Inventory Management Tips: How to Forecast Demand for Your Retail Store

Here’s a fun fact. Did you know that Amazon earns more than one-fifth of its retail revenue in North America because local stores can’t forecast their sales accurately? This happens when customers try to purchase the product at a physical store, but those stores are out-of-stock, so what does the customer end up doing, they go look to buy it on Amazon.

Clearly, forecasting essential, but we should note that it’s more than just predicting the demand for your products. Demand forecasting also helps businesses effectively manage cash flow and maintain lean operations. If you’re carrying extra stock or don’t have enough to meet demand, you’re losing money.

What is demand forecasting?

In retail terms, demand forecasting is the practice of predicting which products and how many of them customers will buy over a specific period of time. Demand forecasting is typically done using historical data (if available) as well as external insights (ex. weather, consumer trends, etc.).

Forecasting customer demand helps retailers understand when they need to order new merchandise for certain products, and how much they’ll need to order. When determining this timeframe, you’ll need to consider the necessary lead time to help inform your reorder point.

How to forecast inventory demand

Understanding how to forecast inventory demand may be a little intimidating at first glance, and for good reason. It can be a complicated process, and it’s difficult to get it right. But, with the proper tools and approach, you can make the process much easier for your store.

Demand forecasting methods and techniques

There are several forecasting methods and techniques, some of which can be used simultaneously. Mainly, though, forecasting for demand can be broken down into four main types:

    Qualitative
    Time series analysis
    Causal
    Simulation

Qualitative forecasting: This is an estimation method that uses expert judgment, rather than numerical analysis. This type of forecasting relies upon the knowledge of highly experienced employees and consultants to provide insights into future outcomes. Rather than just using historical data alone, as in a quantitative approach, qualitative forecasting accounts for different factors that will impact future customer sales demand.

Time series analysis: The time series analysis for demand forecasting skews closer to the quantitative approach that comprises of methods for analyzing time series data in order to extract more meaningful statistics and other characteristics of the data your looking into. Time series forecasting is the used to predict future values based on previously observed values.
 
Causal: Causal forecasting will pay closer attention to the relationship between different events or variables. For example, the weather. Estimating techniques based on the assumption that the variable to be forecast (dependent variable) has cause-and-effect relationship with one or more other (independent) variables.

Examining causal relationships helps your business forecast more accurately because you can better predict and account for external factors that affect customer sales demand. 

Simulation: Simulation forecasting is the approach where all methods are mixed together. It accounts for both qualitative and quantitative insights to provide a more holistic outlook on demand. However, this is also arguably the most complicated demand forecasting technique to DIY, because of its complicated nature. Simulation also accounts for internal and external factors — those elements identified in your causal forecasting.

If you’re new to demand forecasting, one of the first things you’ll want to do is establish a baseline. Without data, it’s difficult to make informed forecasting decisions and predictions.

To better forecast demand so you can better manage inventory and customer sales demand, it’s most important to understand your customer well and their shopping tendencies.

Some things to think about are:

1.    Do my customers shop seasonally or is it consistent year round?
2.    What sizes and/or colors do my customers prefer?
3.    Are shoppers partial to certain brands?
4.    What do shoppers in my local area like?
5.    How quickly do trends catch on with consumers in my store’s area?

Analyze your Retail Sales KPIs

One of the key metrics of the forecasting process is sell-through rate, which is the percentage of non-clearance items that you will sell in relation to on-hand product for a given time period. Identify the right sell-through rate and forecast demand, retailers often work collaboratively with suppliers to forecast demand (and their purchases) based on market information they might have along with promotional plans.

Leverage technology and automation to increase accuracy

15% of inventory distortion issues happen because various pos software solutions can’t talk to each other properly. And when retailers don’t use tech the right way, they are way more susceptible to data discrepancies caused by human error.

Invest in an all-in-one point of sale & Inventory management system

No matter how big or small your retail store is or how many stores you operate, investing in technology will not only save you an incredible amount of money on mistakes, but it will make your business so much more and increase profits like never before. 

A great point of sale system with inventory management, customer management, loyalty programs, a mobile pos system, reporting, and all the latest pos hardware equipment working together and in the cloud is highly recommended. 

One such recommendation is Vend, who is one of America’s leading point of sale software systems with the best pos inventory management software systems retailers all over the world love to use that will be great for your customer demand forecasting too. No matter what your retail challenges are, you will find great comfort in Vend. You can also try out their pos system free for 30-days too with no obligation either.