sales data can completely offset an otherwise relatively accurate demand forecast. If that original data error was then left uncorrected or unnoticed, significant demand planning consequences would likely follow.
4. Forecasting Refinement
Demand forecasting and demand planning are both intensive business processes. Business professionals should keep in mind that their demand forecasting and demand planning processes may take some time to adjust to.
When the same forecasting techniques are consistently used, businesses become more and more comfortable using them. Ideally, over time, a company will develop expertise in the forecasting techniques they employ.
When businesses are able to more accurately predict their future customer demand and estimated sales, they will likely make better-informed decisions, objectives, and preparations. As a result, great demand forecasting will benefit a business's bottom line profitability, longevity, and successfulness.
- Demand forecasting is the process used to predict future customer demand and sales by utilizing historical sales data. Demand forecasting is a crucial component of the more comprehensive demand planning process.
- A demand forecast is used for a wide range of business operations from inventory management to supply chain management. Demand forecast results are also helpful for decision making and objective setting.
- Causation does not equal correlation, variables must be thoroughly vetted throughout the demand forecasting process to avoid unfounded conclusions. While time series predictions and historical data provide an abundance of data, experienced human intuition is also a forecasting technique that deserves consideration.
- From long term market research to real time sales data there is not a lack of data sources. Data must not only be reliable but also used correctly. Over time the combination of more effectively used forecasting techniques and intuition can majorly improve a business's demand forecast and demand planning processes.