How to Forecast Demand the Right Way For any business that deals with the public, it's essential to have a way to predict the demand for products or services.
By Peter Daisyme Edited by Dan Bova
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For any business that deals with the public, it's essential to have a way to predict the demand for products or services. Knowing how many customers you'll have over the course of a given day will help you as you order inventory and schedule staff to accommodate the customers that arrive. Even online businesses need to be able to predict customer demand in order to prepare.
But as many businesses have discovered, there are methods for demand forecasting that can make it more accurate and less of a headache. I've had to deal with this on a daily basis for our products and services. What if we order to much, or even worse, too little to keep up with demand.
Here are a few ways to improve your business's demand forecasting efforts.
Use the right numbers.
Big data may be the hottest trend in business today but as Duetto Research points out in its blog, "8 Steps to Improving Data Forecasts," those numbers are only as good as the information feeding it. It's important that you hone-in on the numbers that give you the information you need to make decisions.
Related: How to Anticipate Cash-Flow Problems
In this case, you're looking for information on pricing trends and demand for certain products. If, for instance, you want to see how many people shopped in your store on a specific day in order to meet that demand, you should narrow down your data to those days. It's important that your system feed that information accurately throughout the year so that when you're ready to review the numbers, you have the right information.
Adjust for variables.
There are many factors that go into a business's daily interactions with customers. When a business is estimating customer traffic, that business may go straight to last year's numbers to see what those numbers were on that day a year ago. However, there could have been other variables not reflected in those numbers, such as weather or different economic conditions in the area.
Being aware that these variables can exist is the first step. If you aren't capturing information about those variables, you begin to question sudden spikes or drops in customer activity and question what might have been the cause. You can likely research historical data like weather and realize that you may not have the same customer interactions this year as you have in previous years.
Know your business.
As great as statistical data is, sometimes your intuition tells you it's going to be a busy day. Once you've been in business for a while, you begin to learn more about your own customers. Over time, this allows you to sometimes make an educated guess when it's going to be a busy day. You may also have a greater understanding of your local area than any statistical software ever could. You know your neighborhood and surrounding areas and this knowledge can sometimes lead you to make decisions that go against what the numbers say.
Related: The Biggest Mistake Is Ignoring the Law of Supply and Demand
For best results, employ a combination of data, analytics and customer awareness to forecast demand for your business. You'll have better results and your customers will notice that you're interested in the products they want you to keep in stock.
Constantly refine.
Demand forecasting is an always-evolving practice, with businesses learning as they go. Data science has only recently become readily available to smaller businesses on a larger scale, so many SMBs are still learning to put it to use.
Each year, you'll reevaluate your demand forecasting efforts and refine them to be more accurate. You'll also learn to capture additional data as you go that will help you better understand your customers. As a result, you'll have a customer-focused business that strives to constantly provide better service to consumers.
The best way to make sure you can handle customer demand is to study business activity and identify trends based on historical information. While demand forecasting is a great way to accomplish this, it's not a perfect science, so it's important to listen to your own instincts, as well.
Related: Show Your Work: Letting a Great Product Sell Itself
