Demand forecasting is one of the most important business activities. Poor demand forecasting leads to businesses making purchases of products that they can't move, or buying too little product and being unable to meet customer demand, potentially putting their business at risk.
However, many businesses don't do demand forecasting very well. It's often looked at as difficult, requiring a lot of data and a team of analysts. However, that's not true: we're going to show you how with technology and the right forecasting methods, any business can improve their demand forecasting abilities.
Use Statistical Demand Forecasting Methods
Statistical demand forecasting methods are purely quantitative. They take numerical data and use statistical techniques to look at relationships and model future demand.
Time series methods take historical data and use math to project forward in time. It's a way to model future sales by taking what the business has done in the past.
Regression methods take the relationship between inputs and plot them on a line. It's a purely statistical method that will require software suites such as R, as well as enough data on the variables that may affect customer demand. Companies with a lot of data and a need to understand the variables that affect customer demand will use this method.
Use Surveys To Forecast Demand
Survey methods are an excellent way to combine qualitative understanding with raw numbers to help estimate customer demand. So what kind of survey methods are available?
● A simple customer survey, where you ask your customers questions and use what you learn from those questions to make decisions.
● A sample survey, where you take a sample of your target market or current customers and ask them questions. You then use statistics to figure out the probable demand based on the size of your sample.
● Complete enumeration method, where you get information of future purchase plans of all potential customers, then add the total sum of quantities from the customer opinion. This is a highly expensive technique, and difficult to estimate real demand.
● Expert opinion method, where you take either sales representatives or professional market experts and ask them questions based on their experience. Highly limiting, and revolves around subjective experience.
● Delphi method, where multiple expert opinions are taken into consideration to estimate demand. This alleviates some of the issues with subjective experience.
Use the latest in technology.
Social Media: Use The Chatter To Your Advantage
On social media, people are always talking about their opinions on certain products and experiences. You can use analytics and listening tools to figure out trends in what people are saying about your brand, your products, and your product category.
Artificial Intelligence: Smart Machines
In the past five years, businesses have started to lean more heavily on big data to improve their demand forecasting. AI can leverage all kinds of data and learn as the dataset grows, giving you a much wider picture of customer demand than ever before. It allows for demand forecasts based on data sources that most people don't even think about collecting, and thanks to how much data there is, it's how many big companies are forecasting demand.
Internet of Things (IoT): We Are All Connected
This is still nascent technology, but the Internet of Things can help manage inventory with real-time tracking. But that's not all. The IoT can sense demand shifts based on data collected from various difference sources.