5 Best Practices for Demand Forecasting

The science of forecasting involves making predictions. Supply chain management is aided by demand forecasting, which gauges demand for goods and services. Various sectors use it, including retail, eCommerce, manufacturing, and wholesale.

Data sources like business intelligence insights, sales history, seasonality, market research data, and supplier lead times are used as forecasting inputs. Knowing what constitutes a reasonable prediction can make all the difference in the success of your business.

Demand forecasting is a challenging task with a high error rate. People who predict your customers’ purchasing behavior are often wrong in their forecasts. But occasionally, they are correct. And in those cases, they have prevented you from buying too much or too little, which would have resulted in out-of-stock situations.

Although vital, their work is incredibly challenging. We’ll go through a few demand forecasting best practices to assist you in doing your work more effectively. You may enhance profit margins and lower inventory expenses by forecasting demand correctly. But, let’s first define demand forecasting.

What Is Demand Forecasting?

Demand forecasting is estimating and predicting future consumer demand for a good or service using predictive analysis of previous data. By evaluating future sales and revenue, demand forecasting assists the company in making more educated supply decisions.

Organizations may use demand forecasting to maximize inventory by utilizing previous sales data to estimate future sales. It allows them to make well-informed decisions, from managing inventory and warehousing requirements to running flash sales and satisfying consumer expectations.

The Best Practices for Demand Forecasting

Make sure your demand forecasting methods are efficient and scalable to position yourself for success. To help you get started, consider the following five demand forecasting best practices.

Create a Repeatable Monthly Process

A consistent, monthly procedure that evaluates past forecasts and contrasts them with actual market outcomes is necessary to improve demand forecasting accuracy.

You will gather information about when your predictions were accurate or inaccurate, as well as the state of the market. Then you can assess the top 20% to ascertain why you were incorrect and how to be correct the next time by sorting those “variances” (when you were right or wrong) from the maximum to the lowest.

Maintain Accurate, Real-Time Data

It is a recipe for disaster to create a demand strategy with wrong or inadequate data. Verify your calculations are accurate before taking any action. Implement a dependable and efficient data collection process in the future.

You should combine all the information from every sales channel for each product if you have numerous channels, such as an omnichannel eCommerce approach.

If you lack accurate data, you cannot estimate demand with any degree of accuracy. The best techniques for demand forecasting center on current sales, inventories, raw materials, and other data.

You will require data that is as current as feasible to produce wise forecasts, avoid calculating demand with any incomplete data points, and continuously anticipate demand monthly or weekly with new data.

How can you monitor your financial, POS, and stock data on the same platform? Use a data management and reporting platform like ClicData that works with all of your business software.

Implement a Future-Proof Demand Planning Tool

Automation and machine learning are two examples of AI technologies that are rapidly evolving. We don’t necessarily think that demand planner roles will be taken over by robots anytime soon. However, this kind of technology has the potential to fundamentally change how we view supply chain management as a whole and will continue to play an increasingly important role in the future. Demand forecasters must be ready.

Because of this, ensure your demand forecasting tools are adaptable. Consider more than just how your software utilizes the most recent advanced sophisticated analytics. Consider whether it can accommodate new developments. For instance, how quick and straightforward are software updates to install? Your demand forecasting tools should be able to develop and help you for years to come, regardless of the solution you’ve adopted.

Understand Your Markets and the Current Macroeconomic Trends

It’s simple to overlook taking a step back and considering the broader picture while you’re in the thick. Stock levels and the volume of SKUs sold are two examples of internal demand markers that are essential data factors that shouldn’t be overlooked. However, they also don’t fully convey the narrative.

According to Gartner, only 17% of research participants said they predict demand at the customer planning, location, and SKU levels. It is a problem because increasing client demands are one of the leading causes of demand volatility.

Our world has become much smaller thanks to technological breakthroughs than it was ten years ago. And this is a pattern that will undoubtedly persist. Neither your customers nor your supply chains are local; they are both global. Understand how your products are doing on the worldwide market. Watch out for your rivals. Additionally, be aware of how macroeconomic trends could affect the business you conduct locally.

Lastly, you will be able to comprehend the error’s origin better and enhance your workflow if you evaluate demand errors at the customer level.

Final Word

There is no business if there is no demand. Companies cannot make wise selections if they do not grasp the market. Successful sales management is built on accurate demand forecasting. Your team’s resources, time, and money will be used to the fullest extent possible.

Your capacity for forecasting, operational processes, and marketing will all be enhanced by a strong demand prediction. You’ll succeed in sales if you succeed in demand forecasting.

Even though we regrettably lack a crystal ball to see into and predict what the future may bring, we are sure that these demand forecasting best practices will remain helpful in any scenario.

To learn more about demand forecasting best practices or how you can accurately predict demand using data, tune into ClicData for all the latest information. 


You will also like:

Share this on