Since demand can change capriciously , retailers (and anyone who cares about demand) need to be able to predict what products will or won’t sell and where to send them to at a moment’s notice. This is where short-term Demand Forecasting comes into play. As a subset of the broad and highly customisable method that is Demand Forecasting, short-term forecasts are particularly handy for optimizing your short-term capacity and becoming an agile business in these ever-changing times.
What is Short-Term Demand Forecasting?
Demand Forecasting is a type of data analysis that is used to estimate future demand for products and services. As broad as that sounds, it means that Demand Forecasting is a technique that can be quite flexible depending on what you want to use it to achieve, the kinds of data you have on hand, and the kinds of demand that your products have (and you can find out all about that here). And, this is where short-term Demand Forecasting comes in.
Since Demand Forecasting can vary depending on how far into the future you want to forecast for at a given time, short-term Demand Forecasting is generally used to forecast demand for periods anywhere from 0-3 months at a time. This can be stratified even further by the purpose of the forecast and operational cadence of your business.
Grouped in with short-term forecasting is Demand Sensing, which is specifically used for forecasting on the hourly or daily scale up to 10 weeks into the future.
Why do you need it?
As we mentioned earlier, short-term Demand Forecasting can be used to achieve a host of different things in the short-term - think everything from preparing sales-boosting policies to planning your product distribution. And, these things can be split into two major groups:
Tactical forecasting - think inventory and short-term capacity planning
Operational forecasting - includes planning transportation and production, and inventory deployment
Generally speaking, tactical forecasting is done at the monthly or weekly level, whereas operational forecasts are produced for anywhere from an hour to a few days at a time. In addition to tactical forecasting, monthly and weekly forecasts can also be useful for promotion planning.
Additionally, short-term forecasting can enable you to incorporate factors that you wouldn’t be able to otherwise with long-term forecasting. Variables such as foot traffic, weather data, and other sources where the data is at its most accurate point in the short-term can be included. Plus, it can be especially useful for forecasting demand in the midst or wake of significant events - think everything from financial crises to natural disasters and pandemics.
For instance, let’s consider a retailer selling computer monitors, stationery, and other office equipment during COVID-19. To understand how your customers have been affected by the pandemic (and what that will do to your demand), you can analyze POS sales data, customer orders, web traffic on your website, or any other metrics that are available and capture changes in customer behaviour. And, you can combine this with COVID-related data - think virus trajectory, lockdown periods, and other macroeconomic indicators - to give you an insight into what might happen in the short-term. From this, you might notice that the demand for webcams and headphones start to spike at the start of lockdown periods (and the onset of video conferencing and other joys of working from home). This insight can be useful for deciding how much of a product to send to which location. Whether it’s COVID-19, a financial crisis, or any other large-scale event, injecting this information into your short-term forecasting can increase the predictive power of your models, especially where these events cause major disruptions and make all of your other sales history irrelevant. And forecasting in the short-term during these events can give you the agility to make quick decisions as conditions change.
What You’ll Need & Challenges to Expect
When it comes to creating useful and accurate short-term forecasts, it can be a hard and dangerous road. Lucky for you, there are some tools and tricks that we’ve picked up in our travels and they’re available to you at a price (but, we only accept time spent reading this article and witty comments as payment).
The key thing that you’ll need to create short-term forecasts (or any kind of forecast, really) is data. The bulk of your data is probably going to be historical sales data, but you can also include:
Web analytics
Environment data
Historical shipments and future orders
Competitor pricing
Mobility data
Basically, you should include data that can be used to identify trends and patterns in the demand for your products. For instance, you’ll need to consider seasonality, promotional effects, and even causal factors such as price or the weather when creating your forecasts, and either incorporate them into your forecast (if you’re using statistical methods) or use software (such as Remi’s Demand Forecasting platform) to worry about that for you.